International Journal of Computational Intelligence Systems

Histograms are an intuitively understandable tool for graphically presenting frequency data that is available for and useful in modern data-analysis, this also makes comparing histograms an interesting field of research. The concept of similarity and similarity measures have been gaining in importance,...

This paper introduces FISDeT, a tool to support the design of Fuzzy Inference Systems, composed of a set of Python modules sharing the standard specification language FCL used for FIS definition. FISDeT includes a graphical user interface that enables easy definition and quick update of elements composing...

This paper addresses a robust adaptive control problem of non-square nonlinear systems with unmeasurable states. The systems are assumed to be multi-input/multi-output subject to dynamical uncertainties and external disturbances. The approach is studied for two cases, i.e., underactuated and over-actuated...

Effective query expansion terms selection methods are really very important for improving the accuracy and efficiency of Pseudo-Relevance Feedback (PRF) based automatic query expansion techniques in information retrieval system. These methods remove irrelevant and redundant terms from the top retrieved...

A priori incorporation of the decision maker’s preferences is a crucial issue in many-objective evolutionary optimization. Some approaches characterize the best compromise solution of this problem through fuzzy outranking relations; however, they require the elicitation of a large number of parameters...

The guidelines published by the European Banking Authority in 2015 about the contributions to the Deposit Guarantee Systems, establish two approaches to classify the member entities’ risk: the bucket method and the sliding scale method, allowing freedom to every Member State to decide which methodology...

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

The iso, hypo or hyper intensity, similarity of shape, size and location complicates the identification of brain tumors. Therefore, an adequate Computer Aided Diagnosis (CAD) system is designed for classification of brain tumor for assisting inexperience radiologists in diagnosis process. A multifarious...

In this paper, several cross-entropy measures for linguistic hesitant intuitionistic fuzzy information have been developed which integrating cross-entropy measures of intuitionistic fuzzy sets and hesitant fuzzy linguistic sets. Some desirable properties of new cross-entropy measures have been studied....

Classical DC-DC converters used in high voltage direct current (HVDC) power transmission systems, lack in terms of efficiency, reduced transfer gain and increased cost with sensor (voltage/current) numbers. Besides, the internal self-parasitic behavior of the power components reduces the output voltage...

The calculation of the premium cost of an option exchange is usually computed by the different mathematical models that obtain the degree of uncertainty in the financial market by Black-Scholes method though such a degree is inaccurate. In order to improve the management of uncertainty the use of fuzzy...

Acid gas removal (AGR) units are widely used to remove CO2 and H2S from sour gas streams in natural gas processing. When foaming occurs in an AGR system, the efficiency of the process extremely decreases. In this paper, a novel approach is suggested to regularly predict the gas dew point temperature...

Bayesian networks have been widely used for classification problems. These models, structure of the network and/or its parameters (probability distributions), are usually built from a data set. Sometimes we do not have information about all the possible values of the class variable, e.g. data about a...

In this article a fuzzy multiobjective chance constrained programming model is used for modeling and solving land allocation problems efficiently with the help of fuzzy goal programming. Optimal production of seasonal crops and related expenditures are considered from the viewpoint of proper utilization...

The incremental updating of lower and upper approximations under the variation of information systems is an important issue in rough set theory. Many incremental updating approaches with respect to different kinds of indiscernibility relations have been proposed. The grade indiscernibility relation is...

In the current era, crowd behavior analysis is important topic due to the significance of video surveillance in the public area. Literature presents a handful of works for crowd behavior detection and analysis. Even though, the complicated challenges such as, low quality video, wide variation in the...

Diabetes is one of the foremost causes for the increase in mortality among children and adults in recent years. Classification systems are being used by doctors to analyse and diagnose the medical data. Radial basis function neural networks are more attractive for classification of diseases, especially...

A speller is a communication device designed for those suffering from neuromuscular disorders having difficulty to speak. An EMG based design is proposed which uses eye blinks for character selection that offers high accuracy and more comfort to the user. The eye blink signals are feature extracted using...

A simple multigranulation rough set approach is to approximate the target through a family of binary relations. Optimistic and pessimistic multigranulation rough sets are two typical examples of such approach. However, these two multigranulation rough sets do not take frequencies of occurrences of containments...

In sustainable supply chain networks, companies are obligated to have a systematic decision support system in place to help it adopt right decisions at right times. Among strategic decisions, supplier selection and evaluation outranks other decisions in terms of importance due to its long-term impacts....

In order to process the linguistic-valued information with uncertainty in the financial decision- making, the present work uses a lattice-valued logical algebra - lattice implication algebra to deal with both comparable and incomparable linguistic truth-values. A new personal financial decision auxiliary...

Project monitoring and control by using key performance indicators has become a widespread method for decision-making in project-oriented organizations. However, the current schools and IT tools created for this purpose require an upgrade in design due to imprecision, vagueness or uncertainty present...

The stock price shows the character of complex non-linear system, along with changes of internal and external environmental factors in stock market. As a form of artificial intelligence, neural network can fully reveal the complex relationship between investors and price fluctuations. After comparing...

In this article assessment of morningness of individuals has been performed using fuzzy reasoning approach. The responses are quantified using fuzzy numbers. Based on experts’ opinion a fuzzy rule-base is prepared. The model is validated by considering responses of some students, selected randomly, and...

Cloud Computing is a utility model that offers everything as a service and supports dynamical resource provisioning and auto-scaling in datacenter. Cloud datacenter must envision resource allocation and reallocation to meet out the unpredictable user demand that touted gains in the model. This impact...

The model proposed in this paper, is a hybridization of fuzzy neural network (FNN) and a functional link neural system for time series data prediction. The TSK-type feedforward fuzzy neural network does not take the full advantage of the use of the fuzzy rule base in accurate input-output mapping and...

We put forward a completely redesigned approach to soft set based decision making problems under incomplete information. An algorithmic solution is proposed and compared with previous approaches in the literature. The computational performance of our algorithm is critically analyzed by an experimental...

The development of a computational tool for the recognition of numerical characters already segmented from Chilean license plates, located in semi-controlled scenarios, is presented. Two algorithms are highlighted: one for the Fine Segmentation of the Characters through the K-Means algorithm and a system...

We are interested in this paper in studying and developing a decision support tool for multi-skill health care tasks scheduling in the Pediatric Emergency Department. We use an evolutionary algorithm and we propose the use of fuzzy logic to formulate an adapted fitness function. We consider the potential...

Survival prediction of poly-trauma patients measure the quality of emergency services by comparing their predictions with the real outcomes. The aim of this paper is to tackle this problem applying C4.5 since it achieves accurate results and it provides interpretable models. Furthermore, we use sampling...

Intuitionistic fuzzy preference relation (IFPR), which express experts’ preferences from the preferred, the non-preferred and the indeterminate aspects, has turned out to be an efficient tool in describing the rough and subjective opinions of experts. This paper focuses on the consensus measures for...

Indeed, interesting properties of artificial neural networks approach made this non-parametric model a powerful tool in solving various complicated mathematical problems. The current research attempts to produce an approximate polynomial solution for special type of fractional order Volterra integro-differential...

This paper aims to study the lightpaths provisioning problem in optical WDM networks with scarce available wavelengths under the static (off-line) traffic demands such that network operator’s (NO’s) revenue is maximized. To achieve this goal, a NO has to be addressed with the issue how to solve the call...

Though cloud computing has become an attractive technology due to its openness and services, it brings several security hazards towards cloud storage. Since the distributed nature of clouds is achieved through internetworking technologies, clouds suffer from all the vulnerabilities by which networking...

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...

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...

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...

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...

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...

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...

Selecting transport project to invest is an important task. This paper offers a new sustainable transport investment selection approach that applies interval-valued fuzzy sets (IVFSs) to address uncertainty. Relative preference relation is employed to address importance of criteria. Judgments of experts...

This paper proposes a new algorithm called Multimodal Flower Pollination Algorithm (MFPA). Under MFPA, the original Flower Pollination Algorithm (FPA) is enhanced with multimodal capabilities in order to find all possible optima in an optimization problem. The performance of the proposed MFPA is compared...

Software Fault Prediction (SFP) is found to be vital to predict the fault-proneness of software modules, which allows software engineers to focus development activities on fault-prone modules, thereby prioritize and optimize tests, improve software quality and make better use of resources. In this regard,...

In this paper, we investigate the cluster techniques of hesitant fuzzy information. Consider that the distance measure is one of the most widely used tools in clustering analysis, we first point out the weakness of the existing distance measures for hesitant fuzzy sets (HFSs), and then put forward a...

We present a new multiple-type museum visitor routing problem (MT-MVRP) in which a museum’s exhibition rooms are classified into must-see and select-see rooms. A novel encoding scheme is proposed to simultaneously determine the scheduling of rooms for all of the groups and an immune based evolutionary...

Almost all the worldwide and nationwide companies utilize advertising to increase their sales volume and profit. These companies pay millions of dollars to reach consumers and announce their products or services. This forces companies to evaluate advertising effects and check whether ads meet companys...

Graphs are the backbone of many real systems like social networks, image segmentation, scheduling, etc. To input uncertainty to such systems, generalized fuzzy graphs are used. Generalized fuzzy tree is one generalized fuzzy subgraph of a generalized fuzzy graph which characterizes the whole graph. In...

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...

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,...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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 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...

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...

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...

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...

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,...

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...

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...

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)...

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...

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...

For many of the applications in which wireless sensor networks are used, it is important to know from which nodes or what location useful information is acquired. The Global Positioning System (GPS) is conventionally used to determine location. However, GPS systems are not ideal for many applications...

For the damage identification technique of civil structures, the reduction of the computational cost for methods based on the optimization algorithms is the most crucial step. In this study, a fast multi-stage method is developed that uses the multiple damage location assurance criterion and an improved...

This study examines the crew pairing problem, which is one of the most comprehensive problems encountered in airline planning, to generate a set of crew pairings that has minimal cost, covers all flight legs and fulfils legal criteria. In addition, this study examines current research related to crew...

This paper proposes a novel performance enhanced Jaya algorithm with a two group adaption (E-Jaya). Two improvements are presented in E-Jaya. First, instead of using the best and the worst values in Jaya algorithm, E-Jaya separates all candidates into two groups: the better and the worse groups based...

Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN) is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process...

This study applies the game theory to the discussion and analysis of trans-regional Telemedicine System, builds the game model of the selection strategies of trans-regional hospitals and patients and analyzes evolving paths, equilibrium states and influencing factors of the three parties. It is derived...

Solar energy is an important and reliable source of energy. Better understanding the concepts and relationships of the factors that affect solar energy generation capacity can enhance the usage of solar energy. This understanding can lead investors and governors in their solar power investments. However,...

In this paper, a multi-period multi-echelon reverse logistics network design problem under high extent of uncertainty is addressed. We first formulate and then solve the multi-period network design model using the cloud-based design optimization framework which ensures to: (1) handle high number of uncertain...

In this paper a coarse-grain execution model for evolutionary algorithms is proposed and used for solving numerical and combinatorial optimization problems. This model does not use migration as the solution dispersion mechanism, in its place a more efficient population-merging mechanism is used that...

Many hydrocarbon explorations in mature fields have been severely affected by complex and overburdening issues, such as shallow gas accumulation, gas pockets, and gas seepage. In this work, a new forward modelling technique is proposed in evaluating the potential survey design for fields affected by...

The significance of addressing Big Data applications is beyond all doubt. The current ability of extracting interesting knowledge from large volumes of information provides great advantages to both corporations and academia. Therefore, researchers and practitioners must deal with the problem of scalability...

The uncertain nonlinear systems can be modeled with fuzzy equations or fuzzy differential equations (FDEs) by incorporating the fuzzy set theory. The solutions of them are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this paper, the solutions...

This paper introduces the 3rd major release of the KEEL Software. KEEL is an open source Java framework (GPLv3 license) that provides a number of modules to perform a wide variety of data mining tasks. It includes tools to perform data management, design of multiple kind of experiments, statistical analyses,...

Wireless Sensor Networks (WSN) has the disadvantage of limited and non-rechargeable energy resource in WSN creates a challenge and led to development of various clustering and routing algorithms. The paper proposes an approach for improving network lifetime by using Particle swarm optimization based...

Localization is one of the key issues in wireless sensor networks. Several algorithms and techniques have been introduced for localization. Localization is a procedural technique of estimating the sensor node location. In this paper, a novel three hybrid algorithms based on firefly is proposed for localization...

Computational intelligence is often used in smart environment applications in order to determine a user’s context. Many computational intelligence algorithms are complex and resource-consuming which can be problematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. These...

Many endogenous and external components may affect the physiological, mental and behavioral states in humans. Monitoring tools are required to evaluate biomarkers, identify biological events, and predict their outcomes. Being one of the valuable indicators, brain biomarkers derived from temporal or spectral...

Modeling users’ data traces is of crucial importance for human behavior analysis and context-aware applications in ambient assisted living (AAL) environments. However, learning the parameters of the underlying model is a challenging task in multi-occupant environments; because, the anonymous users’ data...

Violence detection represents an important issue to take into account in the design of intelligent algorithms for smart environments. This paper proposes an energy-efficient system capable of acoustically detecting violence. In our solution, genetic algorithms are used to select the best subset of features...

Gender violence is one of the most serious and widespread problems in our society. In dangerous cases, the use of special devices for GPS tracing is recommended in some countries. However, these devices are used only in extreme cases and have many drawbacks. This work describes a new system to combat...

Topology plays an important role for Particle Swarm Optimization (PSO) to achieve good optimization performance. It is difficult to find one topology structure for the particles to achieve better optimization performance than the others since the optimization performance not only depends on the searching...

Network robustness against cascades is a major topic in the fields of complex networks. In this paper, we propose an attack-cost-based cascading failure model, where the attack cost of nodes is positively related to its degree. We compare four attacking strategies: the random removal strategy (RRS),...

Delivering goods in an efficient and cost-effective way is always a challenging problem in logistics. In this paper, the multi-depot vehicle routing is focused. To cope with the conflicting requirements, an advanced multi-objective evolutionary algorithm is proposed. Local-search empowered genetic operations...

Although conventional multi-objective evolutionary optimization algorithms (MOEAs) are proven to be effective in general, they are less superior when applied to solve a large-scale combinational real-world optimization problem with tightly coupled decision variables. For the purpose to enhance the capability...

We introduce a new method for storing, modeling, and analyzing power grid data. First, we present an architecture for building the network model for a power grid using the open source graph database Neo4j. Second, we design single- and multi-threading systems for initial energization analysis of the...