International Journal of Computational Intelligence Systems

Distributed Permutation Flowshop Scheduling Problem (DPFSP) is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper,...

Personalized individual semantics (PIS) exist widely in our daily life, and it means that different people have different understandings regarding the same word. In decision making, decision makers are accustomed to express their preferences using a linguistic way, and it is naturally that the PIS will...

This paper proposes the combination of Swarm Intelligence algorithm of artificial bee colony with heuristic scheduling algorithm, called Heuristic Task Scheduling with Artificial Bee Colony (HABC). This algorithm is applied to improve virtual machines scheduling solution for cloud computing within homogeneous...

In this paper the Borda rule is extended by allowing the voters to show their preferences among alternatives through linguistic labels. To this aim, we need to add them up for assigning a qualification to each alternative and then to compare such qualifications. Theoretically, all these assessments and...

In this paper, we define hesitant fuzzy partitions (H-fuzzy partitions) to consider the results of standard fuzzy clustering family (e.g. fuzzy c-means and intuitionistic fuzzy c-means). We define a method to construct H-fuzzy partitions from a set of fuzzy clusters obtained from several executions of...

Patent classification systems are applied extensively in innovative analysis. Existing patent classification schemes are either technology-dependent or TRIZ-based. The former ones, such as the IPC and UPC, are normally developed by different patent offices in the world mainly for the purpose of patentability...

The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain...

In this study, to overcome navigation concerns of visually impaired people, an algorithm based on neuro-fuzzy controller composed of multi-layer fuzzy inference systems (FIS) for obstacle avoidance was developed and it was implemented in a smart clothing system. The success of the proposed algorithm...

Large-scale spam emails cause a serious waste of time and resources. This paper investigates the text features of email documents and the feature noises among multi-field texts, resulting in an observation of a power law distribution of feature strings within each text field. According to the observation,...

The key frames extraction technique extracts key postures to describe the original motion sequence, which has been widely used in motion compression, motion retrieval, motion edition and so on. In this paper, we propose a method based on the amplitude of curve to find key frames in a motion captured...

It is very important to enhance the accuracy of financial crisis prediction (FCP). Because the traditional probabilistic neural network (PNN) has some deficiencies, such as the difficult estimation of parameters and the high computational complexity, this paper proposes a new combination model, which...

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...

The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement system, fuzzy control charts are available tools for monitoring and evaluating...

Teaching-learning based optimization is a newly developed intelligent optimization algorithm. It imitates the process of teaching and learning simply and has better global searching capability. However, some studies have shown that TLBO is good at exploration but poor at exploitation and often falls...

The main purpose of any facility location is to select the optimal places that satisfy project's goals. In location problems, the object is usually to optimize a function - objective function - that defines the problem conditions and efficient decision parameters. Numerous methods are proposed to challenge...

In this short paper, the label printing problem (LPP) is investigated. The LPP can be formulated as a nonlinear integer programming problem and it aims to minimize the total wastage of labels under a fixed number of templates with subject to the minimal required quantities of various labels. Since the...

In this paper, we present a new integration approach for managing Information Technology variables within enterprise architecture in an integrated way. Additionially, a novel method based on fuzzy logic for cause-effect variable analysis is proposed as a useful support decision-making tool for companies...

High utility pattern mining is an emerging research topic in the data mining field. Unlike frequent pattern mining, high utility pattern mining deals with non-binary databases, in which the information about purchased quantities of items is maintained. Due to the non-existence of anti-monotone property...

In some cases, the relationship between an object set and an attribute set is set up by means of a fuzzy context sequence. A particular case of this situation appears when we want to study the evolution of an L-fuzzy context in time.

Aiming at the diversity of Nondominated Sorting Genetic Algorithm II (NSGA-II) in screening out nondominated solutions, a crowding distance elimination (CDE) method is proposed. Firstly, the crowding distance is calculated in the same level of nondominated solutions, and the solution of minimum crowding...

In the present paper, we introduce a new axiomatic definition of the inclusion measure for intuitionistic fuzzy sets (IFSs, for short). The close relationships among entropy, similarity measure, and inclusion measure of IFSs are then discussed in detail. Also, we obtain some important theorems by which...

The aim of the paper is to discuss some new operations on hesitant fuzzy linguistic terms sets based on Archimedean t-norm and t-conorm. The advantage is that the operations on hesitant fuzzy linguistic terms sets are closed, by studying propositions of the operations on hesitant fuzzy linguistic terms...

No-wait flowshop scheduling problem (NW-FSSP) with the objective to minimize the makespan is an important sequencing problem in the production plans and applications of no-wait flowshops can be found in several industries. In a NW-FSSP, jobs are not allowed to wait between two successive machines. The...

Ranking of triangular intuitionistic fuzzy numbers (TIFNs) is an important problem, which is solved by the value and ambiguity based ranking method developed in this paper. Firstly, the concept of TIFNs is introduced. Arithmetic operations and cut sets over TIFNs are investigated. Then, the values and...

Based on the Choquet integral and the generalized Shapley function, two new induced Atanassov's interval-valued intuitionistic fuzzy hybrid aggregation operators are defined, which are named as the induced generalized Shapley Atanassov's interval-valued intuitionistic fuzzy hybrid Choquet arithmetical...

New products are appearing in the marketplace at an ever-increasing step. Their launching is either market driven, or technology driven. Pricing and warranty policies play a vital role in launching of a new product, consequently growth of a company. In this paper a decision model is proposed to determine...

In previous work we presented CoCoNAD (Continuous-time Closed Neuron Assembly Detection), a method to find significant synchronous patterns in parallel point processes with the goal to analyze parallel neural spike trains in neurobiology3,9. A drawback of CoCoNAD and its accompanying methodology of pattern...

In the cloud storage system, data sets replicas technology can efficiently enhance data availability and thereby increase the system reliability by replicating commonly used data sets in geographically different data centers. Most current approaches largely focus on system performance improvement by...

Community detection structure is very important for understanding the organization of the complex networks. This problem is NP-hard, which is modeled as a seriously nonlinear optimization problem. Recently, different intelligence algorithm has shown promising results for this problem. The chemical reaction...

In this paper we present a new version of a GP financial forecasting tool, called EDDIE 8. The novelty of this version is that it allows the GP to search in the space of indicators, instead of using pre-specified ones. We compare EDDIE 8 with its predecessor, EDDIE 7, and find that new and improved solutions...

Resource-constraint multi-project scheduling is one of the most important topic in the field of project management. Most current works solve this problem based on an idea that multiple projects can be simply emerged into a super-project in a deterministic environment, regardless of the project priority...

Bio-inspired visual attention models human visual system to detect the most salient part of a visual field. In the existing diversified computational models, bottom-up visual attention that works out a saliency map to indicate the conspicuity of visual stimuli in an image has gained much popularity....

This paper proposes an enhanced Multi-objective Go with the Winners (MOGWW) algorithm to solve multi-objective combinatorial optimization problems. The original MOGWW algorithm is equipped with the well known Pareto Local Search (PLS) procedure. In order to assess the performance of the hybridization,...

In this study, a fuzzy multi-response standard ready-mixed concrete (SRMC) optimization problem is addressed. This problem includes two conflicting quality optimization objectives. One of these objectives is to minimize the production cost. The other objective is to assign the optimal parameter set of...

This paper presents a conceptual framework for ecological function allocation and optimization matching solution for a human-machine interface with intelligent characteristics by “who does what and when and how” consideration. As a highlighted example in nature-social system, intelligent transportation...

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...

This paper presents an efficient modified particle swarm optimization (EMPSO) algorithm for solving mixed-integer nonlinear programming problems. In the proposed algorithm, a new evolutionary strategies for the discrete variables is introduced, which can solve the problem that the evolutionary strategy...

This work presents an accurate and smooth functional link artificial neural network (FLANN) for classification of noisy database. The accuracy and smoothness of the network is taken birth by suitably tuning the parameters of FLANN using differential evolution and filter based feature selection. We use...

We propose optimal priority methods on the incomplete intuitionistic fuzzy preference relation (IFPR) and the incomplete interval preference relation (IPR). The least squares method has been used previously to derive the priority vector of the fuzzy preference relation (FPR). In this paper, we generalize...

The essence characteristics of software trustworthiness are software execution effect and behavior can be anticipated, which is an important index of software quality. Under the open and dynamic environments, some uncertainty factors cause the behavior of software to be uncontrolled, uncertainty and...

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....

Monotonic classification is a special task in machine learning and pattern recognition. As to monotonic classification, it is assumed that both features and decision are ordinal and there is the monotonicity constraints between the features and decision. Little work has been focused on feature selection...

Sentiment classification is a fundamental task in NLP, and its aim to predict the sentiment polarities of the given texts. Recent researches show great interest in modeling Chinese sentiment classification. However, the complexity of Chinese grammar makes the performance of the existing Chinese sentiment...

Biogeography-based optimization (BBO) algorithm is based on species migration between habitats to complete information circulation and sharing, which achieves the global optimization by improving the adaptability of habitats. In this paper, the basic migration balance model of biogeography theory is...

Approximation computation is a critical step in rough sets theory used in knowledge discovery and other related tasks. In practical applications, an information system often evolves over time by the variation of attributes or objects. Effectively computing approximations is vital in data mining. Dominance-based...

Multi-objective evolutionary algorithms have been criticized when they are applied to classification rule mining, and, more specifically, in the optimization of more than two objectives due to their computational complexity. It is known that a multi-objective space is much richer to be explored than...

Based on the extension Hukuhara difference between interval numbers, a generalized form of cooperative fuzzy games with a coalition structure and interval payoffs is proposed, which can be seen as an extension of crisp case. The interval Owen value for this kind of fuzzy games is studied, and its explicit...

The TODIM (an acronym in Portuguese for interactive multicriteria decision-making) method can consider the decision-makers’ (DMs’) psychological behavior. However, the classical TODIM method has been unable to address fuzzy information such as the linguistic neutrosophic number (LNN), which is an effective...

The variability in travel times is a very important feature in determining the arrival of the passenger at the destination within a given travel time threshold and can be noted as one of the most important characteristic for travel time reliability that is an increasing concern of travelers, because...

Aircraft's availability is certainly one of the most important features of modern avionic industry. The aircraft maintenance scheduling is one of the major decisions an airline has to make during its operation. When an aircraft maintenance event occurs, the overhaul tasks management process requires...

In normal operation, doubly-fed induction generator (DFIG) can generate certain range of reactive power and the DFIG based wind farm can participate in reactive power control of grid as a reactive power supply. This paper proposes one multi-objective power dispatch optimization model which considers...

Supplier selection is a multiattribute decision making (MADM) problem which contains both qualitative and quantitative factors. Supplier selection has vital importance for most companies. The aim of this paper is to provide an AHP based analytical tool for decision support enabling an effective multicriteria...

The evaluation of the players' performance in sports teams is commonly based on the opinion of experts who do not always agree on the importance of the chosen indicators. This paper presents a novel approach based on fuzzy multi-criteria group decision-making tools for selecting those criteria that...

In the last five years, deep learning methods and particularly Convolutional Neural Networks (CNNs) have exhibited excellent accuracies in many pattern classification problems. Most of the state-of-the-art models apply data-augmentation techniques at the training stage. This paper provides a brief tutorial...

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...

Based on our previous researchs about generalized modus ponens (GMP) with linguistic modifiers for If … Then rules, this paper proposes new generalized modus tollens (GMT) inference rules with linguistic modifiers in linguistic many–valued logic framework with using hedge moving rules for...

This paper presents a parameterized schema for building memetic algorithms based on cross-entropy (CE) methods. This novel schema is general in nature, and features multiple probability mass functions and Lamarckian learning. The applicability of the approach is assessed by considering the Tool Switching...

This paper mainly provides one new nature inspired Energy Conversation Optimization (ECO) method to search for the optimal sensor position of sensor network in the typical tunnels, fully covering the tunnel and dynamically locating the high-speed train in the tunnel. Firstly, one objective of this study...

Group decision-making can effectively deal with complex decision problems in reality and takes important research status in the field of decision-making. In recent years, three-way decision has been a hot topic in the field of uncertain decision-making, so the models of three-way decision under group...

During the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational...

To improve the accuracy of automatic recognition and classification of vegetables, this paper presents a method of recognition and classification of vegetable image based on deep learning, using the open source deep learning framework of Caffe, the improved VGG network model was used to train the vegetable...

In this work we present the first stage of a two-stage approach for designing rapid transit networks, where the stations and links to be constructed are selected by solving an integer linear optimization model that maximizes an estimation of the number of trips through the rapid transit network. It is...

Service disruptions due to deliberate sabotage are serious threats to supply systems. To alleviate the loss of accessibility caused by such disruptions, identifying the system vulnerabilities that would be worth strengthening is a critical problem in the field of Critical Infrastructure Protection (CIP)....

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...

The paper reports a study of nonlinear nature of face image. A novel feature extraction method using state space feature parameter for the recognition of face images is studied. The results of simulation experiments performed on the standard AT & T face database using both Artificial Neural Network and...

Ant colony optimization (ACO) takes inspiration from the foraging behaviour of real ant species. This ACO exploits a similar mechanism for solving optimization problems for the various engineering field of study. Many successful implementations using ACO are now available in many applications. This paper...

Mobile ad-hoc network (MANET) is a dynamic collection of mobile computers without the need for any existing infrastructure. Nodes in a MANET act as hosts and routers. Designing of robust routing algorithms for MANETs is a challenging task. Disjoint multipath routing protocols address this problem and...

Interactive genetic algorithms have been used in a wide variety of applications and extensively developed to facilitate the personalization and customization of products for users. However, the ambiguity effect or cognitive ambiguity of users during the product customization process will affect the effects...

In this work, the axiomatical definition of similarity measure, distance measure and inclusion measure for interval-valued intuitionistic fuzzy soft set (IVIFSSs) are given. An axiomatical definition of entropy measure for IVIFSSs based on distance is firstly proposed, which is consistent with the axiomatical...

In multi-attribute group decision making (MAGDM) problems, decision attributes of alternatives are often considered as with quantitative and qualitative information. Therefore decision making problems may include preference information in different formats. In this paper, a multi-attribute group decision...

Successful blogs receive high ratings and generate marketing value. What factors contribute to the success of a blog and how to predict its success level are questions worth discussing. A hybrid swam intelligence approach is proposed in this study to predict blog success level. First, this study develops...

Covering algorithms (CAs) constitute a type of inductive learning for the discovery of simple rules to predict future activities. Although this approach produces powerful models for datasets with discrete features, its applicability to problems involving noisy or numeric (continuous) features has been...

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...

With explosive growth of the astronomical data, astronomy has become a representative data-rich discipline so as to defy traditional research methodologies and paradigm to analyze data and discover new knowledge from the data. How to effectively process and analyze the astronomical data is a fundamental...

Multi-view learning analyzes the information from several perspectives and has largely been applied on semi-supervised contexts. It has not been extensively analyzed for inducing interpretable rule-based classifiers. We present a multi-view and grammar-based genetic programming model for inducing rules...

Social networks existing among employees, customers or other types of users of various IT systems have become one of the research areas of growing importance. Data about people and their interactions that exist in social media, provides information about many different types of relationships within one...

In this paper, a temperature control in real time control process was presented using several control algorithms. A quantitative comparison based on the real power consumption and (the precision and the robustness) of these controllers during the same control process and under the same conditions will...

SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis is a commonly used and an important technique for analyzing internal and external environments in order to provide a systematic approach and support for a decision making. SWOT is criticized mostly for considering only qualitative examination...

Tap changing operations of multiple transformers at a substation is a complex problem due to issues in controlling the parallel operations of the transformers involved, differences in manufacturer's design and inaccuracy of the measures. In earlier work Artificial Neural Network (ANN) based tap changer...

To solve the interval-valued intuitionistic fuzzy decision-making problems with high-dimension data, the fuzzy matrix is extended to the fuzzy tensor in this paper. Based on the constructed tensor definition, we propose the generalized interval-valued intuitionistic fuzzy weighted averaging (GIIFWA)...

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...

Multi-Objective Particle Swarm Optimizers (MOPSOs) are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO) is proposed to address these issues. In CEPSO, Multi-objective Optimization...

Prospect theory is a very effective method to express behavioral decision making under uncertainty. This paper attempts to develop a method to multi-attribute decision making with Atanassov's interval-valued intuitionistic fuzzy information using prospect theory. This method first transforms Atanassov's...

In this work we analyze the key issue of the relationship that should hold between the operators in a family {} of aggregation operators in order to understand they properly define a whole. Here we extend some of the ideas about stability of a family of aggregation operators into a more general framework,...

This paper presents a novel method on building relationship between the vision features of the terrain images and the terrain traversability which manifests the difficulty of field robot traveling across one terrain. Vision features of the image are extracted based on color and texture. The travesability...

For secure biometric verification, most existing methods embed biometric information directly into the cover image, but content correlation analysis between the biometric image and the cover image is often ignored. In this paper, we propose a novel biometric image hiding approach based on the content...

Fast-growing scientific papers bring the problem of rapidly and accurately finding a list of reference papers for a given manuscript. Reference paper recommendation is an essential technology to overcome this obstacle. In this paper, we study the problem of personalized query-focused astronomy reference...

Nowadays, children have access to Internet on a regular basis. Just like the real world, the Internet has many unsafe locations where kids may be exposed to inappropriate content in the form of obscene, aggressive, erotic or rude comments. In this work, we address the problem of detecting erotic/sexual...

In this research we applied classification models for prediction of students’ performance, and cluster models for grouping students based on their cognitive styles in e-learning environment. Classification models described in this paper should help: teachers, students and business people, for early...

A Subject-Action-Object (SAO) is a triple structure which can be used to both describe topics in detail and explore the relationship between them. SAO analysis has become popular in bibliometrics, however there are two challenges in the identification of SAO structures: low relevance of SAOs to domain...

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...

This study presents detection of pulmonary disorders using different spectral analysis methods such as fast Fourier transform, autoregressive and the autoregressive moving average. Power spectral densities of the sounds were estimated through these methods. Feature vectors were constructed by extracting...

An approach based on relative optimal membership degree is proposed to deal with multiple attribute decisionmaking (MADM) problems under risk with weight information unknown and attribute value as linguistic variable. Firstly, the operational laws of linguistic variable are introduced, and risk linguistic...

Artificial Bee Colony (ABC) algorithm inspired by the intelligent source search and consumption characteristics of the real honey bees is one of the most powerful optimization techniques. Although the existing behaviours of the honey bees in standard ABC algorithm are capable of producing optimal or...

Due to the advantages of Fuzzy reasoning Petri-nets(FPN)on uncertain and incomplete information processing. It is a promising technique to solve the complex power system fault-section estimation problem. Therefore, we propose a novel estimation method based on Adaptive Fuzzy Petri Nets (AFPN), in this...

Metaheuristics has attained increasing interest for solving complex real-world problems. This paper studies the principles and the state-of-the-art of metaheuristic methods for engineering optimization. Both the classic and emerging approaches to optimization using metaheuristics are reviewed and analyzed....

The Sloan Digital Sky Survey (SDSS) has been one of the most successful sky surveys in the history of astronomy. To map the universe, SDSS uses their telescopes to take pictures of the sky over the whole survey area. Now the total SDSS data volume is larger than 125 TB since every night telescopes produce...

Among the various discriminant analysis (DA) methods, researchers have investigated several directions in this area: statistics, econometrics, computer data mining technologies and mathematical programming. Recently, as a nonparametric mathematical programming approach, Data envelopment analysis has...