International Journal of Computational Intelligence Systems

In this paper, a multi-objective particle swarm optimization algorithm with a new global best () selection strategy is proposed for dealing with multi-objective problems. In multi-objective particle swarm optimization, plays an important role in convergence and diversity of solutions. A -means algorithm...

Cross-border E-commerce has grown exponentially in the past decade in global market. To gain global competition in product-convergent markets, China’s over 200 thousands cross-border E-commerce businesses have focused more on the service and cost control of supply chain downstream. In this study, we...

Designing secure and robust grouping-proof protocols based on RFID characteristics becomes a hotspot in the research of security in Internet of Things (IOT). The proposed grouping-proof protocols recently have security and/or privacy omission and these schemes afford order-dependence by relaying message...

This paper presents a novel approach to automatic design of a robust optimal controller for interval plants with Genetic Programming based on Kharitonov Theorem (KT), which provides a theoretical foundation in the design of robust controller for interval plants. The structure and parameters of the robust...

This paper introduces a new self-tuning mechanism to the local search heuristic for solving of combinatorial optimization problems. Parameter tuning of heuristics makes them difficult to apply, as parameter tuning itself is an optimization problem. For this purpose, a modified local search algorithm...

By means of infinite product of uniformly distributed probability spaces of cardinal , the concept of -validity degrees and validity degree vectors of formulae in two-valued predicate logic are introduced. It is proved that the validity degree vectors of formulae can preserve the logical relation between...

Accurate demand forecast can help improve teleconsultation efficiency. But teleconsultation demand forecast has not been reported in existing literature. For this purpose, the study proposes a novel model based on deep learning algorithm for daily teleconsultation demand forecast to fill in the research...

MicroRNA regulatory module (MRM) plays an important role in the study of microRNA synergism. To detect MRMs, researchers have developed a number of related methods in the preceding decades. However, some existing methods are stochastic or specific to a certain situation. In this paper, we presented a...

Complex q-rung orthopair fuzzy set (CQROFS), as a modified notion of complex fuzzy set (CFS), is an important tool to cope with awkward and complicated information. CQROFS contains two functions which are called truth grade and falsity grade by the form of complex numbers belonging to unit disc in a...

This paper presents an improved particle swarm optimizer (PSO) for solving multimodal optimization problems with problem-specific constraints and mixed variables. The standard PSO is extended by employing a comprehensive learning strategy, different particle updating approaches, and a feasibility-based...

Clause learning is the key component of modern SAT solvers, while conflict analysis based on the implication graph is the mainstream technology to generate the learnt clauses. Whenever a clause in the clause database is falsified by the current variable assignments, the SAT solver will try to analyze...

Chaotic synchronization, as a key technique of chaotic secure communication, has received much attention in recent years. This paper proposes a nonlinear synchronization scheme for the time-delay chaotic system in the presence of noise. In this scheme, an integrator is introduced to suppress the influence...

In an islanded microgrid, while considering the complex nature of line impedance, the generalized droop control fails to share the actual real/reactive power between the distributed generation (DG) units. To overcome this power sharing issue, in this paper a new approach based on feed forward neural...

In this paper, the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed delays and general activation functions is considered. By virtue of Lyapunov functional and Halanay delay differential inequality, several new criteria in linear matrix inequalities (LMIs) form...

Cellular manufacturing (CM) has been identified as an innovative practice for manufacturer to achieve efficiency as well as flexibility under an uncertain environment. This study addresses a new mathematical robust model for a cellular manufacturing problem integrated with tactical aspects under supply...

Computer vision-based tracking and fault detection methods are increasingly growing method for use on railway systems. These methods make detection of components of the railways and fault detection and condition monitoring process can be performed using data obtained by means of computers. In this study,...

A Peer-to-Peer (P2P) system relies on the cooperation of the peers and the contributions of their resources. To motivate autonomous peers share their resources, the system needs to support effective resource allocation strategies with respect to peers’ task priorities, and their personal information...

In this paper we discuss and analyze some of the intelligent classifiers which allows for automatic detection and classification of networks attacks for any intrusion detection system. We will proceed initially with their analysis using the WEKA software to work with the classifiers on a well-known IDS...

Fuzzy multisets represent a particularly challenging generalization of the concept of fuzzy sets. The membership degrees of fuzzy multisets are given by multisets in 0,1 rather than single values. Mathematically, they can be also seen as a generalization of the hesitant fuzzy sets. But in this general...

Medical studies have confirmed the causal relationship between autism and brain areas. Such relationship can effectively promote the early diagnosis and timely intervention of autism. However, existing experiment-driven methods discovering such relationships are costly while machine-learning-based methods...

Multi-step-ahead prediction of tunnel surrounding rock displacement is an effective way to ensure the safe and economical construction of tunnels. This paper presents a multi-step-ahead prediction model, which is based on support vector machine (SVM), for tunnel surrounding rock displacement prediction....

This paper develops an Internet-based fuzzy control system for an industrial process plant to ensure the remote and fuzzy control in cement factories in Algeria. The remote process consists of control, diagnosing alarms occurs, maintaining and synchronizing different regulation loops. Fuzzy control of...

As one of research and practice hotspots in the field of intelligent manufacturing, the machine learning approach is applied to diagnose and predict equipment fault for running state data. Despite deep learning approach overcomes the problem that the traditional machine learning approaches for fault...

This paper analyzes the study of a Multi-Objective Transportation Problem (MOTP) under uncertain environment. Assuming the uncertainty in real-life decision making problems, the concept of reliability is incorporated in the transportation cost and the effectiveness is justified through the proposed MOTP....

In this paper, a Gravitational Co-evolution and Opposition-based Optimization (GCOO) algorithm is proposed for solving unconstrained optimization problems. Firstly, under the framework of gravitation based co-evolution, individuals of the population are divided into two subpopulations according to their...

Electric power industry has been undergoing enormous transformations. Therefore, it is necessary to improve the security of electric power system and the decision capacity in the emergency process. As a complicated system, electric power system is affected by many factors, the reasoning of which can...

A congestion control scheme based on credibility is proposed. In this scheme, the whole network is divided into several independent domains, and each domain contains a congestion control server (CCS) and several control modules (CM). The CCS is used to collect credit information and make punishment decisions...

Predicting stock composite index is useful, which can raise the interest of both the investors and the corresponding researchers. This paper presented a new combination prediction model based on the technique of artificial intelligence and the principle of combination forecast. The principle of combination...

This paper deals with the permutation flow shop scheduling problem. The objective is to minimize the maximum completion time, or makespan. To solve this problem which has been proved to be strongly NP-hard, a combination between an ant colony algorithm, a heuristic algorithm and a local search procedure...

Most sectors of the economy like the universities, high-tech, financial services, and government institutions have data center. However, there are some issues which encompass current data center such as physical location, energy consumption, performance, flexibility. Big organizations like Google, IBM...

This paper presents a H-infinite state estimator for Takagi-Sugeno fuzzy delayed Hopfield neural networks. Based on Lyapunov-Krasovskii stability approach, a delay-dependent criterion is proposed to ensure that the resulting estimation error system is asymptotically stable with a guaranteed H performance....

Understanding online shopping behaviors is crucial for the survival of many firms. Modeling the customers' online shopping behaviors is a complex problem that involves uncertainty, hesitancy, and imprecision since different generations have different attitudes toward e-commerce. In this study, a...

One of the important factors in increasing the productivity of the incubation industry is to be sure that the eggs placed in the incubators are fertile. In this research, a fertility detection machine vision system is developed and evaluated. To this end, a mechatronic machine is fabricated for acquiring...

Decision making implies selection of the best decision from a set of possible options. In some cases, this selection is based on past experience. Past experience is used to analyse the situations and the choice made in these situations. The aim of this work is to analyse the strength of the nonlinear...

This paper introduces the notion of safety and availability checking for user authorization query processing, and develop a recursive algorithm use the ideas from backtracking-based search techniques to search for the optimal solution. For the availability checking, we introduce the notion of max activatable...

This paper presents the design and implementation of a smart and safe minimarket prototype for deployment in busy smart cities to mitigate the overhead of shopping experience. The prototype allows customers to remotely access and browse the available products at the minimarket using a special smart-phone...

This paper proposes a new scheme for preventing a Particle Swarm Optimizer from premature convergence on multimodal optimization problems. Instead of only using fitness evaluation, we use a new index called particle age to guide population towards more promising region of the search space. The particle...

Recently, many feature extraction methods, which are based on the matrix representation of image and matrix bidirectional projection technique, are proposed. However, these methods in solving the two projection matrices will suffer from non-optimized or non-convergent solution. To overcome this problem,...

With advanced technology in medicine and biology, data sets containing information could be huge and complex that sometimes are difficult to handle. Dynamic computing is an efficient approach to solve some problems. Since multigranulation rough sets were proposed, many algorithms have been designed for...

The paper proposes a novel blind audio watermarking scheme based on singular value decomposition (SVD) and neural networks (NN), which makes use of memorization and adaptation capabilities of NN. Experimental results show that the proposed watermarking algorithm is strongly robust against several kinds...

Diabetes is a chronic disease that requires patient-centered treatment. The physician strategy for treatment of diabetes varies from one patient to another. Using the clinical parameters and the evidence of diabetes at various group of people are to be treated with the drugs that provide significant...

As a basic prerequisite for worm detection based on computational intelligence in networks with locator/identifier separation, it is well worth considering the influence on worm propagation due to the incoming locator/identifier separation. In this paper, according to the characteristics of locator/identifier...

Considering the rapid growth, complications and treatment side-effects of MI, so using data mining techniques seems necessary. On the other hand, in real-world MI cases are much less compared to healthy cases. The traditional algorithms for imbalanced problems lead to very low Sensitivity, thus, we propose...

Conventional Network intrusion detection system (NIDS) mostly uses individual classification techniques, such system fails to provide the best possible attack detection rate. In this paper, we propose a new two-stage hybrid classification method using Support Vector Machine (SVM) as anomaly detection...

Modern multicore architectures have an ability to allocate optimum system resources for a specific application to have improved energy and throughput balance. The system resources can be optimized automatically by using optimization algorithms. State-of-the-art using optimization algorithm in the field...

Digital watermarking is an effective way for authentication of stereo images when they are transmitted over networks. Since the left and right images of a stereo image pair are not independent but similar to each other, their watermarking design should be different from that of mono-images. This paper...

Finding the optimal weights for a set of financial assets is a difficult task. The mix of real world constrains and the uncertainty derived from the fact that process is based on estimates for parameters that likely to be inaccurate, often result in poor results. This paper suggests that a combination...

This paper presents an automated image registration approach to detecting changes in multi-temporal remote sensing images. The proposed algorithm is based on the scale invariant feature transform (SIFT) and has two phases. The first phase focuses on SIFT feature extraction and on estimation of image...

In this research, we study a cost minimization problem for a firm that acquires capacity from providers to accomplish daily operations on telecommunication networks. We model the related optimization problem considering quality of service and capacity requirements and offer a solution approach based...

This paper proposes an advanced fuzzy load forecast method optimized by modified Jaya optimization (MJO) algorithm. MATLAB® platform is used to implement the proposed hybrid Fuzzy-MJO load forecasting algorithm and to verify the outperforming features of a Jaya technique over a fuzzy load forecast model....

In this paper, we give a new notion of the m-polar single-valued neutrosophic sets (m-PSVNSs) which is a hybrid of the single-valued neutrosophic sets (SVNSs) and the m-polar fuzzy sets (m-PFSs) and study several of the structure operations including subset, equal, union, intersection, and complement....

Wormhole attacks, as a devastating type of threats in wireless mesh networks, have received much attention in recent years. This paper proposes a type of wormhole attack model and its corresponding detection scheme. In this scheme, the combination of a number of techniques, such as distributed voting,...

With the rapid development of network technology, especially in the internet area, distributed computation and parallel processing of data are urgently needed. This paper studies the combination operation of the lattice-valued concept lattices to realize its distributed computation and parallel processing....

Compressed sensing theory is widely used in image and video signal processing because of its low coding complexity, resource saving, and strong anti-interference ability. Although the compression sensing theory solves the problems brought by the traditional signal processing methods to a certain extent,...

Logarithm Least-Squares Support Vector Regression (LLS-SVR) has been applied in addressing forecasting problems in various fields, including bioinformatics, financial time series, electronics, plastic injection moulding, Chemistry and cost estimations. Cautious Random Particle Swarm Optimization (CRPSO)...

Multiple attributes group decision making problems aim to find the best alternative for the experts from a solution set of alternatives. Because the attribute value and decision-makers evaluation with respect to the alternatives are usually vague and imprecise, fuzzy multiple attributes group decision...

As the ontology alignment facilitates the knowledge exchange among the heterogeneous data sources, several methods have been introduced in literature. Nevertheless, few of them have been interested in decreasing the problem complexity and reducing the research space of correspondences between the input...

It is becoming increasingly likely that in the future most vehicles will be semi-autonomous with communication capabilities and will possess diverse speed capabilities. The aim of this paper is to describe the creation of an integrated traffic simulation system for such settings. While behaviours such...

Genetic Algorithms are efficient search and optimization techniques inspired by natural evolution. To show the difficulties in solving constrained optimization problems through GA, the 0/1 knapsack problem with user specific object preferences has been taken up. A new genetic operator, namely, ‘gene...

To provide security for data gathering based on network coding in wireless sensor networks (WSNs), a secure network coding-based data gathering model is proposed, and a data-privacy preserving and pollution preventing (DPP&PP) protocol using network coding is designed. DPP&PP makes use of a new...

Aiming at the decision-making problem in heterogeneous information environment and considering the influence of decision makers' psychological behavior on decision-making results, this paper proposes a multi-attribute decision-making method based on prospect theory in heterogeneous information environment....

The evolution of wireless multimedia sensor networks (WMSN) has opened the door to a wide range of applications such as telemedicine, surveillance, and intrusion detection. However, the delivery of multimedia content over wireless sensor networks requires maintaining the quality of service demands of...

The main objective of this paper is to present a transparent Decision Support System (DSS) for the energy managers of buildings, which can assist them in setting indoor temperature set point, based on the feedback received by the occupants. Within the proposed DSS, the Thermal Comfort Validator (TCV)...

In soccer, like in other collective sports, although players try to hide their strategy, it is always possible, with a careful analysis, to detect it and to construct a model that characterizes their behavior throughout the game phases. These findings are extremely relevant for a soccer coach, in order...

Nowadays the effect of industrial production on the environment brought out the importance of the green concept in supply chains. Particularly for supplier firms, greening is essential in a supply chain because with growing worldwide awareness of environmental protection, green production has become...

Few-shot image segmentation intends to segment query images (test images) given only a few support samples with annotations. However, previous works ignore the impact of the object scales, especially in the support images. Meanwhile, current models only work on images with the similar size of the object...

The LED is a new lightweight cipher, which was published in CHES 2011. This cipher could be applied in the Wireless Sensor Network to provide security. On the basis of the single byte-oriented fault model, we propose a differential fault analysis on the LED cipher. The attack could recover its 64-bit...

Cloud computing services are a new information technology trend for business applications in knowledge management systems (KMS). The link between cloud computing services and KMS is a new concept, and methods for selecting multiple choice goals of cloud computing service provider have lacked a formal...

In the area of video surveillance, tracking model for multiple object video is still a challenging task since the objects are usually affected with inter-object occlusion, object confusion, different posing, environment with heavy clutter, small size of objects, similar appearance among objects, and...

Literature presents several search algorithms to find an item with specified properties from a search space defined by a mathematical formula or procedure. One of the widely accepted algorithms is optimization algorithm which can find the optimal element within a certain period of time if the search...

Recently, a kind of heuristic optimization algorithm named gravitational search algorithm (GSA) has been rapidly developed. In GSA, there are two main parameters that control the search process, namely, the number of applied agents (Kbest) and the gravity constant (G). To balance exploration and exploitation,...

Delays often occur during some activities in software development projects. Without handling of project delays effectively, many software development projects fail to meet their deadlines. If extra employees with same or similar skills and domain knowledge can be rescheduled for the remaining activities...

In this paper, an uncertain integrated model for simultaneously locating temporary health centers in the affected areas, allocating affected areas to these centers, and routing to transport their required good is considered. Health centers can be settled in one of the affected areas or in a place out...

Facial expressions are important cues to observe human emotions. Facial expression recognition has attracted many researchers for years, but it is still a challenging topic since expression features vary greatly with the head poses, environments, and variations in the different persons involved. In this...

The issue of decision-making of autonomous agents constitutes the current work topic for many researchers. In this paper we propose to extend the existing model of value-based teleological reasoning by a new, numerical manner of representation of the level of value promotion. The authors of the paper...

A reputation management system is crucial in online transaction systems, in which a reputation function is its central component. We propose a generalized set-theoretic reputation function in this paper, which can be configured to meet various assessment requirements of a wide range of reputation scenarios...

Roughness is a comprehensive assessment indicator of pavement performance. Prediction of pavement roughness exhibits great difficulties by using traditional methods such as mechanistic-empirical method and regression method. Considering the fact that the value of international roughness index (IRI) varies...

Designing a wearable driver assist system requires extraction of relevant features from physiological signals like galvanic skin response and photoplethysmogram collected from automotive drivers during real-time driving. In the discussed case, four stress-classes were identified using cascade forward...

Text present in image provides important information for automatic annotation, indexing and retrieval. Therefore, its extraction is a well known research area in computer vision. However, variations of text due to differences in orientation, alignment, font, size, low image contrast and complex background...

In the MS/TP network, token is passed according to the address of master station. A novel token passing algorithm was proposed based on the characteristics of MS/TP network frame distribution and the requirements of real-time performance. The algorithm adopts distributed control method, which can adjust...

This paper presents a novel approach of designing linear phase FIR low pass and high pass filter using Random PSO in hybrid with DE known as Random PSODE (RPSODE). In this paper, the Random PSO is used which utilises the weighted particle to guide the search direction for both explorative and exploitative...

In this paper, we propose a framework for building a human-machine language dictionary. Given a concept/word, an application can extract the definition of the concept from the dictionary, and consequently “understand” its meaning. In the dictionary, a concept is defined through its relations with other...

Localization of sensor nodes in wireless sensor networks (WSNs) is very important since it associates spatial context with the data collected by sensor nodes and used in applications. Rapid development of wireless sensor technologies and wide applications of wireless sensor networks have also made security...

Energy storage alternatives that help storing excess energy and then using it when the system needs it has become more important in recent years. Determination of the most suitable energy storage alternative can be analyzed by using multi criteria decision making (MCDM) techniques. There are many criteria...

The theory of Pythagorean fuzzy sets possesses significant advantages in handling vagueness and complex uncertainty. Additionally, Pythagorean fuzzy information is useful to simulate the ambiguous nature of subjective judgments and measure the fuzziness and imprecision more flexibly. The aim of this...

Encryption is an important mechanism used to protect private information from unauthorized access. Thus, cipher systems play an important role in the communication and storage systems. But, designing a cipher system of good properties, such as high degree of security and efficiency, is a complex process....

Dominance-based rough set approach is the extension of classical Pawlak rough set theories and methodologies, in which the information with preference-ordered relation on the domain of attribute value is fully considered. In the dominance-based information system, upper and lower approximations will...

Feature selection is used as a preprocessing step in the resolution of many problems using machine learning. It aims to improve the classification accuracy, speed up the model generation process, reduce the model complexity and reduce the required storage space. Feature selection is an NP-hard combinatorial...

Nowadays, drones are expected to be used in several engineering and safety applications both indoors and outdoors, e.g., exploration, rescue, sport, entertainment, and convenience. Among those applications, it is important to make a drone capable of flying autonomously to carry out an inspection patrol....

Cloud computing bring a tremendous complexity to information security. Remote attestation can be used to establish trust relationship in cloud. TBVMM is designed to extend the existing chain of trust into the software layers to support dynamic remote attestation for cloud computing. TBVMM uses Bayesian...

For actual decision making problems, decision makers sometimes may have difficulty to provide all the preference information over alternatives through pairwise comparisons. In this paper, we focus on estimating missing elements for an incomplete uncertain 2-tuple linguistic preference relation. First,...

The flexible job shop scheduling problem (FJSP) is one of the most important problems in the field of production scheduling, which is the abstract of some practical production processes. It is a complex combinatorial optimization problem due to the consideration of both machine assignment and operation...

Prior to every academic semester, every department's administrator is required to offer the best overall set of courses to meet student requirements, instructor needs and department regulations. The key contributions of this research is firstly, determining the potential factors that influence student...

The modeling of biological phenomena and its adaptations to distributed computing are promising research areas. The computational modeling of neurobiological phenomena, such as cognition and consciousness, has potential for applications into bio-inspired distributed computing. The functioning of neurological...

Based on the fully implicational idea, we investigate the interval-valued fuzzy reasoning with multiantecedent rules. First, we construct a class of interval-valued fuzzy implications by means of a type of implications and a parameter on the unit interval, then use them to establish three kinds of fully...

The elitist nondominated sorting genetic algorithm (NSGA-II) is hybridized with the sine-cosine algorithm (SCA) in this paper to solve multiobjective optimization problems. The proposed hybrid algorithm is named nondominated sorting sine-cosine genetic algorithm (NS-SCGA). The main idea of this algorithm...

Integrating aspects of the risk perception attitude framework and perceived interactivity, this study investigates the impact of the social media interaction environment on users' motivation and behavioral intention to reproductive health communication. A survey was conducted, and structural equation...

The population migration algorithm is a very effective evolutionary algorithm for solving single-objective optimization problems, but very few applications are available for solving multi-objective optimization problems (MOPs). The current study proposes an improved population migration algorithm for...