International Journal of Computational Intelligence Systems

Credit risk prediction is an effective way of evaluating whether a potential borrower will repay a loan, particularly in peer-to-peer lending where class imbalance problems are prevalent. However, few credit risk prediction models for social lending consider imbalanced data and, further, the best resampling...

Rainfall prediction has emerged as a challenging time-series prediction problem in recent years. In this paper, we propose a novel rainfall prediction technique using effective feature indicators and a hybrid technique. Our proposed model consists of three phases, namely, layer model simulation, training...

Real world problems for prediction usually try to predict rare occurrences. Application of standard classification algorithm is biased toward against these rare events, due to this data imbalance. Typical approaches to solve this data imbalance involve oversampling these “rare events” or under sampling...

For decades, image enhancement has been considered one of the most important aspects in computer science because of its influence on a number of fields including but not limited to medical, security, banking and financial sectors. In this paper, a new gray level image (edge preserving) enhancement method...

Access control is an important element in network security. Meanwhile, trust provides a new direction for access control in open network environments. Based on the dynamic nature of trust, we study the temporal and spatial characteristics in the security of society and propose the concept of scenario...

One of key issues for -() ary resolution automated reasoning based on lattice-valued logic with truth-value in a lattice implication algebra is to investigate the -() ary resolution of some generalized literals. In this article, the determination of -resolution of any 3-ary generalized literals which...

Today, computer networks are complex and illegal wiretapping is possible. This poses a real problem for the security during transmission of data. For ethical reasons, the transfer of sensitive data cannot be done with such a danger and must protect themselves. Protection best suited for this type of...

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...

In this paper, a novel fusion method based on Total Error Rate (TER) and multiple hidden layer probabilistic extreme learning machine is proposed. At first, the study transfers the matching scores into TER based on corresponding False Reject Rates (FRR) and False Accept Rates (FAR) aims at avoiding to...

The paper proposes a method using convolutional neural network to effectively evaluate the discrimination between face and non face patterns, gender classification using facial images and facial expression recognition. The novelty of the method lies in the utilization of the initial trainable convolution...

We present a model made up of linguistic multi-criteria decision making processes to integrate the answers to heterogeneous questionnaires, based on a five-point Likert scale, into a unique form rooted in the widespread course experience questionnaire. The main advantage of having the resulting integrated...

The purpose of a brain–computer interface (BCI) is the recording of brain signals to translate them into commands. This work proposes new naturalistic and intuitive motor imagery (MI) BCI task for aircraft Pilots for a BCI System, and explore if they take advantage of their previous motor experience...

Image segmentation plays crucial role in medical image analysis and forms the basis for clinical diagnosis and patient's treatment planning. But the large variation in organ shapes, inhomogeneous intensities, poor contrast, organic nature of textures and complex boundaries in medical images makes...

As a relatively new collaborative service mode, Mobile Instant Messaging (MIM) is gaining ever greater popularity. MIM users interact within a complex system to influence others' adoption decisions, thus resulting in behavioral evolution. An agent-based computational approach is a methodology well suited...

The content authenticity of the multimedia delivery is important issue with rapid development and widely used of multimedia technology. Till now many authentication solutions had been proposed, such as cryptology and watermarking based methods. However, in latest heterogeneous network the video stream...

Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Fuzzy autoregressive integrated moving average (FARIMA) models are the fuzzy improved version of the autoregressive integrated moving average (ARIMA) models, proposed in order...

In this paper, we investigate a class of stochastic shunting inhibitory cellular neural networks with time-varying delays. Applying integral inequality, some sufficient conditions on the existence and p-exponential stability of periodic solutions for stochastic shunting inhibitory cellular neural networks...

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...

Effective channel order determination is an important problem in convolutive blind channel identification. The classical techniques are based on information theoretic criteria, which show a great potentiality to estimate the effective channel order. However, these methods are just effective for the overdetermined...

This paper proposes a novel approach to decision making based on grey relational analysis and MYCIN certainty factor, which describes decision making problems with fuzzy soft sets. Firstly, we utilize grey relational analysis to obtain the grey mean relational degree, and the uncertain degree of various...

Computer-aided detection(CAD) system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM) classifiers is proposed for detecting both...

Clustering is carried out to explore and solve power dissipation problem in wireless sensor network (WSN). Hierarchical network architecture, based on clustering, can reduce energy consumption, balance traffic load, improve scalability, and prolong network lifetime. However, clustering faces two main...

Recent deep convolutional neural network-based object detectors have shown promising performance when detecting large objects, but they are still limited in detecting small or partially occluded ones—in part because such objects convey limited information due to the small areas they occupy in images....

In the learning process of the conventional SOM, the neuron which is closer to the winner neuron learns more than the neuron which is farther away from the winner neuron. The neurons farther away from input are not able to learn properly and some dead units are left on the map. To decrease dead unit...

Uninorms play a prominent role both in the theory and the applications of aggregations and fuzzy logic. In this paper a class of uninorms, called group-like uninorms will be introduced and a complete structural description will be given for a large subclass of them. First, the four versions of a general...

Multiple objects tracking is a challenging task. This article presents an algorithm which can detect and track multiple objects, and update target model automatically. The contributions of this paper as follow: Firstly,we also use color histogram(CH) and histogram of orientated gradients(HOG) to represent...

Ever since the introduction of Pythagorean fuzzy (PF) sets, many scholars have focused on solving multicriteria decision-making (MCDM) problems with PF information. The technique for order preference by similarity to ideal solutions (TOPSIS) is a well-known and effective method for MCDM problems. The...

To be cost-effective, most commercial off-the-shelf industrial controllers have low system order and a predefined internal structure. When operating in an industrial environment, the system output is often specified by a reference model, and the control system must closely match the model’s response....

A novel froth image analysis based production condition recognition method is presented to identify the froth phases under various production conditions. Gabor wavelet transformation is employed to froth image processing firstly due to the ability of Gabor functions in simulating the response of the...

This paper presents a new approach to crime hotspot detection and monitoring. The approach consists of three phases’ namely: video analysis, crime prediction and crime mapping. In video analysis, crime indicator events are modelled using statistical distribution of semantic concepts. In crime prediction,...

In this study, a novel sparsity-driven weighted ensemble classifier (SDWEC) that improves classification accuracy and minimizes the number of classifiers is proposed. Using pre-trained classifiers, an ensemble in which base classifiers votes according to assigned weights is formed. These assigned weights...

Network reconfiguration of a power distribution system is an operation to alter the topological structure of distribution feeders by changing open/closed status of sectionalizing and tie switches. Network reconfiguration balances feeder loads and helps in managing overload conditions of the network by...

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...

Information fusion has been a hot topic currently, how to make information fusion for intelligent decision is a challenge. Although the applications of random set theory attract many researchers, the probability function distribution is still imprecise. In this paper, we give a new definition of probability...

In a context of lattice-valued functions (also called lattice-valued fuzzy sets), where the codomain is a complete lattice L, an equivalence relation defined on L by the equality of related cuts is investigated. It is known that this relation is a complete congruence on the join-semilattice reduct of...

The aim of this paper is to present a novel approach for deriving weights of the decision criteria or alternatives in multi-attribute decision making (MADM) under intuitionistic fuzzy (IF) environment. In order to tackle the uncertainty and imprecision of the practical situations, decision makers’...

As a primary means for representing and reasoning about knowledge, Answer Set Programming (ASP) has been applying in many areas such as planning, decision making, fault diagnosing and increasingly prevalent e-service. Based on the stable model semantics of logic programming, ASP can be used to solve...

This study presents the normative knowledge source for the belief space of cultural algorithm(CA) based on an adaptive Radial Basis Function Neural Network (RBFNN). The use of the RBFNN makes it possible to use the previous upper and lower bounds of the normative knowledge to update them and to extract...

The hesitant fuzzy linguistic term set (HFLTS) and the linguistic distribution (LD) are becoming popular tools to describe decision makers’ linguistic preferences. By combining HFLTS and LD, this paper proposes a new concept called hesitant linguistic distribution (HLD), and then presents the transformation...

We describe an applied methodology to build fuzzy models of geographical expressions, which are meant to be used for natural language generation purposes. Our approach encompasses a language grounding task within the development of an actual data-to-text system for the generation of textual descriptions...

Recently, there have been many studies on solving different kinds of fuzzy equations. In this paper, the solution of a trapezoidal fully fuzzy linear system (FFLS) is studied. Uzawa approach, which is a popular iterative technique for saddle point problems, is considered for solving such FFLSs. In our...

Artificial Intelligence (AI) is part of our everyday life and has become one of the most outstanding and strategic technologies. Explainable AI (XAI) is expected to endow intelligent systems with fairness, accountability, transparency and explanation ability when interacting with humans. This paper describes...

This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP) with high efficiency. We first analyze agent and agent-based simulation framework,...

In this paper, we propose a new entropy measure with geometrical interpretation of intuitionistic fuzzy sets. Compared with the entropy measure provided by Szmidt and Kacprzyk, the new entropy formula in this paper can measure both fuzziness and intuitionism for intuitionistic fuzzy sets. According to...

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...

This paper aims at developing a voltage-based impedance model-reference controller using fuzzy uncertainty estimator for the robust control of electrically driven robot manipulators. The proposed control scheme not only utilizes a desired impedance as a reference model, but also provides the integrated...

Minor component analysis (MCA) are used in many applications such as curve and surface fitting, robust beam forming, and blind signal separation. Based on the generalized eigen-decomposition, we present a completely different approach that leads to derive a novel MCA algorithm. First, in the sense of...

Time series forecasting has been an important tool in many areas such as agriculture, finance, management, production or sales. In recent years, a large literature has evolved on the use of artificial neural networks (ANN) in time series forecasting. However conventional ANN is limited by its instantaneous...

In this work, using the identification between implication operators and aggregation functions, we study the implication operators that are recovered from overlap functions. In particular, we focus in which properties of implication operators are preserved. We also study how negations can be defined...

Remanufacturing has been attracting attentions of global manufacturers as an important sustainable development strategy. Component oriented remanufacturing decision-making for complex product involving two phases is proposed in this paper. The first phase is to decide which components to be remanufactured...

Tremendous effort has been exerted over the past few decades to construct multi-attribute decision functions with the capacity to model heterogeneous interrelationships among attributes. In this paper, we report an empirical study aiming to test whether or not considering interrelationships among attributes...

This paper considers the greening policies in a decentralized channel between one manufacturer and one retailer in a fuzzy decision making environment. We consider the manufacturing cost and the parameters of demand function as the fuzzy variables. Based on the different market structures, we develop...

We introduce the concept of a fuzzy total preorder. Then we analyze its numerical representability through a real-valued order-preserving function defined for each -cut.

This paper is a contribution to the study of two distinct kinds of logics for modelling uncertainty. Both approaches use logics with a two-layered modal syntax, but while one employs classical logic on both levels and infinitely-many multimodal operators, the other involves a suitable system of fuzzy...

A new methodology for processing non-normal fuzzy sets is proposed. To break the predominant constraint on normality of fuzzy numbers the concept of fuzzy semi-numbers is introduced Then it is shown how to generalize operations defined on fuzzy numbers onto a family of fuzzy semi-numbers with possibly...

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...

The notion of –ideal is introduced in lattice implication algebras. Firstly, the equivalent conditions of –ideals and –ideals are given in lattice implication algebras. Then the proposition of –ideal is investigated in lattice implication algebras. Next, the relations between...

Strategic decisions such as mergers, acquisitions and joint ventures have a strong effect on firm performance. In order to be successful in highly competitive environments firms have to make right and on time strategic decisions. However, the nature of making the right strategic decision is complex and...

In this paper, we propose a feature-weighted mountain clustering method. The proposed method can work well when there are noisy feature variables and could be useful for obtaining initial estimat of cluster centers for other clustering algorithms. Results from color image segmentation illustrate the...

A low complexity Polynomial Functional link Artificial Recurrent Neural Network (PFLARNN) has been proposed for the prediction of financial time series data. Although different types of polynomial functions have been used for low complexity neural network architectures earlier for stock market prediction,...

To obtain reliable results in a qualitative multi-attribute group decision-making (MAGDM) problem, how to retain the evaluation information as much as possible and how to determine the reasonable weights of experts and attributes are two important issues. Proportional hesitant fuzzy linguistic term set...

Since the multigranulation rough sets (MGRS) can be considered as the compositions of multi–independent Pawlak's rough sets, the multigranulation rough set rules (MGRS rules) are then the compositions of decision rules, which are supported by multi–independent Pawlak's rough sets. To measure...

In practice, suppliers often provide retailers with forward financing to increase demand or decrease inventory. This paper proposes a new and practical joint replenishment and delivery (JRD) model by considering trade credit. However, because of the complex mathematical properties of JRD, high-quality...

Although the individuals' transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations...

To effectively score pages with uncertainty in web social networks, we first proposed a new concept called transition probability matrix and formally defined the uncertainty in web social networks. Second, we proposed a hybrid page scoring algorithm, called WebScore, based on the PageRank algorithm and...

Failure mode and effect analysis (FMEA) is a risk management technique frequently applied to enhance the system performance and safety. In recent years, many researchers have shown an intense interest in improving FMEA due to inherent weaknesses associated with the classical risk priority number (RPN)...

Coreference resolution is one of the most critical issues in various applications of natural language processing, such as machine translation, sentiment analysis, summarization, etc. In the process of coreference resolution, in this paper, a fully connected neural network approach has been adopted to...

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...

Generalized fuzzy graphs are perfect to represent any system like networks, images, scheduling, etc. compared to fuzzy graphs. This study introduces the concept of a generalized fuzzy neighbourhood of a vertex and generalized fuzzy graphs. Also, an associated graph, called minimal graphs of competition...

Enterprises nowadays are often confronted with selecting supplier collaborative configuration problems in supply chain management. The aim of this paper is to develop a group selection methodology with the correlation of experts and attributes for solving supplier collaborative configuration problems....

Due to the seriousness of the network security situation, as a low-cost, high-efficiency email attack method, it is increasingly favored by attackers. Most of these attack vectors were embedded in email attachments and exploit vulnerabilities in Adobe and Office software. Among these attack samples,...

The existing stability analysis of particle swarm optimization (PSO) algorithm is chiefly concluded by the assumption of constant transfer matrix or time-varying random transfer matrix. Firstly, one counterexample is provided to show that the existing convergence analysis is not possibly valid for PSO...

In the research presented in the paper, we test the classification potential for different configurations of the MMPI data used for nosological diagnosis of patients with mental disorders. Originally, each patient is described by an MMPI profile consisting of a set of values of thirteen attributes (the...

The aim of this paper is to provide an algorithm for the computation of support and confidence of the association rules on interval-valued fuzzy sets. Each element of the interval-valued fuzzy set has a membership degree defined as an interval. In other words, the membership intervals may be interpreted...

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...

In this paper, we introduce a fast implementation of the CT EXT algorithm for testor property identification, that is based on an accumulative binary tuple. The fast implementation of the CT EXT algorithm (one of the fastest algorithms reported), is designed to generate all the typical testors from a...

Currently, recommender systems (RS) are incorporating implicit information from social circle of the Internet. The implicit social information in human mind is not easy to reflect in appropriate decision making techniques. This paper consists of 2 contributions. First, we develop an item-based prototype...

Over the years, there has been an evolution in the manner in which we perform traditional tasks. Nowadays, almost every simple action that we can think about involves the connection among two or more devices. It is desirable to have a high quality connection among devices, by using electronic or optical...

In the field of financial investment, investing in stocks is relatively easy compared to other investment commodities, since making a profit through buying a stock at a low price and selling it at a higher price is intuitive. However, it is really challenging work for an investor to choose stocks which...

This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the...

Identification and characterization of gene regulatory binding motifs is one of the fundamental tasks toward systematically understanding the molecular mechanisms of transcriptional regulation. Recently, the problem has been abstracted as the challenge planted (l,d)-motif problem. Previous studies have...

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....

This paper presents a novel framework that automatically classifies hand grasps using Electromyogram (EMG) signals based on advanced Wavelet Transform (WT). This method is motivated by the observation that there lies a unique correlation between different samples of the signal at various frequency levels...

In this paper, we consider the revenue sharing contract between supply chain actors in a multi-echelon supply chain, where the demand of the customers and retail price are fuzzy variables. The centralized decision making system and a coordinating contract, namely, the revenue sharing contract with fuzzy...

In recent years, hesitant multiplicative preference relation (HMPR) has been a powerful means to represent the evaluation information of decision makers during the pairwise comparison concerning alternatives. As the important parts of group decision making (GDM) issues with HMPRs, the consistency improving...

Automatic services collaboration calls for the development of semantically structured service network to maximize the utility of Web services. Service Semantic Link Network (S-SLN) is the semantic model for effectively managing Web service resources by the dependency relationship between services. We...

In this paper, we have studied the constrained version of the fuzzy minimum spanning tree problem. Costs of all the edges are considered as fuzzy numbers. Using the measure, a generalization of credibility measure, the problem is formulated as chance-constrained programming problem and dependent-chance...

This paper comprises a new iterative method for multi-person decision making based on multiplicative consistency with incomplete reciprocal preference relations (IRPRs). Additionally, multiplicative transitivity property of reciprocal preference relation (RPR) is used at the first level to estimate the...

A novel fuzzy rough granular neural network (NFRGNN) based on the multilayer perceptron using backpropagation algorithm is described for fuzzy classification of patterns. We provide a development strategy of knowledge extraction from data using fuzzy rough set theoretic techniques. Extracted knowledge...

One of the key issues in the theory of concept lattices is to extract the useful rules from the decision formal context. The maximal rules implicate the others, thus people are interested in them. This paper proposes two new kinds of attribute reduction in the decision formal context based on maximal...

Genetic algorithm (GA) is a search algorithm based on the theory of Darwin. For the purpose of improving the convergent rate and maintaining the population diversity in GA, this paper presents a new genetic operator called trisecting group and directional selection mechanism (TDGA), in which the worst...

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...

Digital filters are generally designed by identifying the transfer functions. Most researches are focused on the goal of approaching the desired frequency response, and take less additional consideration of structure characteristics which can greatly affect the performance of the digital filter. This...

Fuzzy tensors encode to what extent n-ary predicates are satisfied. The disjunctive box cluster model is a regression model where sub-tensors are explanatory variables for the values in the fuzzy tensor. In this article, locally optimal patterns for that model, with high areas times squared densities,...

Proximal support vector machine via generalized eigenvalue (GEPSVM) is a recently proposed binary classification technique which aims to seek two nonparallel planes so that each one is closest to one of the two datasets while furthest away from the other. In this paper, we proposed a novel method called...

Cloud computing is defined as an on-demand large-scale distributed network to provide and realize computational resources. This flexibility expectation of cloud products forces cloud service providers (CSPs) to tailor their products to the needs of their customers. The framework in this paper proposes...

Semantic annotation of named entities for enriching unstructured content is a critical step in development of Semantic Web and many Natural Language Processing applications. To this end, this paper addresses the named entity disambiguation problem that aims at detecting entity mentions in a text and...

In recent years a lot of attention and efforts have been dedicated on optimizing the design and quality of coffee pods. These would be applicable on professional as well as on household machines such as Senseo or Nestle. By providing a new method to describe the mechanisms of the brewing process within...

The quality of reconstructed images is an important and direct criterion to quantitatively evaluate the effectiveness of reconstruction algorithms in electrical tomography (ET). Unfortunately, there lacks of effective and efficient approach to assessing the quality of ET images in literature and practices....

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...