International Journal of Computational Intelligence Systems

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...

In this paper, the problem of qualitative description and quantitative optimization for tactical reconnaissance agents system organization is considered with objective of higher teamwork efficiency and more reasonable task balancing strategies. By analyzing tactical reconnaissance system and its environment,...

The paper demonstrates performance enhancement using selective cloning on evolutionary neural network over the conventional genetic algorithm and neural back propagation algorithm for data classification. Introduction of selective cloning improves the convergence rate of the genetic algorithm without...

E-commerce has grown exponentially in the past decade in global market. In China most E-commerce enterprises are small and medium-sized (SMEs). Compared to their large-sized counterparts, SMEs have to face many obstacles when extending their E-commerce businesses. In view of the complexity and periodicity...

This paper presents a hybrid wavelet-fuzzy based multiresolution (MR) controller for robust speed control of induction motor. The discrete wavelet transform (DWT) is used to decompose the error between the actual speed and command speed of the induction motor drive in to different frequency components....

In this paper, we analyze the stability and convergence of a one-layer neural network proposed by Gao and Wang, which is designed to solve a class of horizontal linear complementarity problems. The globally asymptotical stability and globally exponential stability of this network are proved strictly...

Sepsis is a life-threatening condition that arises when the body's response to infection causes injury to its own tissues and organs. Despite the advancement of medical diagnosis and treatment technologies, the morbidity and mortality of sepsis are still relatively high. In this paper, a two-layer...

Currently, researches on content based image copy detection mainly focus on robust feature extraction. However, most of existing approaches use only a single feature to represent an image for copy detection, which is often insufficient to characterize the image content. Besides, with the exponential...

This paper proposes the concept of intervention rule which tries to reveal the interventional relationship between elements in a system in the following three aspects. (1) Casual relationship. Intervention rule shows which element is the cause and which element is the consequence. (2) Quantitative relationship:...

In some cases, the specification limits of a quality characteristic should be defined under uncertain information. In the literature, process capability analyses have been handled by using type-1 fuzzy sets under fuzziness up to now. In this paper, we develop the concept of type-2 fuzzy quality and use...

Recurrent neural network (RNN) is one of the most popular architectures for addressing variable sequence text, and it shows outstanding results in many natural language processing (NLP) tasks and remarkable performance in capturing long-term dependencies. Many models have achieved excellent results based...

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...

Bilevel optimization are often addressed in an organizational hierarchy in which the upper level decision maker is the leader and the lower level decision maker is the follower. The leader frequently cannot obtain complete information from the follower. As a result, the leader most tends to be risk-averse,...

The performance of Differential Evolution (DE) for multiobjective optimization problems (MOPs) can be greatly enhanced by hybridizing with other techniques. In this paper, a new hybrid DE incorporating preference based local search is proposed. In every generation, a set of nondominated solutions is...

Vertical mining methods are very effective for mining frequent patterns and usually outperform horizontal mining methods. However, the vertical methods become ineffective since the intersection time starts to be costly when the cardinality of tidset (tid-list or diffset) is very large or there are a...

Currently Mutual Information has been widely used in pattern recognition and feature selection problems. It may be used as a measure of redundancy between features as well as a measure of dependency evaluating the relevance of each feature. Since marginal densities of real datasets are not usually known...

In this paper, Fuzzy Linear Programming (FLP) was used to model the production processes at a university-based bakery for optimal decisions in the daily productions of the bakery. Using the production data of five products from the bakery, a fuzzy linear programme was developed to help make decisions...

Although timely access to information is becoming increasingly important and gaining such access is no longer a problem, the capacity for humans to assimilate such huge amounts of information is limited. Topic Detection(TD) is then a promising research area that addresses speedy access of desired information....

A two-phase online anomaly detection method based on support vector clustering (SVC) in the presence of non-stationary data is developed in this paper which permits arbitrary-shaped data clusters to be precisely treated. In the first step, offline learning is performed to achieve an appropriate detection...

Technology that detects user personality based on user speech signals must be researched to enhance the function of interaction between a user and virtual agent that takes place through a speech interface. In this study, personality patterns were automatically classified as either extroverted or introverted....

This paper analyzes the collective behaviors of swarm robots that play role in the aggregation scenario. Honeybee aggregation is an inspired behavior of young honeybees which tend to aggregate around an optimal zone. This aggregation is implemented based on variation of parameters values. In the second...

Now, there are a lot of multiobjective evolutionary algorithms (MOEAs) available and these MOEAs argue that they are competitive. In fact, these results are generally unfair and unfaithful. In order to make fair comparison, comprehensive performance index system is established. The weights among the...

Several real-world situations can be modeled as maximal covering location problem (MCLP), which is focused on finding the best locations for a certain number of facilities that maximizes the coverage of demand nodes located within a given exact coverage distance (or travel time). In a real scenario,...

The type-2 fuzzy logic system permits us to model uncertainties existing in membership functions. Accordingly, this study aims to propose a linear and a piecewise framework for an interval type-2 fuzzy regression model based on the existing possibilistic models. In this model, vagueness is minimized,...

Conventional nonnegative matrix factorization and its variants cannot separate the noise data space into a clean space and learn an effective low-dimensional subspace from Salt and Pepper noise or Contiguous Occlusion. This paper proposes a weighted nonnegative matrix factorization (WNMF) to improve...

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...

This study addresses the construction of Takagi-Sugeno-Kang (TSK) fuzzy models by means of clustering. A contribution-factor based fuzzy min-max neural network (CFMN) is developed based on Simpson’s well-known fuzzy min-max neural network (FMNN) for clustering. The contribution-factor (CF) is also known...

In the last decades, nature-inspired algorithms have been widely used to solve complex combinatorial optimisation problems. Among them, Evolutionary Algorithms (EAs) and Swarm Intelligence (SI) algorithms have been extensively employed as search and optimisation tools in various problem domains. Evolutionary...

Wavelet analysis based on image enhancement technique is only applicable to black-and-white image, and pseudo-color image processing technology cannot adequately deal with some of the details information of the image. In this paper, an enhanced approach of remote sensing image based on orthogonal wavelet...

Motivated by intuitionistic fuzzy sets and fzzy linguistic approach, this article proposes the concept of linguistic intuitionistic fuzzy numbers (LIFNs) where membership and and nonmembership are represented as linguistic terms. In order to process the multiple attribute decision making (MADM) with...

In this paper, we propose an outlier detection approach based on local kernel regression for instance selection. It evaluates the reconstruction error of instances by their neighbors to identify the outliers. Experiments are performed on the synthetic and real data sets to show the efficacy of the proposed...

Establishing high performance cooperation and estimating nodes’ risk level in mobile ad hoc networks (MANETs) are currently fundamental and challenging due to the inherent characteristics of MANETs, such as the highly dynamic topology and the absence of an effective security mechanism. Trust based...

A new method is developed to solve multi-attribute group decision making (MAGDM) problem in which the attribute values, attribute weights and expert weights are all in the form of 2-tuple linguistic information. First, the operation laws for 2-tuple linguistic information are defined and the related...

We propose a semi-automatic method for the generation of educational-competency maps from repositories of multiple-choice question responses, using Bayesian structural learning and data-mining techniques. We tested our method on a large repository of responses to multiple-choice exam questions from an...

In recent years, the boom in social media sites such as Facebook and Twitter has brought people together for the sharing of opinions, sentiments, emotions, and experiences about products, events, politics, and other topics. In particular, sentiment-based applications are growing in popularity among individuals...

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....

We present a multi-objective evolutionary algorithm to exploit a medium-sized fuzzy outranking relation to derive a partial order of classes of alternatives (we call it RP2-NSGA-II). To measure the performance of RP2-NSGA-II, we present an empirical study over a set of simulated multi-criteria ranking...

Most municipal agencies are facing challenges regarding the deterioration of infrastructures due to the lack of available funds and available data. There is a need to perform infrastructure asset management for infrastructure assets in an integrated manner. This research proposes a decision making plan...

This paper presents a novel method for simultaneous feature selection and classification by incorporating a robust L1-norm into the objective function of Minimax Probability Machine (MPM). A fractional programming framework is derived by using a bound on the misclassification error involving the mean...

The faults occurring in different phases at multiple locations and different times are difficult to locate exact location using conventional techniques. This paper develops a fault location estimation approach using fuzzy inference system for multi location phase to ground faults and transforming phase...

The proportional 2-tuple linguistic model provides a tool to deal with linguistic term sets that are not uniformly and symmetrically distributed. This study further develops multi-attribute group decision making methods with linguistic assessments and linguistic weights, based on the proportional 2-tuple...

In traditional models, fuzzy sets are used to describe trust degree and evaluate reputation for vague words. But in some practical applications, the determination of membership functions associated with vague concepts is difficult or impossible. This paper builds a reputation computing model based on...

The performance of machine learning algorithms is affected by the imbalanced distribution of data among classes. This issue is crucial in various practical problem domains, for example, in medical diagnosis, network intrusion, fraud detection etc. Most efforts so far are mainly focused upon binary class...

The Bonferroni mean is a traditional mean type aggregation operator bounded by the max and min operators, which is suitable to aggregate the crisp data. In this paper, we consider situations where the input data are interval numbers. We develop some uncertain Bonferroni mean operators, and then combine...

This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS) provides the designer with a powerful...

The development of empirical classification models for fault diagnosis usually requires a process of training based on a set of examples. In practice, data collected during plant operation contain signals measured in faulty conditions, but they are ‘unlabeled’, i.e., the indication of the...

In data mining, data clustering is a prevalent data analysis methodology that organizes unlabeled data points into distinct clusters based on a similarity measure. In recent years, several clustering algorithms found, dependent on a predefined number of clusters and centered around the dataset with either...

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....

Detection of non-technical losses (NTL) which include electricity theft, faulty meters or billing errors has attracted increasing attention from researchers in electrical engineering and computer science. NTLs cause significant harm to the economy, as in some countries they may range up to 40% of the...

Trust can play an important role for the sharing of resources and information in open network environments. Trust quantification is thus an important issue in dynamic trust management. By considering the fuzziness and uncertainty of trust, in this paper, we propose a fuzzy comprehensive evaluation method...

Product design is an important phase of the new product development process and one of the most crucial decisions in marketing. In the latest two decades, a significant number of marketing decision support systems (MDSSs) for automating new product design activities have been reported in the literature...

Selecting a suitable proximity measure is one of the fundamental tasks in clustering. How to effectively utilize all available side information, including the instance level information in the form of pair-wise constraints, and the attribute level information in the form of attribute order preferences,...

The aim of this paper is to develop some new 2-tuple linguistic hybrid aggregation operators, which are called the extended 2-tuple linguistic hybrid arithmetical weighted (ET-LHAW) operator, the extended 2-tuple linguistic hybrid geometric mean (ET-LHGM) operator, the induced ET-LHAW (IET-LHAW) operator...

This paper designs a non-linear integer mathematical model for the cellular manufacturing system (CMS) with dual-resource constrained setting. The multi-functional machines and the multi-skilled workers need to be grouped and assigned to the cells. Moreover, each operation of the parts has different...

Users’ preferences have traditionally been exploited in query personalization to better serve their information needs. Most of the time, user preferences depend on context, that is, they may have different values depending on the situation of the user. In this paper, we propose a fuzzy-rule-based...

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...

Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work,...

In this study, an optimized extended Kalman filter (EKF), and an interval type-2 fuzzy sliding mode control (IT2FSMC) in presence of uncertainties and disturbances are presented for robotic manipulators. The main contribution is the proposal of a novel application of Biogeography-Based Optimization (BBO)...

Owing to the dynamic characteristics of mobile environments, a mobile application needs to adapt to changing contexts to improve performance and resource utilization. We have developed an adaptive middleware infrastructure that simultaneously satisfies the individual needs of applications while maintaining...

Lung cancer is known as the highest mortality rate cancer, which needs biopsy to determine its subtype for further treatment. Recently, deep learning has provided powerful tools in lung cancer diagnose and therapeutic regimen making. However, it is still a challenge to identify the pathological type...

Multibiomitric systems are expected to be more accurate due to the presence of multiple evidences, score level fusion is the most commonly used approach in multibiometrics. In this paper, A novel approach is proposed for the fusion at score level fusion based on False Reject Rate(FRR) and False Accept...

The Lee–Carter model is a useful dynamic stochastic model to represent the evolution of central mortality rates throughout time. This model only considers the uncertainty about the coefficient related to the mortality trend over time but not to the age-dependent coefficients. This paper proposes a fuzzy-random...

Recommender systems are currently successful solutions for facilitating access for online users to the information that fits their preferences and needs in overloaded search spaces. In the last years several methodologies have been developed to improve their performance. This paper is focused on developing...

Considering trust issues in cloud computing, we analyze the feasibility of adopting ant colony optimization algorithm to simulate trust relationships between entities in the cloud and then propose a novel behavior trust model: ACO-BTM. Trust relationships between entities in cloud computing are dynamic,...

The last decade has witnessed a great interest on the application of evolutionary algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO) and gene expression programming (GEP), for optimization problems. This paper presents a hybrid algorithm by combining the GEP algorithm and the...

In this paper, a newly emerging duopoly market with a short life cycle is analyzed. The partially known information of market is characterized by the possibility distribution of the parameter in the demand function. Since the life cycle of the new product is short, how many products should be produced...

The finite-range voter system, one of stochastic particle systems, is applied to model a financial price process for further description and investigation of fluctuations of Shanghai Composite Index. For different parameter values of the intensity and the range , we investigate the statistical behaviors...

Inspired by the process of immunoglobulin secretion in biological body, we present a Web Page Malicious Script Detection Method (WPMSD). In this paper, Firstly, the basic definitions of artificial immune items are given. Secondly, according to the spreading range of malicious script, the immunoglobulin...

In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi's Bacterial Evolutionary Algorithm and various discrete local search techniques. These algorithms have proven to be efficient...

In this paper, we describe an approach to database preference queries based on the notion of outranking, suited to the situation where preferences on different attributes are not commensurable. This model constitutes an alternative to the use of Pareto order whose main drawback is to leave many tuples...

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...

We aim at maximizing the comfort of operators in mixed-model assembly lines. To achieve this goal, we evaluate two assembly line balancing models: the first that minimizes the maximum ergonomic risk and the second one that minimizes the average absolute deviations of ergonomic risk. Through a case study...

Software projects estimations are a crucial component of successful software development. There have been many approaches that deal with this problem by using different kinds of techniques. Most of the successful techniques rely on one shot prediction of some variables, as cost, quality or risk, taking...

As a planning strategy, “connectivity” has been used to promote the functions of Urban Waterfront space to revitalize the city. By analyzing the hierarchy of functions of Urban Waterfront, namely ecological function, social function and context function, an index system of assessing its functions...

Image intensity in magnetic resonance (MR) images in the presence of noise obeys Rician distribution. The signal-dependent Rician noise makes accurate image segmentation a challenging task. Although existing fuzzy c-means (FCM) variants with local filters improve the segmentation performance, they are...

This paper presents a novel quantitative credit scoring model based on support vector machine (SVM) with adaptive genetic algorithm, gr-GA-SVM. In this study, two real world credit datasets in the University of California Irvine Machine Learning Repository are selected for the numerical experiments....

A secret sharing model can secure a secret over multiple noise-like shadows and remain recoverable despite multiple shadow failures. Even if some of the shadows are compromised, the secret will not be revealed as long as the number of the compromised shadows is smaller than a pre-determined threshold....

It is crucial to evaluate the information obtained from the sensors in a fast and accurate manner in air vehicles exposed to many internal and external influences during their flights. The effectiveness and flexibility of the reasoning method comes to the forefront when the pilot or flight control system...

In this paper, by considering the notion of MV-modules, which is the structure that naturally correspond to lu-modules over lu-rings, we investigate some properties of a new kind of MV-modules, that we introduced in Borzooei and Saidi Goraghani, Free MV-modules, J. Intell. Fuzzy Syst. 31 (2016), 151–161...

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...

Differential evolution (DE) represents a class of population-based optimization techniques that uses differences of vectors to search for optimal solutions in the search space. However, promising solutions/regions are not adequately exploited by a traditional DE algorithm. Memetic computing has been...

Customer relationship management (CRM) has gained lately widespread popularity in many industries. With the development of economy and society, customers are unsatisfied with the stereotyped products. As customers usually describe their demands in nature language, the demands are often conflicting with...

Several adaptation approaches have been devised to ensure end-to-end quality-of-service (QoS) for enterprise distributed systems in dynamic operating environments. Not all approaches are applicable, however, for the stringent accuracy, timeliness, and development complexity requirements of distributed...

An immune-inspired adaptive automated intrusion response system model, named as , is proposed. The descriptions of self, non-self, immunocyte, memory detector, mature detector and immature detector of the network transactions, and the realtime network danger evaluation equations are given. Then, the...

Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. In this paper, we discussed some properties of the –complement of bipolar fuzzy...

Optimized task scheduling is one of the most important challenges in parallel and distributed systems. In such architectures during compile step, each program is decomposed into the smaller segments so-called tasks. Tasks of a program may be dependent; some tasks may need data generated by the others...

Inspiring by nature have motivated many researchers in many fields of sciences and engineering. The Gravitational search algorithm (GSA) is a recent created metaheuristic algorithm by using law of gravity and mass interactions. In this paper, a new operator inspired by some of the characteristics of...

High traffic flow is a typical characteristic of a mobilized city with a high population. Efficient traffic management is a proper solution to reduce the stress and anxiety associated with driving or traveling. The road users can have better timing for traveling as they will not experience journey delays...

Engagement-level simulation is a quantitative way to evaluate the effectiveness of weapon systems before construction and acquisition, minimizing the risk of investment. Though contractors have built simulation systems with high fidelity models of weapon systems and battlefields, developing competent...

New environmental regulations have driven companies to adopt low-carbon manufacturing. This research is aimed at considering carbon dioxide in the operational decision level where limited studies can be found, especially in the scheduling area. In particular, the purpose of this research is to simultaneously...

In a continuously changing environment, like globalization, technological innovation, restructuring and outsourcing, organizations can no longer cope without continually developing their competencies and human resources. As a result academic research and company practices have actively started to develop...

The location-aided routing algorithm adopts the flooding mechanism to transmit route control packet in mobile Ad Hoc networks. Such mechanism not only affects nodes which do not join the final route, but also needs a large number of unnecessary deliveries of control packets. To address this issue, we...

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...

This paper presents a congruence measurement method by partitions to apply software trustworthiness measures in dynamic behavior feature datasets. The datasets are generated at software running time. And the method compares the datasets with the static attribute feature datasets generated at software...

An incomplete interval-valued information system (IIVIS) is an information system (IS) in which the information values are interval numbers with missing values. This article researches information structures in an IIVIS. First, information structures in an IIVIS are obtained. In addition, the dependence...

Many hard optimization problems have been efficiently solved by two notable swarm intelligence algorithms, artificial bee colony (ABC) and firefly algorithm (FA). In this paper, a collaborative hybrid algorithm based on firefly and multi-strategy artificial bee colony, abbreviated as FA-MABC, is proposed...

Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, the notion of soft relation is introduced which is a generalization of the notion of soft set relation, and some related properties are examined. Furthermore, the connections...

Knowledge management (KM) systems can provide businesses a wide range of advantages and efficiency improvements. Increasing competition forces companies to seek new ways to streamline their processes and manage their information and knowledge better, leading to increased demand for KM solutions. Considering...