International Journal of Computational Intelligence Systems
Volume 14, Issue 1, 2021
1. Deep Learning-Based Short-Term Load Forecasting for Transformers in Distribution Grid
Renshu Wang, Jing Zhao
Pages: 1 - 10
Load of transformer in distribution grid fluctuates according to many factors, resulting in overload frequently which affects the safety of power grid. And short-term load forecasting is considered. To improve forecasting accuracy, the input information and the model structure are both considered. First,...
2. Stability and Stabilization Condition for T-S Fuzzy Systems with Time-Delay under Imperfect Premise Matching via an Integral Inequality
Zejian Zhang, Dawei Wang, Xiao-Zhi Gao
Pages: 11 - 22
This paper focuses on the stability and stabilization analysis for the T-S fuzzy systems with time-delay under imperfect premise matching, in which the number of fuzzy rules and membership functions employed for the fuzzy model and fuzzy controller are different. By introducing an augmented Lyapunov-Krasovskii...
3. Emotion Recognition from Speech: An Unsupervised Learning Approach
Stefano Rovetta, Zied Mnasri, Francesco Masulli, Alberto Cabri
Pages: 23 - 35
Speech processing is quickly shifting toward affective computing, that requires handling emotions and modeling expressive speech synthesis and recognition. The latter task has been so far achieved by supervised classifiers. This implies a prior labeling and data preprocessing, with a cost that increases...
4. Multi-folded N-Structures with Finite Degree and its Application in BCH- Algebras
Jeong-Gon Lee, Kul Hur, Young Bae Jun
Pages: 36 - 42
The generalization of N-structure is introduced first and then applied to BCH-algebra for research. The concepts of k-folded N-subalgebra, k-folded N-closed ideal and (closed) k-folded N-filter are introduced, and then their relations and several properties are investigated. Conditions for the k-folded...
5. An Extended Three-Stage DEA Model with Interval Inputs and Outputs
Guo-Qing Cheng, Liang Wang, Ying-Ming Wang
Pages: 43 - 53
The traditional three-stage data envelopment analysis (DEA) model only measures exact input–output indicator data, but cannot perform efficiency analysis on uncertain data. The interval DEA method does not exclude the influence of external environmental factors. Therefore, this paper combines the traditional...
6. An Adaptive Multi-Objective Evolutionary Algorithm with Two-Stage Local Search for Flexible Job-Shop Scheduling
Yingli Li, Jiahai Wang, Zhengwei Liu
Pages: 54 - 66
An adaptive evolutionary algorithm with two-stage local search is proposed to solve the multi-objective flexible job-shop scheduling problem (MOFJSP). Adaptivity and efficient solving ability are the two main features. An autonomous selection mechanism of crossover operator is designed, which divides...
7. New Framework for FCMs Using Dual Hesitant Fuzzy Sets with an Analysis of Risk Factors in Emergency Event
Zengwen Wang, Jian Wu, Xiaodi Liu, Harish Garg
Pages: 67 - 78
As a kind of soft computing tool with strong knowledge representation and causal reasoning ability, fuzzy cognitive maps (FCMs) is a product of fuzzy logic and neural network. A limitation of the current FCMs method is its inability to model the uncertainty that is introduced into a complex system due...
8. Three-Dimensional Multi-Mission Planning of UAV Using Improved Ant Colony Optimization Algorithm Based on the Finite-Time Constraints
Weiheng Liu, Xin Zheng
Pages: 79 - 87
An improved ant colony optimization (IACO) is proposed to solve three-dimensional multi-task programming under finite-time constraints. The algorithm introduces the artificial preemptive coefficient matrix into the transfer probability formula, which makes results convergence and also reduces the convergence...
9. Underwater Image Restoration and Enhancement via Residual Two-Fold Attention Networks
Bo Fu, Liyan Wang, Ruizi Wang, Shilin Fu, Fangfei Liu, Xin Liu
Pages: 88 - 95
Underwater images or videos are common but essential information carrier for observation, fishery industry and intelligent analysis system in underwater vehicles. But underwater images are usually suffering from more complex imaging interfering impacts. This paper describes a novel residual two-fold...
10. Fault Tree Construction Model Based on Association Analysis for Railway Overhead Contact System
Kaiyi Qian, Long Yu, Shibin Gao
Pages: 96 - 105
The overhead contact system (OCS) is the power source of electrified railway, it is very important to evaluate the system status accurately to maintain its safe and stable operation. At present, fault tree analysis is the main method of reliability assessment for OCS. Existent methods to establish the...
11. Dictionary Learning Approach to Monitoring of Wind Turbine Drivetrain Bearings
Sergio Martin-del-Campo, Fredrik Sandin, Daniel Strömbergsson
Pages: 106 - 121
Condition monitoring is central to the efficient operation of wind farms due to the challenging operating conditions, rapid technology development, and a large number of aging wind turbines. In particular, predictive maintenance planning requires the early detection of faults with few false positives....
12. Pyramidal Nonlocal Network for Histopathological Image of Breast Lymph Node Segmentation
Zehra Bozdağ, Fatih M. Talu
Pages: 122 - 131
The convolutional neural networks (CNNs) are frequently used in the segmentation of histopathological whole slide image- (WSI) acquired breast lymph nodes. The first layers in deep network architectures generally encode the geometric and color properties of objects in the training set, while the last...
13. α-consensus Value of Cooperative Game with Intuitionistic Fuzzy Payment
Jiang-Xia Nan, Jing Guan, Mao-Jun Zhang
Pages: 132 - 139
This paper studies the α-consensus value of a cooperative game with payoffs of triangular intuitionistic fuzzy numbers and gives the formation mechanism of the α-consensus value, as well as some properties. Using the extended Hukuhara difference of triangular intuitionistic fuzzy numbers, the α-consensus...
14. Semi-Supervised Density Peaks Clustering Based on Constraint Projection
Shan Yan, Hongjun Wang, Tianrui Li, Jielei Chu, Jin Guo
Pages: 140 - 147
Clustering by fast searching and finding density peaks (DPC) method can rapidly identify the centers of clusters which have relatively high densities and high distances according to a decision graph. Various methods have been introduced to extend the DPC model over the past five years. DPC was originally...
15. Characterization of Uninorms on Bounded Lattices and Pre-order They Induce
Dana Hliněná, Martin Kalina
Pages: 148 - 158
In Hliněná et al., Pre-orders and orders generated by uninorms, in 15th International Conference IPMU 2014, Proceedings, Part III, Montpellier, France, 2014, pp. 307–316 the authors, inspired by Karaçal and Kesicioğlu, A t-partial order obtained from t-norms, Kybernetika. 47 (2011), 300–314, introduced...
16. A Novel Target Searching Algorithm for Swarm UAVs Inspired From Spatial Distribution Patterns of Plant Population
Xiaoming Zhang, Yongqiang Hu, Tingjuan Li
Pages: 159 - 167
Like some social animal groups, the evolution of plant populations in nature also contains swarm intelligence. Aiming at the problem of swarm Unmanned Aerial Vehicles (UAVs) target searching in complex and unknown environments, this paper explores search models suitable for swarm UAVs by investigating...
17. An Uncertain and Preference Evaluation Model with Basic Uncertain Information in Educational Management
Cheng Zhu, Er Zi Zhang, Zhen Wang, Ronald R. Yager, Zhi Song Chen, Le Sheng Jin, Zhen-Song Chen
Pages: 168 - 173
Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This study proposed a two-level comprehensive evaluation...
18. An Extended TODIM Method with Unknown Weight Information Under Interval-Valued Neutrosophic Environment for FMEA
Jianping Fan, Dandan Li, Meiqin Wu
Pages: 174 - 186
Failure mode and effect analysis (FMEA) is a powerful risk assessment tool to eliminate the risk and improve the reliability. In this article, a novel risk priorization model based on extended TODIM (an acronym in Portuguese of interactive and multiple attribute decision-making) method under interval-valued...
19. Online Handwritten Arabic Scripts Recognition Using Stroke-Based Class Labeling Scheme
Rabiaa Zitouni, Hala Bezine, Najet Arous
Pages: 187 - 198
With the increasing availability of pen-based user interfaces, we often come upon multiple data sets of online handwritten scripts such as letters, words, etc., that are collected based on a viable interface. In this paper, we set forward a new method for online handwritten Arabic scripts recognition....
20. Using CFW-Net Deep Learning Models for X-Ray Images to Detect COVID-19 Patients
Wei Wang, Hao Liu, Ji Li, Hongshan Nie, Xin Wang
Pages: 199 - 207
COVID-19 is an infectious disease caused by severe acute respiratory syndrome (SARS)-CoV-2 virus. So far, more than 20 million people have been infected. With the rapid spread of COVID-19 in the world, most countries are facing the shortage of medical resources. As the most extensive detection technology...
21. A Novel Probability Weighting Function Model with Empirical Studies
Sheng Wu, Hong-Wei Huang, Yan-Lai Li, Haodong Chen, Yong Pan
Pages: 208 - 227
Probability weighting is one of the key components of the modern risky decision-making theories, an effective probability weight function can more accurately describe the decision-makers' subjective response to the event probability. While the probability weighting functions (PWFs) with several...
22. Parallel DNA Algorithms of Generalized Traveling Salesman Problem-Based Bioinspired Computing Model
Xiaomin Ren, Xiaoming Wang, Zhaocai Wang, Tunhua Wu
Pages: 228 - 237
Generalized traveling salesman problem (GTSP) is a classical combinatorial optimization problem, in which the optimization goal is the minimum route combination. Since the GTSP is a more complex problem than the traveling salesman problem (TSP), the GTSP can be considered an extension of the TSP. At...
23. A Simulation Method of Specific Fish-Eye Imaging System Based on Image Postprocessing
Wenhui Li, You Qu, Ying Wang, Jialun Liu
Pages: 238 - 247
In order to enable the implementation of the computer vision-based perception techniques in the physical-based simulation environment, visual sensors need to be simulated physically. Among others, fish-eye cameras are commonly used visual sensors to provide an omni-directional field of view. The existing...
24. Quantum Clustering Ensemble
Peizhou Tian, Shuang Jia, Ping Deng, Hongjun Wang
Pages: 248 - 256
Clustering ensemble combines several base clustering results into a definitive clustering solution which has better robustness, accuracy, and stability, and it can also be used in knowledge reuse, distributed computing, and privacy preservation. In this paper, we propose a novel quantum clustering ensemble...
25. Feature-Weighting and Clustering Random Forest
Zhenyu Liu, Tao Wen, Wei Sun, Qilong Zhang
Pages: 257 - 265
Classical random forest (RF) is suitable for the classification and regression tasks of high-dimensional data. However, the performance of RF may be not satisfied in case of few features, because univariate split method cannot bring more diverse individuals. In this paper, a novel method of node split...
26. User Community Detection From Web Server Log Using Between User Similarity Metric
M. S. Bhuvaneswari, K. Muneeswaran
Pages: 266 - 281
Identifying users with similar interest plays a vital role in building the recommendation model. Web server log acts as a repository from which the information needed for identifying the users and sessions (pagesets) are extracted. Sparse ID list and Vertical ID list are used for identifying the closed...
27. Differential Calculus of Fermatean Fuzzy Functions: Continuities, Derivatives, and Differentials
Zaoli Yang, Harish Garg, Xin Li
Pages: 282 - 294
Fermatean fuzzy sets are an effective way to handle uncertainty and vagueness by expanding the spatial scope of membership and nonmembership of the intuitionistic fuzzy set and the Pythagorean fuzzy set. However, existing studies only analyzed the discrete information and neglected the continuous state...
28. Novel Complex T-Spherical Fuzzy 2-Tuple Linguistic Muirhead Mean Aggregation Operators and Their Application to Multi-Attribute Decision-Making
Peide Liu, Zeeshan Ali, Tahir Mahmood
Pages: 295 - 331
Complex T-spherical fuzzy 2-tuple linguistic set (CTSF2-TLS), which is a combination of complex fuzzy set (CFS), T-spherical fuzzy set (TSFS), and 2-tulpe linguistic variable set (2-TLVS), is a proficient technique to express uncertain and awkward information in real decision-making. CTSF2-TLS contains...
29. Decision-Making Analysis Under Interval-Valued q-Rung Orthopair Dual Hesitant Fuzzy Environment
Sumera Naz, Muhammad Akram, Samirah Alsulami, Faiza Ziaa
Pages: 332 - 357
Interval-valued dual hesitant fuzzy set (IVDHFS) as an extended structure of hesitant fuzzy set (HFS), interval-valued HFS and dual hesitant fuzzy set (DHFS) has been developed and applied in multi-attribute decision-making (MADM) problem. While deciding the membership degree (MD) and nonmembership degree...
30. A Textural Distributions-Based Detection of Hazelnut Axial Direction
Wenju Zhou, Fulong Yao, Songyu Luan, Lili Wang, Johnkennedy Chinedu Ndubuisi, Xian Wu
Pages: 358 - 366
Since the shell of the hazelnuts is very hard, it is necessary to squeeze the slit in the axial direction to facilitate peeling. When the hazelnuts are automatically processed in the industry chain, the axial of the hazelnuts needs to be quickly positioned. In this paper, the sum of projection gradient...
31. A Short Text Classification Method Based on Convolutional Neural Network and Semantic Extension
Haitao Wang, Keke Tian, Zhengjiang Wu, Lei Wang
Pages: 367 - 375
In order to solve the problem that traditional short text classification methods do not perform well on short text due to the data sparsity and insufficient semantic features, we propose a short text classification method based on convolutional neural network and semantic extension. Firstly, we propose...
32. Research of Synergy Warning System for Gas Outburst Based on Entropy-Weight Bayesian
Jiayong Zhang, Zibo Ai, Liwen Guo, Xiao Cui
Pages: 376 - 385
Based on the statistical analysis of coal occurrence characteristics, and dynamic phenomena of coal and rock in Qianjiaying coal mine, China, an area–local outburst early warning system based on outburst key factors and early warning indicators was constructed. Statistical analysis of anomaly features...
33. Multi-Attribute Decision-Making Using Hesitant Fuzzy Dombi–Archimedean Weighted Aggregation Operators
Peide Liu, Abhijit Saha, Debjit Dutta, Samarjit Kar
Pages: 386 - 411
Multi-attribute decision-making (MADM) has been receiving great attention in recent years due to two major issues which are basically to describe attribute values and secondly to aggregate the described information to generate a ranking of alternatives. For the first case it entails the hesitant fuzzy...
34. Ameliorated Ensemble Strategy-Based Evolutionary Algorithm with Dynamic Resources Allocations
Wali Khan Mashwani, Syed Nouman Ali Shah, Samir Brahim Belhaouari, Abdelouahed Hamdi
Pages: 412 - 437
In the last two decades, evolutionary computing has become the mainstream to attract the attention of the experts in both academia and industrial applications due to the advent of the fast computer with multi-core GHz processors have had a capacity of processing over 100 billion instructions per second....
35. Hidden Conflicts of Belief Functions
Milan Daniel, Václav Kratochvíl
Pages: 438 - 452
In this paper, hidden conflicts of belief functions are observed in the case where the sum of all multiples of the conflicting belief masses equals zero. Degrees of hidden conflicts and a degree of non-conflictness are defined and analyzed, including full non-conflictness. The notion of a hidden conflict...
36. Parameter Identification of Fractional Order Chaotic System via Opposition Based Learning Bare-Bones Imperialist Competition Algorithm
Ting You, Dongge Lei, Lulu Cai, Peijiang Li
Pages: 453 - 460
In this paper, a new method is proposed to identify the parameters of fractional order chaotic system. The parameter identification is achieved by minimizing the mean square error between the states of original fractional chaotic system and those of the estimated one, in which the parameters to be identified...
37. Advanced Soft Relation and Soft Mapping
Güzide Şenel, Jeong-Gon Lee, Kul Hur
Pages: 461 - 470
The research data in this manuscript is drawn from four main sections: First, the union and the intersection of an arbitrary family of soft sets are introduced and further results for various soft set operations are obtained. Second, by using the soft relation introduced by Babitha and Sunil, its some...
38. Dual Neural Network Fusion Model for Chinese Named Entity Recognition
Dandan Zhao, Jingxiang Cao, Degen Huang, Jiana Meng, Pan Zhang
Pages: 471 - 481
Chinese named entity recognition (NER) has important effect on natural language processing (NLP) applications. This recognition task is complicated in its strong dependent-relation, missing delimiters in the text and insufficient feature representation in a single model. This paper thus proposes a dual...
39. Human Body Multiple Parts Parsing for Person Reidentification Based on Xception
Sibo Qiao, Shanchen Pang, Xue Zhai, Min Wang, Shihang Yu, Tong Ding, Xiaochun Cheng
Pages: 482 - 490
A mass of information grows explosively in socially networked industries, as extensive data, such as images and texts, is captured by vast sensors. Pedestrians are the main initiators of various activities in socially networked industries, hence, it is very important to quickly obtain relevant information...
40. Consensus Model with Double Feedback Mechanism Based on Dynamic Trust Relationship in Social Network Group Decision-Making
Yueqin Gu, Tiantian Hao, Dong Cheng, Juan Wang, Faxin Cheng
Pages: 491 - 502
In social network group decision-making, adjusting the opinions of decision makers is often used to promote consensus. But decision makers are not always willing to accept the feedback mechanism, and decision-makers' trust relationships are not constant during the consensus process. This paper constructs...
41. Algorithm for Multiple Attribute Decision-Making with Interactive Archimedean Norm Operations Under Pythagorean Fuzzy Uncertainty
Lei Wang, Harish Garg
Pages: 503 - 527
Recently, a great attention is paid toward developing aggregation operators for Pythagorean fuzzy set (PFS). However, few of them have adopted the rules of Archimedean t-conorm and t-norm (ATT) to aggregate the numbers. Motivated by this, the keep interest of the present work is to define some Pythagorean...
42. Activity Efficiency Model in Business Process Under Conflict Information and Its Application
Qiu Xiaoping, Li Juan, Ruin Fatimah, Jiong Chen
Pages: 528 - 536
Information transition and sharing is necessary for business process management and multi-source information may cause information conflict and reduce activity efficiency. This paper proposes a novel activity efficiency model in business process under conflict information. First, the evidence theory...
43. Fault Diagnosis of Bearings Using an Intelligence-Based Autoregressive Learning Lyapunov Algorithm
Farzin Piltan, Jong-Myon Kim
Pages: 537 - 549
Bearings are complex components with nonlinear behavior that are used to reduce the effect of inertia. They are used in applications such as induction motors and rotating components. Condition monitoring and effective data analysis are important aspects of fault detection and classification in bearings....
44. An Intuitionistic Fuzzy Time Series Model Based on New Data Transformation Method
Long-Sheng Chen, Mu-Yen Chen, Jing-Rong Chang, Pei-Yu Yu
Pages: 550 - 559
Traditional time series methods can predict seasonal problems, but not problems with transferred linguistic data. Thus, a forecasting method for such problems is required. However, existing intuitionistic fuzzy time series forecasting methods lack persuasiveness in determining the degree of hesitation...
45. Intrusion Detection Systems, Issues, Challenges, and Needs
Mohammad Aljanabi, Mohd Arfian Ismail, Ahmed Hussein Ali
Pages: 560 - 571
Intrusion detection systems (IDSs) are one of the promising tools for protecting data and networks; many classification algorithms, such as neural network (NN), Naive Bayes (NB), decision tree (DT), and support vector machine (SVM) have been used for IDS in the last decades. However, these classifiers...
46. Feature Subset Selection Based on Variable Precision Neighborhood Rough Sets
Yingyue Chen, Yumin Chen
Pages: 572 - 581
Rough sets have been widely used in the fields of machine learning and feature selection. However, the classical rough sets have the problems of difficultly dealing with real-value data and weakly fault tolerance. In this paper, by introducing a neighborhood rough set model, the values of decision systems...
47. Generalized Direct Product of Complex Intuitionistic Fuzzy Subrings
Muhammad Gulzar, M. Haris Mateen, Yu-Ming Chu, Dilshad Alghazzawi, Ghazanfar Abbas
Pages: 582 - 593
The objective of this article is to present the notion of direct product of two complex intuitionistic fuzzy subrings. We show that the direct product of two complex intuitionistic fuzzy subrings is also complex intuitionistic fuzzy subring and discuss its various algebraic aspects. We also define the...
48. Hybrid Fuzzy Sliding Mode Control for Uncertain PAM Robot Arm Plant Enhanced with Evolutionary Technique
Ho Pham Huy Anh, Cao Van Kien
Pages: 594 - 604
This paper introduces an enhanced fuzzy sliding mode control (EFSMC) algorithm used for controlling the uncertain pneumatic artificial muscle (PAM) robot arm containing external disturbances. The nonlinear features of investigated PAM robot arm system are approximated using fuzzy logic. Moreover, the...
49. Research on Customer Satisfaction Based on Multidimensional Analysis
Rui Mu, Yujie Zheng, Kairui Zhang, Yufeng Zhang
Pages: 605 - 616
Sentiment analysis has been extensively studied recently for developing methodologies to automatically extract information from online reviews, which is important for manufacturers to improve their products or services. Unfortunately, most of current studies don’t take several key factors (e.g., sentiment...
50. On Computing Domination Set in Intuitionistic Fuzzy Graph
A. Bozhenyuk, S. Belyakov, M. Knyazeva, I. Rozenberg
Pages: 617 - 624
In this paper, the concept of minimal intuitionistic dominating vertex subset of an intuitionistic fuzzy graph was considered, and on its basis, the notion of a domination set as an invariant of the intuitionistic fuzzy graph was introduced. A method and an algorithm for finding all minimal intuitionistic...
51. An Efficient CNN with Tunable Input-Size for Bearing Fault Diagnosis
Jungan Chen, Jean Jiang, Xinnian Guo, Lizhe Tan
Pages: 625 - 634
Deep learning can automatically learn the complex features of input data and is recognized as an effective method for bearing fault diagnosis. Convolution neuron network (CNN) has been successfully used in image classification, and images of vibration signal or time-frequency information from short-time...
52. Teaching Performance Evaluation Based on the Proportional Hesitant Fuzzy Linguistic Prioritized Choquet Aggregation Operator
Lei Wang, Lili Rong, Fei Teng, Peide Liu
Pages: 635 - 650
The quality of teaching can be improved by teaching performance evaluation from multiple experts, which is a multiple attribute group decision-making (MAGDM) problem. In this paper, a group decision-making method under proportional hesitant fuzzy linguistic environment is proposed to evaluate teaching...
53. Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
Jiang Li, Lihong Guo, Yan Li, Chang Liu, Lijuan Wang, Hui Hu
Pages: 651 - 675
The permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs well...
54. Solving Logistics Distribution Center Location with Improved Cuckoo Search Algorithm
Juan Li, Yuan-Hua Yang, Hong Lei, Gai-Ge Wang
Pages: 676 - 692
As a novel swarm intelligence optimization algorithm, cuckoo search (CS), has been successfully applied to solve various optimization problems. Despite its simplicity and efficiency, the CS is easy to suffer from the premature convergence and fall into local optimum. Although a lot of research has been...
55. MADL: A Multilevel Architecture of Deep Learning
Samir Brahim Belhaouari, Hafsa Raissouli
Pages: 693 - 700
Deep neural networks (DNN) are a powerful tool that is used in many real-life applications. Solving complicated real-life problems requires deeper and larger networks, and hence, a larger number of parameters to optimize. This paper proposes a multilevel architecture of deep learning (MADL) that breaks...
56. Granule Description of Object (Attribute)-Oriented Linguistic Concept Lattice Based on Dominance Relation
Hui Cui, Ansheng Deng, Chunmei Chang, Hongyue Diao, Li Zou
Pages: 701 - 714
Concept lattice, as an effective tool for knowledge acquisition and data analysis, has been successfully used in many fields. Aiming at the problem of groups for uncertain information in the linguistic environment, this paper mainly focuses on the granule description with linguistic concept lattice from...
57. Classification of Diabetic Rat Histopathology Images Using Convolutional Neural Networks
Ahmet Haşim Yurttakal, Hasan Erbay, Gökalp Çinarer, Hatice Baş
Pages: 715 - 722
Diabetes mellitus is a common disease worldwide. In progressive diabetes patients, deterioration of kidney histology tissue begins. Currently, the histopathologic examination of kidney tissue samples has been performed manually by pathologists. This examination process is time-consuming and requires...
58. Automatic Acute Ischemic Stroke Lesion Segmentation Using Semi-supervised Learning
Bin Zhao, Shuxue Ding, Hong Wu, Guohua Liu, Chen Cao, Song Jin, Zhiyang Liu
Pages: 723 - 733
Ischemic stroke has been a common disease in the elderly population, which can cause long-term disability and even death. However, the time window for treatment of ischemic stroke in its acute stage is very short. To fast localize and quantitively evaluate the acute ischemic stroke (AIS) lesions, many...
59. What Concerns Consumers about Hypertension? A Comparison between the Online Health Community and the Q&A Forum
Ye Chen, Ting Dong, Qunwei Ban, Yating Li
Pages: 734 - 743
In this paper, the Biterm topic modeling method and comparative analysis were employed to identify consumers' information needs on hypertension and their differences between the Online Health Community and the Q&A Forum. There are common information needs on both platforms but consumers on MedHelp...
60. Exploring the Landscape, Hot Topics, and Trends of Electronic Health Records Literature with Topics Detection and Evolution Analysis
Yuxing Qian, Zhenni Ni, Wenxuan Gui, Yunmei Liu
Pages: 744 - 757
Electronic health records (EHRs)-related publications grow rapidly. It is helpful for experts and scholars in various disciplines to better understand the research landscape, hot topics, and trends of EHRs. We collected 13,438 records of EHRs research literature bibliometrics data from the Web of Science....
61. Consensus Reaching Process in the Two-Rank Group Decision-Making with Heterogeneous Preference Information
Huali Tang, Shoufu Wan, Cong-Cong Li, Haiming Liang, Yucheng Dong
Pages: 758 - 768
This paper proposes a novel consensus reaching process (CRP) for the two-rank group decision-making (GDM) problems with heterogeneous preference information. The methods for deriving the individual and collective preference vector are provided. And the individual and collective two-rank vectors are obtained....
62. Comparing performances and effectiveness of machine learning classifiers in detecting financial accounting fraud for Turkish SMEs
Serhan Hamal, Ozlem Senvar
Pages: 769 - 782
Turkish small- and medium-sized enterprises (SMEs) are exposed to fraud risks and creditor banks are facing big challenges to deal with financial accounting fraud. This study explores effectiveness of machine learning classifiers in detecting financial accounting fraud assessing financial statements...
63. Integrating Grasshopper Optimization Algorithm with Local Search for Solving Data Clustering Problems
M. A. El-Shorbagy, A. Y. Ayoub
Pages: 783 - 793
This paper proposes a hybrid approach for solving data clustering problems. This hybrid approach used one of the swarm intelligence algorithms (SIAs): grasshopper optimization algorithm (GOA) due to its robustness and effectiveness in solving optimization problems. In addition, a local search (LS) strategy...
64. Multi-objective Optimization of Freight Route Choices in Multimodal Transportation
Kwanjira Kaewfak, Veeris Ammarapala, Van-Nam Huynh
Pages: 794 - 807
Route selection strategy has become the main aspect in the multimodal transportation system. The transport cost and time as well as the inherent risks must be considered when determining a corrective design plan. The selection of a multimodal transportation network route is a complex multi-objective...
65. A Doctor Recommendation Based on Graph Computing and LDA Topic Model
Qiuqing Meng, Huixiang Xiong
Pages: 808 - 817
Doctor recommendation technology can help patients filter out large number of irrelevant doctors and find doctors who meet their actual needs quickly and accurately, helping patients gain access to helpful personalized online healthcare services. To address the problems with the existing recommendation...
66. Mathematics and Computational Intelligence Synergies for Emerging Challenges
Jesús Medina, Juan Moreno-García, Eloísa Ramírez-Poussa, László T. Kóczy
Pages: 818 - 820
67. Forecasting Teleconsultation Demand with an Ensemble Attention-Based Bidirectional Long Short-Term Memory Model
Wenjia Chen, Lean Yu, Jinlin Li
Pages: 821 - 833
Accurate demand forecast can help improve teleconsultation efficiency. But teleconsultation demand forecast has not been reported in existing literature. For this purpose, the study proposes a novel model based on deep learning algorithm for daily teleconsultation demand forecast to fill in the research...
68. Constructing Ontology of Brain Areas and Autism to Support Domain Knowledge Exploration and Discovery
Liang Hong, Haoshuai Xu, Xiaoyue Shi
Pages: 834 - 846
Medical studies have confirmed the causal relationship between autism and brain areas. Such relationship can effectively promote the early diagnosis and timely intervention of autism. However, existing experiment-driven methods discovering such relationships are costly while machine-learning-based methods...
69. Analyzing Online Shopping Behaviors via a new Data-Driven Hesitant Fuzzy Approach
M. Çağrı Budak, Sezi Cevik Onar
Pages: 847 - 858
Understanding online shopping behaviors is crucial for the survival of many firms. Modeling the customers' online shopping behaviors is a complex problem that involves uncertainty, hesitancy, and imprecision since different generations have different attitudes toward e-commerce. In this study, a...
70. Statistical and Machine Learning Approaches for Clinical Decision on Drug Usage in Diabetes with Reference to Competence and Safeness
S. Appavu Alias Balamurugan, K. R. Saranya, S. Sasikala, G. Chinthana
Pages: 859 - 868
Diabetes is a chronic disease that requires patient-centered treatment. The physician strategy for treatment of diabetes varies from one patient to another. Using the clinical parameters and the evidence of diabetes at various group of people are to be treated with the drugs that provide significant...
71. Similarity Measures and Multi-person TOPSIS Method Using m-polar Single-Valued Neutrosophic Sets
Juanyong Wu, Ahmed Mostafa Khalil, Nasruddin Hassan, Florentin Smarandache, A. A. Azzam, Hui Yang
Pages: 869 - 885
In this paper, we give a new notion of the m-polar single-valued neutrosophic sets (m-PSVNSs) which is a hybrid of the single-valued neutrosophic sets (SVNSs) and the m-polar fuzzy sets (m-PFSs) and study several of the structure operations including subset, equal, union, intersection, and complement....
72. Few-Shot Image Segmentation Based on Dual Comparison Module and Sequential k-Shot Integration
Chencong Xing, Shujing Lyu, Yue Lu
Pages: 886 - 895
Few-shot image segmentation intends to segment query images (test images) given only a few support samples with annotations. However, previous works ignore the impact of the object scales, especially in the support images. Meanwhile, current models only work on images with the similar size of the object...
73. Value-Based Reasoning in Autonomous Agents
Tomasz Zurek, Michail Mokkas
Pages: 896 - 921
The issue of decision-making of autonomous agents constitutes the current work topic for many researchers. In this paper we propose to extend the existing model of value-based teleological reasoning by a new, numerical manner of representation of the level of value promotion. The authors of the paper...
74. Understanding the Highly Sensitive Health Communication Behavior in Social Media from the Perspective of the Risk Perception Attitude Framework and Perceived Interactivity
Lusheng Guo, Lifang Liao, Donglan Li, Chunnian Liu
Pages: 922 - 934
Integrating aspects of the risk perception attitude framework and perceived interactivity, this study investigates the impact of the social media interaction environment on users' motivation and behavioral intention to reproductive health communication. A survey was conducted, and structural equation...
75. A MCDM Method with Linguistic Variables and Intuitionistic Fuzzy Numbers to Evaluate Product Development Projects
Chen-Tung Chen, Wei-Zhan Hung
Pages: 935 - 945
The high-tech consumer goods market is a rapidly changing environment. Project evaluation and selection play important roles in an organization to increase its competitive advantages successfully. When handling new product project decision problems, it is important to collect information to make the...
76. Fuzzy Hoeffding Decision Tree for Data Stream Classification
Pietro Ducange, Francesco Marcelloni, Riccardo Pecori
Pages: 946 - 964
Data stream mining has recently grown in popularity, thanks to an increasing number of applications which need continuous and fast analysis of streaming data. Such data are generally produced in application domains that require immediate reactions with strict temporal constraints. These particular characteristics...
77. Slope Sliding Force Prediction via Belief Rule-Based Inferential Methodology
Jing Feng, Xiaobin Xu, Pan Liu, Feng Ma, Chengrong Ma, Zhigang Tao
Pages: 965 - 977
Slope sliding force can be measured by an anchor cable sensor with the negative Poisson's ratio (NPR) property. It is capable of reflecting the stability of the slope intuitively. Thus, predicting the variation trend of the sliding force is able to achieve early warning for landslide disaster, thereby...
78. Psychological Health Status Evaluation of the Public in Different Areas Under the Outbreak of Novel Coronavirus Pneumonia
Xiaolan Wu, Chengzhi Zhang, Ningning Song, Weiwei Zhang, Yaya Bian
Pages: 978 - 990
During the outbreak of novel coronavirus pneumonia, the number of confirmed cases and deaths in Hubei province of China increased sharply, and the situation in Hubei was more severe than that in non-Hubei, so we do a research on psychological health status evaluation of the public in Hubei and non-Hubei...
79. An Intuitionistic Fuzzy Decision-Making for Developing Cause and Effect Criteria of Subcontractors Selection
Lazim Abdullah, Zheeching Ong, Nuraini Rahim
Pages: 991 - 1002
The decision-making trial and evaluation laboratory (DEMATEL) method has been applied to solve numerous multi-criteria decision-making (MCDM) problems where crisp numbers are utilized in defining linguistic evaluation. Previous literature suggests that the intuitionistic fuzzy DEMATEL (IF-DEMATEL) can...
80. Deep Learning Models Combining for Breast Cancer Histopathology Image Classification
Hela Elmannai, Monia Hamdi, Abeer AlGarni
Pages: 1003 - 1013
Breast cancer is one of the foremost reasons of death among women in the world. It has the largest mortality rate compared to the types of cancer accounting for 1.9 million per year in 2020. An early diagnosis may increase the survival rates. To this end, automating the analysis and the diagnosis allows...
81. Interval Valued m-polar Fuzzy BCK/BCI-Algebras
G. Muhiuddin, D. Al-Kadi
Pages: 1014 - 1021
The notion of interval-valued m-polar fuzzy sets (abbreviated IVmPF) is much wider than the notion of m-polar fuzzy sets. In this paper, we apply the theory of IVmPF on BCK/BCI-algebras. We introduce the concepts of IVmPF subalgebras, IVmPF ideals and IVmPF commutative ideals and some essential properties...
82. Regret Theory-Based Case-Retrieval Method with Multiple Heterogeneous Attributes and Incomplete Weight Information
Kai Zhang, Ying-Ming Wang, Jing Zheng
Pages: 1022 - 1033
Case retrieval is a crucial step in case-based reasoning (CBR), which is related to decision-making effectiveness. To improve decision support, CBR usually calculates case similarity and evaluates utility. However, the psychological behavior of decision makers is seldom considered in case retrieval....
83. A Study on Semi-directed Graphs for Social Media Networks
Sovan Samanta, Madhumangal Pal, Rupkumar Mahapatra, Kousik Das, Robin Singh Bhadoria
Pages: 1034 - 1041
In the literature of graph theory, networks are represented as directed graphs or undirected graphs and a mixed of both combinations. In today's era of computing, networks like brain and facebook that do not belong to any of the mentioned networks category and in fact, it belongs to the combination...
84. Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems
Radu-Emil Precup, Radu-Codrut David, Raul-Cristian Roman, Emil M. Petriu, Alexandra-Iulia Szedlak-Stinean
Pages: 1042 - 1052
This paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a fresh metaheuristic algorithm, namely the Slime...
85. Rumor Detection by Propagation Embedding Based on Graph Convolutional Network
Dang Thinh Vu, Jason J. Jung
Pages: 1053 - 1065
Detecting rumors is an important task in preventing the dissemination of false knowledge within social networks. When a post is propagated in a social network, it typically contains four types of information: i) social interactions, ii) time of publishing, iii) content, and iv) propagation structure....
86. Modified 2-Way Wavefront (M2W) Algorithm for Efficient Path Planning
Ayesha Maqbool, Alina Mirza, Farkhanda Afzal
Pages: 1066 - 1077
In this paper modified 2-way wavefront algorithm(M2W) is introduced for the discretized path planning problem. The proposed scheme uses the Glasius model, wavefront navigational function, and adaptation of Artificial Potential Fields (APF) for effective obstacle avoidance. Unlike the APF, it does not...
87. Deep Encoder–Decoder Neural Networks for Retinal Blood Vessels Dense Prediction
Wenlu Zhang, Lusi Li, Vincent Cheong, Bo Fu, Mehrdad Aliasgari
Pages: 1078 - 1086
Automatic segmentation of retinal blood vessels from fundus images is of great importance in assessing the condition of vascular network in human eyes. The task is primary challenging due to the low contrast of images, the variety of vessels and potential pathology. Previous studies have proposed shallow...
88. Applying Metaheuristic for Time-Dependent Traveling Salesman Problem in Postdisaster
Pages: 1087 - 1107
The Time-Dependent Traveling Salesman Problem (TDTSP) is a generalization of the Traveling Salesman Problem (TSP) and Traveling Repairman Problem (TRP). In the TSP and TRP, the travel time to travel is assumed to be constant. However, in practice, the travel times vary according to several factors that...
89. The Red Colobuses Monkey: A New Nature–Inspired Metaheuristic Optimization Algorithm
Wijdan Jaber AL-kubaisy, Mohammed Yousif, Belal Al-Khateeb, Maha Mahmood, Dac-Nhuong Le
Pages: 1108 - 1118
The presented study suggests a new nature–inspired metaheuristic optimization algorithm referred to as Red Colobuses Monkey (RCM) that can be used for optimization problems; this algorithm mimics the behavior related to red monkeys in nature. In preparation for proving the suggested algorithm's...
90. Where Should Mobile Health Application Providers Focus Their Goals?
Xiaojia Wang, Kuo Du, Keyu Zhu, Shen Xu, Shanshan Zhang
Pages: 1119 - 1131
In the context of “Internet +” medical treatment, mobile health applications provide services for people in a new way, making it possible for people to carry out health management anytime and anywhere. According to the survey data, the most powerful consumers in the field of mobile health applications...
91. A Comprehensive Study of Machine Learning Methods on Diabetic Retinopathy Classification
Omer Faruk Gurcan, Omer Faruk Beyca, Onur Dogan
Pages: 1132 - 1141
Diabetes is one of the emerging threats to public health all over the world. According to projections by the World Health Organization, diabetes will be the seventh foremost cause of death in 2030 (WHO, Diabetes, 2020. https://www.afro.who.int/health-topics/diabetes). Diabetic retinopathy (DR) results...
92. Optimal FOC-PID Parameters of BLDC Motor System Control Using Parallel PM-PSO Optimization Technique
Nguyen Tien Dat, Cao Van Kien, Ho Pham Huy Anh
Pages: 1142 - 1154
This paper proposes a parallelization method for meta-heuristic particle swarm optimization algorithm to obtain a convincingly fast execution and stable global solution result. Applied the proposed method, the searching region is efficiently separated into sub-regions which are simultaneously searched...
93. Markov Decision Model of Emergency Medical Supply Scheduling in Public Health Emergencies of Infectious Diseases
Xiaojia Wang, Zhizhen Liang, Keyu Zhu
Pages: 1155 - 1169
In this paper, a Markov decision process (MDP) model was established to study emergency medical material scheduling strategies for public health emergencies such as COVID-19. Within the constraints of dispatchable supplies, the priority of each medical node complicates the problem of deciding which hospital...
94. Abnormal Traffic Detection Based on Generative Adversarial Network and Feature Optimization Selection
Wengang Ma, Yadong Zhang, Jin Guo, Kehong Li
Pages: 1170 - 1188
Complex and multidimensional network traffic features have potential redundancy. When traditional detection methods are used for training samples, the detection accuracy of the supervised classification model is affected due to small data samples. Therefore, a method based on generative adversarial networks...
95. Multiobjective Programming Approaches to Obtain the Priority Vectors under Uncertain Probabilistic Dual Hesitant Fuzzy Preference Environment
Songtao Shao, Xiaohong Zhang
Pages: 1189 - 1207
This paper develops uncertain probabilistic dual hesitant fuzzy numbers (UPDHFN), which includes six types of dual hesitant fuzzy sets (DHFNs). Next, the UPDHFN is applied to the uncertain probabilistic dual hesitant fuzzy preference relation (UPDHFPR). Furthermore, the (acceptable) expected consistency,...
96. The Mathematical Model and Deep Learning Features Selection for Whorl Fingerprint Classifications
Ibrahim Jawarneh, Nesreen Alsharman
Pages: 1208 - 1216
In this paper, different classes of the whorl fingerprint are discussed. A general dynamical system with a parameter θ is created using differential equations to simulate these classes by varying the value of θ. The global dynamics is studied, and the existence and stability of equilibria are analyzed....
97. Multi-Scale Person Localization With Multi-Stage Deep Sequential Framework
Sultan Daud Khan, Saleh Basalamah
Pages: 1217 - 1228
Person detection in real videos and images is a classical research problem in computer vision. Person detection is a nontrivial problem that offers many challenges due to several nuisances that commonly observed in natural videos. Among these, scale is the main challenging problem in various object detection...
98. Multi-Attribute Decision-Making Method Based Distance and COPRAS Method with Probabilistic Hesitant Fuzzy Environment
Haifeng Song, Zi-chun Chen
Pages: 1229 - 1241
As an extension of hesitant fuzzy set, the probabilistic hesitant fuzzy set (PHFS) can more accurately express the initial decision information given by experts, thus the decision method based on PHFS is more true and reliable. In this paper, multi-attribute decision-making (MADM) method is proposed...
99. Dynamic Relationship Network Analysis Based on Louvain Algorithm for Large-Scale Group Decision Making
Minxuan Li, Jindong Qin, Tao Jiang, Witold Pedrycz
Pages: 1242 - 1255
In most existing large-scale group decision making (LSGDM) problems, the relationships between decision makers (DMs) are usually ignored or regarded as static. However, in many cases, the results of LSGDM are dynamically influenced by the relationship between group members. To address this issue, a dynamic...
100. Performance of a New Time-Truncated Control Chart for Weibull Distribution Under Uncertainty
Ali Hussein AL-Marshadi, Ambreen Shafqat, Muhammad Aslam, Abdullah Alharbey
Pages: 1256 - 1262
To detect indeterminacy effect in the manufacturing process, attribute control chart using neutrosophic Weibull distribution is proposed in this paper. To make the attribute control chart more efficient for persistent shifts in the industrial process, an attribute control chart using Weibull distribution...
101. A Hybrid Decision-Making Approach Under Complex Pythagorean Fuzzy N-Soft Sets
Muhammad Akram, Faiza Wasim, Ahmad N. Al-Kenani
Pages: 1263 - 1291
The main objectives of this article include the formal statement of a new mathematical model of uncertain knowledge and the presentation of its potential applications. The novel hybrid model is called complex Pythagorean fuzzy N-soft set (CPFNSS) because it enjoys both the parametric structure of N-soft...
102. An Uncertain Model for Analysis the Barriers to Implement Blockchain in Supply Chain Management and Logistics for Perishable Goods
Pages: 1292 - 1302
These days, with the development of advanced space, rising innovations, for example, the blockchain has made a decent open door for organizations to additionally improve the productivity of their supply arranges. Going with and orchestrating the supply chain with computerized advancements can prompt...
103. H2Rec: Homogeneous and Heterogeneous Network Embedding Fusion for Social Recommendation
Yabin Shao, Cheng Liu
Pages: 1303 - 1314
Due to the problems of data sparsity and cold start in traditional recommendation systems, social information is introduced. From the perspective of heterogeneity, it reflects the indirect relationship between users, and from the perspective of homogeneity, it reflects the direct relationship between...
104. Blur2Sharp: A GAN-Based Model for Document Image Deblurring
Hala Neji, Mohamed Ben Halima, Tarek M. Hamdani, Javier Nogueras-Iso, Adel M. Alimi
Pages: 1315 - 1321
The advances in mobile technology and portable cameras have facilitated enormously the acquisition of text images. However, the blur caused by camera shake or out-of-focus problems may affect the quality of acquired images and their use as input for optical character recognition (OCR) or other types...
105. The Commutator of Fuzzy Congruences in Universal Algebras
Gezahagne Mulat Addis, Nasreen Kausar, Muhammad Munir, Yu-Ming Chu
Pages: 1322 - 1336
We develop the commutator theory for fuzzy congruence relations of general universal algebras. In particular, for algebras in modular varieties, we characterize the commutator of fuzzy congruences using the Day’s terms.
106. A Repairing Artificial Neural Network Model-Based Stock Price Prediction
S. M. Prabin, M. S. Thanabal
Pages: 1337 - 1355
Predicting the stock price movements based on quantitative market data modeling is an open problem ever. In stock price prediction, simultaneous achievement of higher accuracy and the fastest prediction becomes a challenging problem due to the hidden information found in raw data. Various prediction...
107. Metaheuristic Multi-Objective Method to Detect Communities on Dynamic Social Networks
Fatemeh Besharatnia, AliReza Talebpour, Sadegh Aliakbary
Pages: 1356 - 1372
Community detection is an important area in social networks analysis, which has many applications. Most social networks are inherently dynamic, consisting of constantly changing communities and therefore, community detection is a challenge in such networks. Since the communities in dynamic networks change,...
108. Communication-Efficient Distributed SGD with Error-Feedback, Revisited
Tran Thi Phuong, Le Trieu Phong
Pages: 1373 - 1387
We show that the convergence proof of a recent algorithm called dist-EF-SGD for distributed stochastic gradient descent with communication efficiency using error-feedback of Zheng et al., Communication-efficient distributed blockwise momentum SGD with error-feedback, in Advances in Neural Information...
109. Knowledge Representations for Constructing Chains of Contexts in Geographic Information Systems
Janusz Kacprzyk, Stanislav Belyakov, Alexander Bozhenyuk, Igor Rozenberg
Pages: 1388 - 1395
Solving complex informal problems using spatial data is often used in industry and business. In the absence of a solution algorithm, analyst resorts to a heuristic search for a solution, which is based on an interactive dialogue with a geographic information system (GIS). The analyst builds a cartographic...
110. Face Spoof Attack Detection with Hypergraph Capsule Convolutional Neural Networks
Yuxin Liang, Chaoqun Hong, Weiwei Zhuang
Pages: 1396 - 1402
Face authentication has been widely used in personal identification. However, face authentication systems can be attacked by fake images. Existing methods try to detect such attacks with different features. Among them, using color images become popular since it is flexible and generic. In this paper,...
111. Some New Classes of Preinvex Fuzzy-Interval-Valued Functions and Inequalities
Muhammad Bilal Khan, Muhammad Aslam Noor, Lazim Abdullah, Yu-Ming Chu
Pages: 1403 - 1418
It is well known that convexity and nonconvexity develop a strong relationship with different types of integral inequalities. Due to the importance of the concept of nonconvexity and integral inequality, in this paper, we present some new classes of preinvex fuzzy-interval-valued functions involving...
112. Attribute Reduction Method of Covering Rough Set Based on Dependence Degree
Li Fachao, Ren Yexing, Jin Chenxia
Pages: 1419 - 1425
Attribute reduction is a hot topic in the field of data mining. Compared with the traditional methods, the attribute reduction algorithm based on covering rough set is more suitable for dealing with numerical data. However, this kind of algorithm is still not efficient enough to deal with large-scale...
113. Distorted Vehicle Detection and Distance Estimation by Metric Learning-Based SSD
Fanghui Zhang, Yi Jin, Shichao Kan, Linna Zhang, Yigang Cen, Wen Jin
Pages: 1426 - 1437
Object detection and distance estimation based on videos are important issues in advanced driver-sssistant system (ADAS). In practice, fisheye cameras are widely used to capture images with a large field of view, which will produce distorted image frames. But most of the object detection algorithms were...
114. Applying Meta-Heuristics Algorithm to Solve Assembly Line Balancing Problem with Labor Skill Level in Garment Industry
Gary Yu-Hsin Chen, Ping-Shun Chen, Jr-Fong Dang, Sung-Lien Kang, Li-Jen Cheng
Pages: 1438 - 1450
This research investigates how to properly place garment industry workers to work stations in the assembly line to achieve a more balanced production and to reduce the production cycle time. We simulate the assembly line balancing problem via staff assignments. In our research, we conduct a comparative...
115. Wood Species Recognition with Small Data: A Deep Learning Approach
Yongke Sun, Qizhao Lin, Xin He, Youjie Zhao, Fei Dai, Jian Qiu, Yong Cao
Pages: 1451 - 1460
Wood species recognition is an important work in the wood trade and wood commercial activities. Although many recognition methods were presented in recent years, the existing wood species recognition methods mainly use shallow recognition models with low accuracy and are still unsatisfying for many real-world...
116. Multi-UAV Cooperative Task Assignment Based on Orchard Picking Algorithm
Weiheng Liu, Xin Zheng, Harish Garg
Pages: 1461 - 1467
The multi-unmanned aerial vehicle (UAV) must autonomously perform reconnaissance-attack-evaluation tasks under multiple constraints in the battlefield environment. This paper proposes a nearest neighbor method designed with the shortest neighboring distance as an indicator which quickly solves the optimal...
117. A Novel Model for Assessing e-Government Websites Using Hybrid Fuzzy Decision-Making Methods
Masoud Shayganmehr, Gholam Ali Montazer
Pages: 1468 - 1488
Websites are considered as the core infrastructure of e-government, so evaluating the quality of websites assists organizations to provide high-quality online services to citizens. For this purpose, this paper is seeking to design a model that enables any organization to evaluate the quality of its websites...
118. A Proposed Order Prediction Methodology for Vendor-Managed Inventory System in FMCG Sector Based on Interval-Valued Intuitionistic Fuzzy Sets
Murat Levent Demircan, Ekin Merdan
Pages: 1489 - 1500
Vendor-managed inventory (VMI) is a supply chain coordination improvement system. Due to the vendor’s responsibility for the replenishment decision, demand forecasting and quick response for retailers’ demand fluctuations are crucial in a VMI system. Our study focuses on order prediction of the VMI for...
119. Water-Energy-Food Nexus and Eco-Sustainability: A Three-Stage Dual-Boundary Network DEA Model for Evaluating Jiangsu Province in China
Jianxuan Li, Sijing Liu, Yizhao Zhao, Zaiwu Gong, Guo Wei, Lihong Wang
Pages: 1501 - 1515
The water–energy–food (W-E-F) nexus approach has become the basis for a host of many methods addressing the security of global resources, whose methods are often nonparametric, due to the complex and indefinable relationship among the three. In this work, the nonparametric evaluation method data envelopment...
120. Certain Properties of Single-Valued Neutrosophic Graph With Application in Food and Agriculture Organization
Shouzhen Zeng, Muhammad Shoaib, Shahbaz Ali, Florentin Smarandache, Hossein Rashmanlou, Farshid Mofidnakhaei
Pages: 1516 - 1540
Fuzzy graph models are present everywhere from natural to artificial structures, embodying the dynamic processes in physical, biological, and social systems. As real-life problems are often uncertain on account of inconsistent and indeterminate information, it seems very demanding for an expert to model...
121. The Arithmetic Operator of Fuzzy Regular Prismoid Numbers and Its Application to Fuzzy Risk Analysis
Pages: 1541 - 1563
We devote to study the arithmetic operator of fuzzy regular prismoid numbers as well as the degree of similarity between fuzzy regular prismoid numbers, and then the arithmetic operator and the degree of similarity are applied in risk analysis. Firstly, the arithmetic operator of fuzzy regular prismoid...
122. Recommendation Algorithm Based on Knowledge Graph to Propagate User Preference
Zhisheng Yang, Jinyong Cheng
Pages: 1564 - 1576
In recommendation algorithms, data sparsity and cold start problems are inevitable. To solve such problems, researchers apply auxiliary information to recommendation algorithms, mine users’ historical records to obtain more potential information, and then improve recommendation performance. In this paper,...
123. A Single Historical Painting Super-Resolution via a Reference-Based Zero-Shot Network
Hongzhen Shi, Dan Xu, Hao Zhang, YingYing Yue
Pages: 1577 - 1588
As an important part of human cultural heritage, many ancient paintings have suffered from various deteriorations that have led to texture blurring, color fading, etc. Single image super-resolution (SISR) which aims to recover a high-resolution (HR) version from a low-resolution (LR) input is actively...
124. Integrating Pattern Features to Sequence Model for Traffic Index Prediction
Yueying Zhang, Zhijie Xu, Jianqin Zhang, Jingjing Wang, Lizeng Mao
Pages: 1589 - 1596
Intelligent traffic system (ITS) is one of the effective ways to solve the problem of traffic congestion. As an important part of ITS, traffic index prediction is the key of traffic guidance and traffic control. In this paper, we propose a method integrating pattern feature to sequence model for traffic...
125. Par4 Parallel Robot Trajectory Tracking Control Based on DMR-GWO2 and Fuzzy Predictive
Xiaoqing Zhang, Zhengfeng Ming
Pages: 1597 - 1606
A dynamic Grey Wolf Optimizer (GWO) is proposed, noted as DGWO2, and a novel dynamic improved GWO algorithm is obtained after transferring the mutation operator and the eliminating–reconstructing mechanism to the DGWO2, noted as DMR-GWO2. A Type-2 fuzzy predictive compensation PID trajectory tracking...
126. Detecting COVID-19 Patients in X-Ray Images Based on MAI-Nets
Wei Wang, Xiao Huang, Ji Li, Peng Zhang, Xin Wang
Pages: 1607 - 1616
COVID-19 is an infectious disease caused by virus SARS-CoV-2 virus. Early classification of COVID-19 is essential for disease cure and control. Transcription-polymerase chain reaction (RT-PCR) is used widely for the detection of COVID-19. However, its high cost, time-consuming and low sensitivity will...
127. Analytical Reduction Method for New Type-2 Fuzzy Chance-Constrained Portfolio Selection Model
Guang Yang, Mei Cai, Jindong Qin, Xinwang Liu, Xu Zhang
Pages: 1617 - 1632
In the traditional portfolio selection problem, asset returns are modeled as fuzzy variables with fuzzy return. However, this approach is limited in its ability to capture uncertainty accurately and in analytical model solving. Here, we aim to develop a new fuzzy chance-constrained portfolio model with...
128. The Value Function with Regret Minimization Algorithm for Solving the Nash Equilibrium of Multi-Agent Stochastic Game
Luping Liu, Wensheng Jia
Pages: 1633 - 1641
In this paper, we study the value function with regret minimization algorithm for solving the Nash equilibrium of multi-agent stochastic game (MASG). To begin with, the idea of regret minimization is introduced to the value function, and the value function with regret minimization algorithm is designed....
129. A Regulatable Blockchain Transaction Model with Privacy Protection
Zhiyuan Xue, Miao Wang, Qiuyue Zhang, Yunfeng Zhang, Peide Liu
Pages: 1642 - 1652
Blockchain is a decentralized distributed ledger technology. The public chain represented by Bitcoin and Ethereum only realizes the limited anonymity of user identity, and the transaction amount is open to the whole network, resulting in user privacy leakage. Based on the existing anonymous technology,...
130. Some Cosine Similarity Measures and Distance Measures between Complex q-Rung Orthopair Fuzzy Sets and Their Applications
Peide Liu, Zeeshan Ali, Tahir Mahmood
Pages: 1653 - 1671
As a modification of the q-rung orthopair fuzzy sets (QROFSs), complex QROFSs (CQROFSs) can describe the inaccurate information by complex-valued truth grades with an additional term, named as phase term. Cosine similarity measures (CSMs) and distance measures (DMs) are important tools to verify the...
131. Size and Location Diagnosis of Rolling Bearing Faults: An Approach of Kernel Principal Component Analysis and Deep Belief Network
Heli Wang, Haifeng Huang, Sibo Yu, Weijie Gu
Pages: 1672 - 1686
Diagnosing incipient faults of rotating machines is very important for reducing economic losses and avoiding accidents caused by faults. However, diagnoses of locations and sizes of incipient faults are very difficult in a noisy background. In this paper, we propose a fault diagnosis method that combines...
132. Construction of Garment Pattern Design Knowledge Base Using Sensory Analysis, Ontology and Support Vector Regression Modeling
Zhujun Wang, Jianping Wang, Xianyi Zeng, Xuyuan Tao, Yingmei Xing, Pascal Bruniaux
Pages: 1687 - 1699
Garment pattern design is an extremely significant factor for the success of fashion company in mass customization and industry 4.0. In this paper, we proposed a new approach for constructing a garment pattern design knowledge base (GPDKB) using sensory analysis, ontology and support vector regression...
133. Improved Knowledge Measures for q-Rung Orthopair Fuzzy Sets
Muhammad Jabir Khan, Poom Kumam, Meshal Shutaywi, Wiyada Kumam
Pages: 1700 - 1713
The q-rung orthopair fuzzy set (qROFS) defined by Yager is a generalization of Atanassov intuitionistic fuzzy set (IFS) and Pythagorean fuzzy sets (PyFSs). In this paper, we define the knowledge measure for qROFS by using the cosine inverse function. The information precision and information content...
134. A Distributed Urban Traffic Congestion Prevention Mechanism for Mixed Flow of Human-Driven and Autonomous Electric Vehicles
Chenn-Jung Huang, Kai-Wen Hu, Hsing Yi Ho, Bing Zhen Xie, Chien-Chih Feng, Hung-Wen Chuang
Pages: 1714 - 1727
Traffic congestion in urban areas has become a critical problem that municipal governments cannot overlook. Meanwhile, mixed traffic systems containing both autonomous and human-driven electric vehicles ramp up the challenge for traffic management in urban areas. Although numerous researchers have proposed...
135. An Outranking Approach for Gene Prioritization Using Multinetworks
Jesús Jaime Solano Noriega, Juan Carlos Leyva López, Fiona Browne, Jun Liu
Pages: 1728 - 1741
High-throughput experimental techniques such as genome-wide association studies have been instrumental in the identification of disease-associated genes. These methods often produce large lists of disease candidate genes which are time-consuming and expensive to experimentally validate. Computational...
136. A New Approach for the 10.7-cm Solar Radio Flux Forecasting: Based on Empirical Mode Decomposition and LSTM
Junqi Luo, Liucun Zhu, Hongbing Zhu, Wei Chien, Jiahai Liang
Pages: 1742 - 1752
The daily 10.7-cm Solar Radio Flux (F10.7) data is a time series with highly volatile. The accurate prediction of F10.7 has a great significance in the fields of aerospace and meteorology. At present, the prediction of F10.7 is mainly carried out by linear models, nonlinear models, or a combination of...
137. Tactile–Visual Fusion Based Robotic Grasp Detection Method with a Reproducible Sensor
Yaoxian Song, Yun Luo, Changbin Yu
Pages: 1753 - 1762
Robotic grasp detection is a fundamental problem in robotic manipulation. The conventional grasp methods, using vision information only, can cause potential damage in force-sensitive tasks. In this paper, we propose a tactile–visual based method using a reproducible sensor to realize a fine-grained and...
138. An Intelligent Hybrid System for Forecasting Stock and Forex Trading Signals using Optimized Recurrent FLANN and Case-Based Reasoning
D. K. Bebarta, T. K. Das, Chiranji Lal Chowdhary, Xiao-Zhi Gao
Pages: 1763 - 1772
An accurate prediction of future stock market trends is a bit challenging as it requires a profound understanding of stock technical indicators, including market-dominant factors and inherent process mechanism. However, the significance of better trading decisions for a successful trader inspires researchers...
139. Cliques and Clique Covers in Interval-Valued Fuzzy Graphs
Napur Patra, Tarasankar Pramanik, Madhumangal Pal, Sukumar Mondal
Pages: 1773 - 1783
Finding cliques and clique covers in graphs are one of the most needful tasks. In this paper, interval-valued fuzzy cliques (IVFQs) and interval-valued fuzzy clique covers (IVFQCs) of an interval-valued fuzzy graph (IVFG) are introduced by introducing the fuzziness because, the crisp graphs has some...
140. Transitive Closures of Ternary Fuzzy Relations
Lemnaouar Zedam, Bernard De Baets
Pages: 1784 - 1795
Recently, we have introduced six types of composition of ternary fuzzy relations. These compositions are close in spirit to the composition of binary fuzzy relations. Based on these types of composition, we have introduced several types of transitivity of a ternary fuzzy relation and investigated their...
141. Multi-Tier Student Performance Evaluation Model (MTSPEM) with Integrated Classification Techniques for Educational Decision Making
E. S. Vinoth Kumar, S. Appavu alias Balamurugan, S. Sasikala
Pages: 1796 - 1808
In present decade, many Educational Institutions use classification techniques and Data mining concepts for evaluating student records. Student Evaluation and classification is very much important for improving the result percentage. Hence, Educational Data Mining based models for analyzing the academic...
142. Harmonically Convex Fuzzy-Interval-Valued Functions and Fuzzy-Interval Riemann–Liouville Fractional Integral Inequalities
Gul Sana, Muhammad Bilal Khan, Muhammad Aslam Noor, Pshtiwan Othman Mohammed, Yu-Ming Chu
Pages: 1809 - 1822
It is well known that the concept of convexity establishes strong relationship with integral inequality for single-valued and interval-valued function. The single-valued function and interval-valued function both are special cases of fuzzy interval-valued function. The aim of this paper is to introduce...
143. Fast Category-Hidden Adversarial Attack Against Semantic Image Segmentation
Yinghui Zhu, Yuzhen Jiang, Zhongxing Peng, Wei Huang
Pages: 1823 - 1830
In semantic segmentation, category-hidden attack is a malicious adversarial attack which manipulates a specific category without affecting the recognition of other objects. A popular method is the nearest-neighbor algorithm, which modifies the segmentation map by replacing a target category with other...
144. Research on Comprehensive Evaluation of Data Source Quality in Big Data Environment
Wenquan Li, Suping Xu, Xindong Peng
Pages: 1831 - 1841
Data quality is the prerequisite of big data research and the basis of all data analysis, mining, and decision support. Therefore, a comprehensive fuzzy evaluation method for big data quality evaluation is proposed. Through the analysis of big data quality characteristics, a big data quality evaluation...
145. Team Collaboration Particle Swarm Optimization and Its Application on Reliability Optimization
Bo Zheng, Xin Ma, Xiaoqiang Zhang, Huiying Gao
Pages: 1842 - 1855
Particle swarm optimization (PSO) tends to be premature convergence due to easily trapping into local suboptimal areas. In order to overcome the PSO's defects, the reasons causing the defects are analyzed and summarized as population diversity deficiency, insufficient information sharing, unbalance...
146. Higher-Order Strongly Preinvex Fuzzy Mappings and Fuzzy Mixed Variational-Like Inequalities
Muhammad Bilal Khan, Muhammad Aslam Noor, Khalida Inayat Noor, Yu-Ming Chu
Pages: 1856 - 1870
A family of fuzzy mappings is called higher-order strongly preinvex fuzzy mappings (HOS-preinvex fuzzy mappings), which take the place of generalization of the notion of nonconvexity is introduced through the “fuzzy-max” order among fuzzy numbers. This family properly includes the family of preinvex...
147. Detecting Objects from No-Object Regions: A Context-Based Data Augmentation for Object Detection
Jun Zhang, Feiteng Han, Yutong Chun, Kangwei Liu, Wang Chen
Pages: 1871 - 1879
Data augmentation is an important technique to improve the performance of deep learning models in many vision tasks such as object detection. Recently, some works proposed the copy-paste method, which augments training dataset by copying foreground objects and pasting them on background images. By designing...
148. Predictive Analytics for Product Configurations in Software Product Lines
Uzma Afzal, Tariq Mahmood, Raihan ur Rasool, Ayaz H. Khan, Rehan Ullah Khan, Ali Mustafa Qamar
Pages: 1880 - 1894
A Software Product Line (SPL) is a collection of software for configuring software products in which sets of features are configured by different teams of product developers. This process often leads to inconsistencies (or dissatisfaction of constraints) in the resulting product configurations, whose...
149. Order-αCQ Divergence Measures and Aggregation Operators Based on Complex q-Rung Orthopair Normal Fuzzy Sets and Their Application to Multi-Attribute Decision-Making
Zeeshan Ali, Tahir Mahmood, Abdu Gumaei
Pages: 1895 - 1922
Complex q-rung orthopair fuzzy set (CQROFS) contains the grade of supporting and the grade of supporting against in the form of polar coordinates belonging to unit disc in a complex plane and is a proficient technique to address awkward information, although the normal fuzzy number (NFN) examines normal...
150. Interior BCK/BCI-Algebras
Sun Shin Ahn, Hashem Bordbar, Young Bae Jun
Pages: 1923 - 1933
The notions of interior BCK/BCI-algebras, positive implicative interior BCK-algebras, (weak) interior ideals, positive implicative interior ideals, a positive implicative weak interior ideal of type 1, type 2, and type 3 are introduced, and related properties are investigated. A mapping is provided to...
151. A Multimodal Adversarial Attack Framework Based on Local and Random Search Algorithms
Zibo Yi, Jie Yu, Yusong Tan, Qingbo Wu
Pages: 1934 - 1947
Although many problems in computer vision and natural language processing have made breakthrough progress with neural networks, adversarial attack is a serious potential problem in many neural network- based applications. Attackers can mislead classifiers with slightly perturbed examples, which are called...