International Journal of Computational Intelligence Systems

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1147 articles

Demand forecasting procedure for short life-cycle products with an actual food processing enterprise

Rie Gaku
Pages: 85 - 92
A procedure of demand forecasting using data mining techniques is proposed to forecast the sales amount of new short life-cycle products for an actual food processing enterprise. The enterprise annually produces 100∼150 kinds of new items with short life-cycle between one week and three months to...

A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning

Shengdong Du, Tianrui Li, Xun Gong, Shi-Jinn Horng
Pages: 85 - 97
Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traffic flow forecasting, which can jointly and adaptively learn the spatial–temporal correlation features and long temporal interdependence...

Evaluation of Expert Systems Techniques for Classifying Different Stages of Coffee Rust Infection in Hyperspectral Images

Wilson Castro, Jimy Oblitas, Jorge Maicelo, Himer Avila-George
Pages: 86 - 100
In this work, the use of expert systems and hyperspectral imaging in the determination of coffee rust infection was evaluated. Three classifiers were trained using spectral profiles from different stages of infection, and the classifier based on a support vector machine provided the best performance....

An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment

Yejun Xu, Huimin Wang, Daniel Palacios-Marqués
Pages: 87 - 95
The aim of this paper is to develop an interactive approach for multiple attribute decision making with incomplete weight information under linguistic environment. Some of the concepts are defined, such as the distance between two 2-tuple linguistic variables, the expectation level of alternative, the...

LPBoost with Strong Classifiers

Yu K. Fang, Jun L. Zhou, Yan Fu, Chong J. Sun
Pages: 88 - 100
The goal of boosting algorithm is to maximize the minimum margin on sample set. Based on minimax theory, the goal can be converted into minimize the maximum edge. This idea motivates LPBoost and its variants (including TotalBoost, SoftBoost, ERLPBoost) which solve the optimization problem by linear programming....

Towards the Applied Hybrid Model in Decision Making: A Neuropsychological Diagnosis of Alzheimer's Disease Study Case

Ana Karoline Araujo de Castro, Placido Rogério Pinheiro, Mirian Caliope Dantas Pinheiro, Isabelle Tamanini
Pages: 89 - 99
A hybrid model, combining influence diagrams and a multicriteria method, is presented in order to assist with the decision making process about which questions would be more attractive to the definition of the diagnosis of Alzheimer's disease, considering the stages of Clinical Dementia Rating. The modeling...

Integrating Gradient Search, Logistic Regression and Artificial Neural Network for Profit Based Unit Commitment

A. Amudha, C. Christober Asir Rajan
Pages: 90 - 104
As the electrical industry restructures many of the traditional algorithms for controlling generating units, they need either modification or replacement. In the past, utilities had to produce power to satisfy their customers with the objective to minimize costs and actual demand/reserve were met. But...

Fuzzy Rough Graph Theory with Applications

Muhammad Akram, Maham Arshad, Shumaiza
Pages: 90 - 107
Fuzzy rough set theory is a hybrid method that deals with vagueness and uncertainty emphasized in decision-making. In this research study, we apply the concept of fuzzy rough sets to graphs. We introduce the notion of fuzzy rough digraphs and describe some of their methods of construction. In particular,...

Soft points, s-relations and soft rough approximate operations

Guangji Yu
Pages: 90 - 103
Soft set theory is a new mathematical tool to deal with uncertain problems. Since soft sets are defined by mappings and they lack “points”, managing them is not convenient. In this paper, the concept of soft points is introduced and the relationship between soft points and soft sets is investigated....

Cross-docking Location Selection in Distribution Systems: A New Intuitionistic Fuzzy Hierarchical Decision Model

S. Meysam Mousavi, Behnam Vahdani
Pages: 91 - 109
This paper introduces a new intuitionistic fuzzy hierarchical group decision-making (IFHGDM) model for the cross-docking location selection problem. The model is based on intuitionistic fuzzy modified group complex proportional assessment and group order preference by similarity to ideal solution, structuring...

On the Supply of Superior Order-1 Building Blocks for a Class of Periodical Fitness Functions

Hongqiang MO Zhong LI
Pages: 91 - 98
In addition to GA-deception, the lack of fitness differences among low-order schemata can also degrade GA's search. Therefore, a coding should present adequate superior low-order building blocks at the early stage of search. This paper aims to reveal the inherent periodicity in the search process of...

A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties

Hong-Zhong Huang, Xudong Zhang, De-Biao Meng, Yu Liu, Yan-Feng Li
Pages: 93 - 110
Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO) has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving...

Criteria Weighting and 4P's Planning in Marketing Using a Fuzzy Metric Distance and AHP Hybrid Method

Tuncay Gürbüz, Y.Esra Albayrak, Elif Alaybeyoğlu
Pages: 94 - 104
Production and consumption relationship shows that marketing plays an important role in enterprises. In the competitive market, it is very important to be able to sell rather than produce. Nowadays, marketing is customer- oriented and aims to meet the needs and expectations of customers to increase their...

Current Computational Trends in Equipment Prognostics

J. Wesley Hines, Alexander Usynin
Pages: 94 - 102
CURRENT COMPUTATIONAL TRENDS IN EQUIPMENT PROGNOSTICS The article overviews current trends in research studies related to reliability prediction and prognostics. The trends are organized into three major types of prognostic models: failure data models, stressor models, and degradation models. Methods...

Fuzzy Approaches to Flexible Querying in XML Retrieval

Stefania Marrara, Gabriella Pasi
Pages: 95 - 103
In this paper we review some approaches to flexible querying in XML that apply several techniques among which Fuzzy Set Theory. In particular we focus on FleXy, a flexible extension of XQuery-FT that was developed as a library on the open source engine Base-X. We then present PatentLight, a tool for...

Double Circuit EHV Transmission Lines Fault Location with RBF Based Support Vector Machine and Reconstructed Input Scaled Conjugate Gradient Based Neural Network

K. Gayathri, N. Kumarappan
Pages: 95 - 105
A new algorithm is developed to enhance the solution for the problems associated with double circuit transmission lines for the mutual coupling between the two circuits under fault conditions and which is highly variable in nature. The algorithm depends on the three-line voltages and the six line currents...

Exponential stability analysis for delayed stochastic Cohen-Grossberg neural network

Guanjun Wang, Jinling Liang
Pages: 96 - 102
In this paper, the exponential stability problems are addressed for a class of delayed Cohen-Grossberg neural networks which are also perturbed by some stochastic noises. By employing the Lyapunov method, stochastic analysis and some inequality techniques, sufficient conditions are acquired for checking...

Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

Yi Xiao, Jin Xiao, Fengbin Lu, Shouyang Wang
Pages: 96 - 114
Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural...

Enhanced Particle Swarm Optimization Based on Reference Direction and Inverse Model for Optimization Problems

Wei Li, Yaochi Fan, Qingzheng Xu
Pages: 98 - 129
While particle swarm optimization (PSO) shows good performance for many optimization problems, the weakness in premature convergence and easy trapping into local optimum, due to the ignorance of the diversity information, has been gradually recognized. To improve the optimization performance of PSO,...

Particle Swarm Optimization with Novel Processing Strategy and its Application

Yuanxia Shen, Wang, Chunmei Tap
Pages: 100 - 111
The loss of population diversity is one of main reasons which lead standard particle swarm optimization (SPSO) to suffer from the premature convergence when solving complex multimodal problems. In SPSO, the personal experience and sharing experience are processed with a completely random strategy. It...

Missing values estimation and consensus building for incomplete hesitant fuzzy preference relations with multiplicative consistency

Yejun Xu, Caiyun Li, Xiaowei Wen
Pages: 101 - 119
This paper proposes a decision support process for incomplete hesitant fuzzy preference relations (HFPRs). First, we present a revised definition of HFPRs, in which the values are not ordered for the hesitant fuzzy element. Second, we propose a method to normalize the HFPRs and estimate the missing elements...

Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm

Xiao-ming You, Sheng Liu, Yu-ming Wang
Pages: 101 - 113
A novel Parallel Ant Colony Optimization Algorithm based on Quantum dynamic mechanism for traveling salesman problem (PQACO) is proposed. The use of the improved 3-opt operator provides this methodology with superior local search ability; several antibody diversification schemes were incorporated into...

A New Fuzzy MADM Approach and its Application to Project Selection Problem

Ali Pahlavani
Pages: 103 - 114
In this paper, a novel fuzzy MADM model with some specifications that make it distinguished from the available methods. Decision matrix is defined as a full fuzzy structure. The model only uses information on the alternatives i.e. does not require pre-assigned weight values for the attributes. The weights...

New Vector Ordering in the RedGreenBlue Colour Model with Application to Morphological Image Magnification

Valérie de Witte, Stefan Schulte, Etienne E. Kerre
Pages: 103 - 115
In this paper we present a new vector ordering ≤RGB for colours modelled in the RedGreenBlue colour model. The RedGreenBlue colour model becomes with this new ordering and associated minimum and maximum operators a complete lattice. We also have defined a complement co for colours in the RedGreenBlue...

The Influence of the Update Dynamics on the Evolution of the Cooperation

Carlos Grilo, Luis Correia
Pages: 104 - 114
We investigate the influence of the update dynamics on the evolution of cooperation. Three of the most studied games in this area are used: Prisoner’s Dilemma, Snowdrift and the Stag Hunt. Previous studies with the Prisoner’s Dilemma game reported that less cooperators survive with the asynchronous...

Computer Aided Diagnosis System-A Decision Support System for Clinical Diagnosis of Brain Tumours

Puneet Tiwari, Jainy Sachdeva, Chirag Kamal Ahuja, Niranjan Khandelwal
Pages: 104 - 119
The iso, hypo or hyper intensity, similarity of shape, size and location complicates the identification of brain tumors. Therefore, an adequate Computer Aided Diagnosis (CAD) system is designed for classification of brain tumor for assisting inexperience radiologists in diagnosis process. A multifarious...

Voronoi Fuzzy Clustering Approach for Data Processing in WSN

S. Nithyakalyani, S. Suresh Kumar
Pages: 105 - 113
Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent...

Weighting Under Ambiguous Preferences and Imprecise Differences in a Cardinal Rank Ordering Process

Mats Danielson, Love Ekenberg, Aron Larsson, Mona Riabacke
Pages: 105 - 112
The limited amount of good tools for supporting elicitation of preference information in multi-criteria decision analysis (MCDA) causes practical problem. In our experiences, this can be remedied by allowing more relaxed input statements from decision-makers, causing the elicitation process to be less...

Solutions to Open Problems on Fuzzy Filters of -algebras

Wang Wei, Arsham Borumand Saeid
Pages: 106 - 113
This paper focuses on the investigation of fuzzy filters of -algebras, an important and popular generic logical algebra. By studying the equivalent conditions of fuzzy fantastic filter and fuzzy normal filter of -algebras, the relation between these two filters are revealed. Two open problems of -algebras,...

Multi-Scale Fuzzy Feature Selection Method applied to Wood Singularity Identification

Vincent BOMBARDIER, Laurent WENDLING
Pages: 108 - 122
A multi-scale feature selection method based on the Choquet Integral is presented in this paper. Usually, aggregation decision-making problems are well solved, relying on few decision rules associated to a small number of input parameters. However, many industrial applications require the use of numerous...

Hesitant Fuzzy Filters in BE-algebras

Akbar Rezaei, Arsham Borumand Saeid
Pages: 110 - 119
In this paper, we introduce the notion of hesitant fuzzy (implicative) filters and get some results on BE-algebras and show that every hesitant fuzzy implicative filter is a hesitant fuzzy filter but not the converse. Finally, we state and prove the relationship between hesitant fuzzy (implicative) filters...

Anesthesiology Nurse Scheduling using Particle Swarm Optimization

Leopoldo Altamirano, María Cristina Riff, Ignacio Araya, Lorraine Trilling
Pages: 111 - 125
In this article we present an approach designed to solve a real world problem: the Anesthesiology Nurse Scheduling Problem (ANSP) at a public French hospital. The anesthesiology nurses are one of the most shared resources in the hospital and we attempt to find a fair/balanced schedule for them, taking...

Incremental Versus Non-incremental: Data and Algorithms Based on Ordering Relations

Xiuyi Jia, Lin Shang, Jiajun Chen, Xinyu Dai
Pages: 112 - 122
Based on multi-dominance discernibility matrices, a non-incremental algorithm RIDDM and an incremental algorithm INRIDDM are proposed by means of Dominance-based Rough Set Approach. For the incremental algorithm, when a new object arrives, after updating one row or one column in the matrix, we could...

Offline recognition of degraded numeral characters with MMTD-based fuzzy classifiers

Weiqing Cheng, Long Hong, Shaobai Zhang
Pages: 113 - 120
Enabling machines to read like human beings has been a hot issue for more than fifty years. A novel offline degraded numeral recognition method (DNRBM) based on the measure of medium truth degree (MMTD) is proposed in this paper to identify segmented degraded numeral characters in gray images. It consists...

Interval-Valued Linear Model

Xun Wang, Shoumei Li, Thierry Denœux
Pages: 114 - 127
This paper introduces a new type of statistical model: the interval-valued linear model, which describes the linear relationship between an interval-valued output random variable and real-valued input variables. Firstly, notions of variance and covariance of set-valued and interval-valued random variables...

Research on Inventory Control Policies for Nonstationary Demand based on TOC

Leng Kaijun, Wang Yuxia
Pages: 114 - 128
An effective inventory replenishment method employed in the supply chain is one of the key factors to achieving low inventory while maintaining high customer delivery performance. The state of demand process is often not directly observed by the decision maker. Thus, in many literatures, the inventory...

The process incapability index under fuzziness with an application for decision making

İhsan Kaya
Pages: 114 - 128
Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined capability prerequisite. They have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). The PCIs have been successfully applied by companies...

Optimal IP Assignment for Efficient NoC-based System Implementation using NSGA-II and MicroGA

Marcus Vinicius Carvalho da Silva, Nadia Nedjah, Luiza de Macedo Mourelle
Pages: 115 - 123
Network-on-chip (NoC) are considered the next generation of communication infrastructure, which will be omnipresent in most of industry, office and personal electronic systems. In platform-based methodology, an application is implemented by a set of collaborating intellectual properties (IPs) blocks....

On aggregation of metric structures: the extended quasi-metric case

Sebastià Massanet, Oscar Valero
Pages: 115 - 126
In 1981, J. Borsík and J. Doboš studied and solved the problem of how to merge, by means of a function, a (not necessarily finite) collection of metrics in order to obtain a single one as output. Later on, in 2010, G. Mayor and O. Valero proposed and solved the Borsík and Doboš...

Similarity Measuring Approach for Engineering Materials Selection

H. Doreswamy, M.N. Vanajaskhi
Pages: 115 - 122
Advanced engineering materials design involves the exploration of massive multidimensional feature spaces, the correlation of materials properties and the processing parameters derived from disparate sources. The search for alternative materials or processing property strategies, whether through analytical,...

Language Identification of Kannada, Hindi and English Text Words Through Visual Discriminating Features

M.C. Padma, P.A. Vijaya
Pages: 116 - 126
In a multilingual country like India, a document may contain text words in more than one language. For a multilingual environment, multi lingual Optical Character Recognition (OCR) system is needed to read the multilingual documents. So, it is necessary to identify different language regions of the document...

Toward Automated Quality Classification via Statistical Modeling of Grain Images for Rice Processing Monitoring

Jinping Liu, Zhaohui Tang, Qing Chen, Pengfei Xu, Wenzhong Liu, Jianyong Zhu
Pages: 120 - 132
Computer vision-based rice quality inspection has recently attracted increasing interest in both academic and industrial communities because it is a low-cost tool for fast, non-contact, nondestructive, accurate and objective process monitoring. However, current computer-vision system is far from effective...

The linguistic intuitionistic fuzzy set TOPSIS method for linguistic multi-criteria decision makings

Yue Ou, Liangzhong Yi, Bin Zou, Zheng Pei
Pages: 120 - 132
In the paper, we express uncertain assessments information in linguistic multi-criteria decision makings (LMCDMs) as linguistic intuitionistic fuzzy sets, i.e., the decision maker provides membership and non-membership fuzzy linguistic terms to represent uncertain assessments information of alternatives...

Linguistic hesitant intuitionistic fuzzy cross-entropy measures

Wei Yang, Yongfeng Pang, Jiarong Shi
Pages: 120 - 139
In this paper, several cross-entropy measures for linguistic hesitant intuitionistic fuzzy information have been developed which integrating cross-entropy measures of intuitionistic fuzzy sets and hesitant fuzzy linguistic sets. Some desirable properties of new cross-entropy measures have been studied....

Applicability of artificial bee colony algorithm for nurse scheduling problems

Kadir Buyukozkan, Ahmet Sarucan
Pages: 121 - 136
This paper describes the first Artificial Bee Colony (ABC) Algorithm approach applied to nurse scheduling evaluated under different working environments. For this purpose, the model has been applied on a real hospital where data taken from different departments of the hospital were used and the schedules...

Fuzzy Regression Control Chart Based on α-cut Approximation

Sevil Sentürk
Pages: 123 - 140
The fuzzy regression control chart is a functional technique to evaluate the process in which the average has a trend and the data represents a linguistic or approximate value. In this study, the theoretical structure of the “α-level fuzzy midrange for α-cut fuzzy X -regression control chart” is proposed...

A New Minkowski Distance Based on Induced Aggregation Operators

José Merigo, Montserrat Casanovas
Pages: 123 - 133
The Minkowski distance is a distance measure that generalizes a wide range of distances such as the Hamming and the Euclidean distance. In this paper, we develop a generalization of the Minkowski distance by using the induced ordered weighted averaging (IOWA) operator. We call it the induced Minkowski...

Reduced computational cost prototype for street theft detection based on depth decrement in Convolutional Neural Network. Application to Command and Control Information Systems (C2IS) in the National Police of Colombia.

Julio Suarez-Paez, Mayra Salcedo-Gonzalez, M. Esteve, J.A. Gómez, C. Palau, I. Pérez-Llopis
Pages: 123 - 130
This paper shows the implementation of a prototype of street theft detector using the deep learning technique R-CNN (Region-Based Convolutional Network), applied in the Command and Control Information System (C2IS) of National Police of Colombia, the prototype is implemented using three models of CNN...

Cellular Neural Networks-Based Genetic Algorithm for Optimizing the Behavior of an Unstructured Robot

Alireza Fasih, Jean Chamberlain Chedjou, Kyandoghere Kyamakya
Pages: 124 - 131
A new learning algorithm for advanced robot locomotion is presented in this paper. This method involves both Cellular Neural Networks (CNN) technology and an evolutionary process based on genetic algorithm (GA) for a learning process. Learning is formulated as an optimization problem. CNN Templates are...

Commercial Territory Design for a Distribution Firm with New Constructive and Destructive Heuristics

Jaime Cano-Belmán, RogerZ. Ríos-Mercado, M. Angélica Salazar-Aguilar
Pages: 126 - 147
A commercial territory design problem with compactness maximization criterion subject to territory balancing and connectivity is addressed. Four new heuristics based on Greedy Randomized Adaptive Search Procedures within a location-allocation scheme for this NP-hard combinatorial optimization problem...