International Journal of Computational Intelligence Systems

By simulating the self-adaptive phenomena of plants in nature, a novel evolutionary algorithm named Bean Optimization Algorithm (BOA) was proposed in 2008. BOA can be used for resolving complex optimization problems. As BOA is a new optimization algorithm, theoretical analysis of the algorithm is still...

Selecting an appropriate six sigma project is one of the most important problems for a manufacturing company because it impacts the manufacturing costs. Besides, an appropriate choice of Six Sigma projects is very important as it helps to improve quality, reduce variation, and eliminate waste of a manufacturing...

Maritime transport is one of the oldest methods of moving various types of goods, and it continues to have an important role in our modern society. More than 20 million containers are transported across the oceans daily. However, this form of transportation is constantly threatened by illegal operations,...

Process Failure Modes and Effects Analysis (PFMEA) concept, has been developed based on the success of Failure Modes and Effects Analysis (FMEA) to include a broader analysis team for the realization of a comprehensive analysis in a short time. The most common use of the PFMEA involves manufacturing...

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...

Sentiment analysis has been extensively studied recently for developing methodologies to automatically extract information from online reviews, which is important for manufacturers to improve their products or services. Unfortunately, most of current studies don’t take several key factors (e.g., sentiment...

Abstract In this work we present the results for the automatic determination of the mean longitudinal magnetic field in polarized stellar spectra through the analysis of spectropolarimetric observations. In order to determine this important parameter, we first developed a synthetic database encompassing...

Primary school selection is actually a decision making problem that should be supported with several source of information. Parents usually handle this problem in an unstructured manner which is indeed a fuzzy mental ranking of schools with respect to the effectiveness. In this study, an analytical hybrid...

This paper presents a flexible multi-criteria group decision making method based on ideal points concept, which can be used to deal with heterogeneous information(numerical, interval valued and linguistic variable with different granularity and/or semantic)and reflect the Decision Makers’ different...

This paper aims to formally define a concept of interpretability according to natural language of a logical theory, and show advances for demonstrating that the logic system called Compensatory Fuzzy Logic is interpretable. A logical theory is interpretable according to natural language if the calculus...

Feature selection is an important preprocessing step in pattern classification and machine learning, and mutual information is widely used to measure relevance between features and decision. However, it is difficult to directly calculate relevance between continuous or fuzzy features using mutual information....

In the field of fuzzy utility mining, the characteristics of transaction time have been a widely studied topic in data mining. However, using a single-conditional threshold for all items does not suffice to reflect the true properties of items. This paper, therefore, proposes a multi-conditional minimum...

Gradient search based neural network training algorithm may suffer from local optimum, poor generalization and slow convergence. In this study, a novel Memetic Algorithm based hybrid method with the integration of “extremal optimization” and “Levenberg–Marquardt” is proposed to train multilayer perceptron...

In this paper, the concept of minimal intuitionistic dominating vertex subset of an intuitionistic fuzzy graph was considered, and on its basis, the notion of a domination set as an invariant of the intuitionistic fuzzy graph was introduced. A method and an algorithm for finding all minimal intuitionistic...

As a new type of heterogeneous social network, Event-Based Social Network (EBSN) has experienced rapid development after its appearance. In EBSN, the interaction data between users and events is relatively sparse because of the short life cycle of events, which brings great challenges to event recommendation....

Network intrusion detection systems (NIDSs) have become an indispensable component for the current network security infrastructure. However, a large number of alarms especially false alarms are a big problem for these systems which greatly lowers the effectiveness of NIDSs and causes heavier analysis...

A fuzzy logic system (FLS) is established for damage identification of simply supported bridge. A novel damage indicator is developed based on ratios of mode shape components between before and after damage. Numerical simulation of a simply-supported bridge is presented to demonstrate the memory, inference...

As an attractive generalization to hesitant fuzzy linguistic term set, double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) is used to represent complex linguistic expressions by providing rich and flexible context. Previous studies on DHHFLTS show that aggregation of preference information...

Deep learning can automatically learn the complex features of input data and is recognized as an effective method for bearing fault diagnosis. Convolution neuron network (CNN) has been successfully used in image classification, and images of vibration signal or time-frequency information from short-time...

In this paper, we investigate the document categorization task with statistical language models. Our study mainly focuses on categorization of documents in agglutinative languages. Due to the productive morphology of agglutinative languages, the number of word forms encountered in naturally occurring...

This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, is related to some technical limitations that exist on small satellite technology. The...

It is critical to develop secure software with long-term performance and capability to withstand and forestall the growing competition in the software development industry. To enhance the potential of Confidentiality, Integrity, and Availability (CIA), a mechanism is required to built in and secure the...

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...

A new hybrid adaptive control algorithm is proposed for the nonlinear system controller design of underwater robot. Compared with the previous works in the controller design of underwater robot, the main advantages of this work are: (1) A new disturbance prediction and compensation model is proposed;...

In this study, we consider data envelopment analysis for comparison between thermal energy plants which are natural gas based and coal based power plants. Results of this study will give a roadmap to decision makers in selecting type of thermal plant they will construct. Also public and private energy...

Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers...

This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN). Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems...

For good security and large payload in information hiding, matrix embedding is a popular method for increasing the embedding efficiency. This paper analyzes the security of matrix embedding against cryptanalytic attacks. The secrecy security of matrix embedding using information theory under the conditions...

As the rapid booming of reviews, a valid sentiment analysis model will significantly boost the review recommendation system’s capability, and present more constructive information for consumers. Topic probabilistic models have already shown many advantages for detecting potential structure of topics...

The quality of teaching can be improved by teaching performance evaluation from multiple experts, which is a multiple attribute group decision-making (MAGDM) problem. In this paper, a group decision-making method under proportional hesitant fuzzy linguistic environment is proposed to evaluate teaching...

This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE) algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE), which adopts an adaptive...

A general Methodology referred to as Daphne is introduced which is used to find optimum combinations of methods to preprocess and forecast for time-series datasets. The Daphne Optimization Methodology (DOM) is based on the idea of quantifying the effect of each method on the forecasting performance,...

The technology state is determined not by a single data, but by multiple data sources that has a certain degree of uncertainty and ambiguity, and even be contradictory which is difficult to support decision-making effectively. In this paper, an efficient intelligent decision-making method based on multi-source...

In this paper, robust adaptive tracking control is proposed for the underwater robot in the presence of parametric uncertainties and unknown external disturbances. Backstepping control of the system dynamics is introduced to develop full state feedback tracking control. Using parameter adaptation, backstepping...

In this paper are introduced some concepts of interval-valued fuzzy relations and some of their properties: reflexivity, symmetry, T-transitivity, composition and local reflexivity. The existence and uniqueness of T-transitive closure of interval-valued fuzzy relations is proved. An algorithm to compute...

It proposes a pseudo-random number generation algorithm based on cellular neural networks. This method uses the hyper-chaos characteristics of the cellular neural networks and sets the appropriate parameters to generate the pseudo-random number. The experimental results show that, compared with other...

Collaborative labeling portrays the process by which numerous users put in metadata in the form of keywords to shared data. Nowadays, collaborative labeling has grown in reputation on the web, on sites that permit users to label bookmarks, photographs and other details. It has been recently become useful...

In this paper, we developed an automatic music generator with midi as the input file. This study uses long short-term memory (LSTM) and gated recurrent units (GRUs) network to build the generator and evaluator model. First, a midi file is converted into a midi matrix in midi encoding process. Then, each...

In this paper we propose a framework for modeling, representing populating and enriching information from online collaborative sessions within Web forums. The main piece of the framework is an ontology called Collaborative Session Conceptual Schema (CS) that allows for specifying collaborative sessions....

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,...

Feature selection is an important technique for dimension reduction in machine learning and pattern recognition communities. Feature evaluation functions play essential roles in constructing feature selection algorithms. This paper introduces a new notion of knowledge granularity, called conditional...

Group method of data handling (GMDH)-type neural network algorithms are the self-organizing algorithms for modeling complex systems. GMDH algorithms are used for different objectives; examples include regression, classification, clustering, forecasting, and so on. In this paper, we present GMDH2 package...

This paper presents a novel Intelligent Inference System (IIS) for the determination of an optimum preshape for multifingered robot hand grasping, given object under a manipulation task. The IIS is formed as hybrid agent architecture, by the synthesis of object properties, manipulation task characteristics,...

The permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs well...

The paper describes solving problem of constructing knowledge database of a decision making in process safety. It provides analyses of the requirements as well the analyses of the system incidents caused by specification, design and the implementation of the project. Main focus of this scientific paper...

In this paper, a modified version of nature-inspired optimization algorithm called Black Hole has been proposed. The proposed algorithm is population based and consists of genetic algorithm operators in order to improve optimization results. The proposed method enhances Black Hole algorithm performance...

Outlier detection is a hot topic in machine learning. With the newly emerging technologies and diverse applications, the interest of outlier detection is increasing greatly. Recently, a significant number of outlier detection methods have been witnessed and successfully applied in a wide range of fields,...

Service selection problem refers to the selection of appropriate Web services from a large number of candidates in order to create complex composite services that can satisfy users’ quality-of-service (QoS) requirements. However, the existing services selection methods seldom consider the parallel...

The sensory evaluation of food quality using a machine learning approach provides a means of measuring the quality of food products. Thus, this type of evaluation may assist in improving the composition of foods and encouraging the development of new food products. However, human intervention has been...

Since their first appearance in 1997 in the prestigious journal Science, algorithm portfolios have become a popular approach to solve static problems. Nevertheless and despite that success, they have not received much attention in Dynamic Optimization Problems (DOPs). In this work, we aim at showing...

Different studies have shown the benefits of a cooperative activities programme for the elderly. Members of a group with similar abilities or disabilities are often encouraged by having the opportunity to share their experiences, knowledge, or opinions. Nevertheless, when caregivers try to plan specific...

When detecting of emotions from music, many features are extracted from the original music data. However, there are redundant or irrelevant features, which will reduce the performance of classification models. Considering the feature problems, we propose an embedded feature selection method, called Multi-label...

In this paper, we propose a facial feature localization algorithm based on a binary neural network technique - k-Nearest Neighbour Advanced Uncertain Reasoning Architecture (kNN AURA) to encode, train and match the feature patterns to accurate identify the nose tip in 3D. Based on the results of the...

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...

This paper presents a computer aided analysis system for detecting epileptic seizure from electroencephalogram (EEG) signal data. As EEG recordings contain a vast amount of data, which is heterogeneous with respect to a time-period, we intend to introduce a clustering technique to discover different...

The Moore–Penrose inverse of a matrix plays a very important role in practical applications. In general, it is not easy to immediately solve the Moore–Penrose inverse of a matrix, especially for solving the Moore–Penrose inverse of a complex-valued matrix in time-varying situations. To solve this problem...

Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very high resource requirements. This paper proposes architecture...

In Mobile Ad hoc networks broadcasting is the one of the most important and crucial phenomenon. Broadcasting can be taken up in many ways and the simplest method of broadcasting is simple flooding which can significantly increase the overheads and can result in redundant messages which can further cause...

The purpose of this study is to compare the performances of Artificial Neural Networks (ANN) and Multinomial Probit (MNP) approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models...

It is very difficult to create the fault trees based on components framework for some complex equipment. So a multi-hierarchy diagnosis method based on fault categories is proposed in this paper. The according storage model of rules is designed, and the concept of rule priority is introduced. Then, a...

In recent years, the relationship between companies and suppliers has changed with the continuous rise in environmental awareness and customer expectations. In order to fulfill customers’ needs, the actors in a Supply Chain (SC) network sometimes compete and sometimes cooperate with each other. In SC...

At present, most of the first-order logic theorem provers use a binary-resolution method, which can effectively solve the general first-order logic problems to a certain extent. However, the cooperative processing ability of this method for multiple clauses is insufficient, and it is easy to cause rapid...

Academia and practitioners confirm that software project effort prediction is crucial for an accurate software project management. However, software development effort estimation is uncertain by nature. Literature has developed methods to improve estimation correctness, using artificial intelligence...

In this work we predict time series of air pollution data taken in Mexico City and the Valley of Mexico, by using the Gamma Classifier which is a novel intelligent associative mathematical model, coupled with an emergent coding technique. Historical and current data about the concentration of specific...

This paper presents a fuzzy multi-criteria decision-making (FMCDM) approach based on cloud model and prospect theory. In addition, a reference point selection method is developed according to the evaluations of the potential customer or similar consumers regarding certain items. An example of purchasing...

Wireless sensor networks (WSNs) involves a set of wireless sensor nodes located within a region of interest (ROI) to acquire and/or transmit specific information from their surroundings. A common problem in the operation of WSNs is sensor coverage, which is related to the distribution of sensor nodes...

As a novel swarm intelligence optimization algorithm, cuckoo search (CS), has been successfully applied to solve various optimization problems. Despite its simplicity and efficiency, the CS is easy to suffer from the premature convergence and fall into local optimum. Although a lot of research has been...

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...

Focusing on the just-in-time (JIT) operations management, earliness as well as, tardiness of jobs’ production and delivery should be discouraged. In accordance to this philosophy, scheduling problems involving earliness and tardiness penalties are very critical for the operations manager. In this...

In this paper, a novel method to generate fuzzy edges in medical images using the Type II fuzzy set theory is presented. Medical images are normally poorly illuminated and many edges are not visible properly, so construction of fuzzy edge image is a difficult task. Fuzzy edges are not the binary edges...

In this paper, we study relations between fuzzy implicators and some kinds of fuzzy conjunctors, in particular, quasi-copulas and copulas. We show that there is a one-to-one correspondence between the classes of all quasi-copulas and 1-Lipschitz fuzzy implicators. A similar relation holds for copulas...

A general framework for vehicle assessment is proposed based on both mass survey information and the evidential reasoning (ER) approach. Several methods for uncertainty and preference modeling are developed within the framework, including the measurement of uncertainty caused by missing information,...

Nan et al. [J.-X. Nan, D.-F. Li and M.-J. Zhang, A lexicographic method for matrix games with payoffs of triangular intuitionistic fuzzy numbers, International Journal of Computational Intelligence Systems 3(3) (2010) 280-289] pointed out that there is no method in the literature to find the solution...

A novel clustering algorithm named local reachability density peaks clustering (LRDPC) which uses local reachability density to improve the performance of the density peaks clustering algorithm (DPC) is proposed in this paper. This algorithm enhances robustness by removing the cutoff distance dc which...

This paper investigated the value concept of lean management to improve the performance of an emergency department (ED). This paper aims to analyze on patient perceived value (PPV) to apply lean management principles in the ED. The DEMATEL (Decision Making Trial and Evaluation Laboratory) method has...

Multi-objective programming with uncertain information has been widely applied in modeling of industrial produce and logistic distribution problems. Usually the expectation value model and chance-constrained model as solution models are used to deal with such uncertain programming. In this paper, we...

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...

Multiple Traveling Salesman Problem (MTSP) is able to model and solve various real-life applications such as multiple scheduling, multiple vehicle routing and multiple path planning problems, etc. While Traveling Salesman Problem (TSP) focuses on searching a path of minimum traveling distance to visit...

Deep neural networks (DNN) are a powerful tool that is used in many real-life applications. Solving complicated real-life problems requires deeper and larger networks, and hence, a larger number of parameters to optimize. This paper proposes a multilevel architecture of deep learning (MADL) that breaks...

We propose an online sensorimotor architecture for controlling a low-cost humanoid robot to perform dance movements synchronized with musical stimuli. The proposed architecture attempts to overcome the robot's motor constraints by adjusting the velocity of its actuators and inter-changing the attended...

Effective manipulation of context is very important in providing the context-aware services. In recent years, a variety of context models have been proposed to properly handle the key aspects of the context, while focusing on scenario-based acquisition, management, and representation of context. However,...

Hesitant fuzzy linguistic term sets (HFLTSs) are very useful for dealing with the situations in which the decision makers hesitate among several linguistic terms to assess an alternative. Some multi-criteria decision-making (MCDM) methods have been developed to deal with HFLTSs. These methods are derived...

Generative adversarial network (GANs) has significant progress in 3D model generation and reconstruction recently years. GANs can generate 3D models by sampling from uniform noise distribution. But they generate randomly and are often not easy to control. To address this problem, we add the class information...

Based on conflict analysis and lattice order theory, this paper integrates fuzziness and non-transitivity of the preference, exclusiveness and incommensurability of the objective into conflict analysis, proposes a new fuzzy multi-objective lattice order decision method for preference ranking in conflict...

The influence of individual heterogeneity on the evolutionary game has been studied extensively in recent years. Whereas many theoretical studies have found that the heterogeneous learning ability effects cooperation rate, the individual learning ability in networks is still not well understood. It is...

Since comprehensive evaluation model was introduced by Wang in 1984, the comprehensive evaluation model has many successful applications in real life. But some examples show the inefficiency of the comprehensive evaluation model. In order to process these problems, in this paper, we introduce two concepts...

In natural language processing the use of deep learning techniques is very common. In this paper, a technique to identify the subject and predicate in a sentence is introduced. To achieve this, the proposed technique completes POS tagging identifying in a later stage the subject and the predicate in...

Concept lattice, as an effective tool for knowledge acquisition and data analysis, has been successfully used in many fields. Aiming at the problem of groups for uncertain information in the linguistic environment, this paper mainly focuses on the granule description with linguistic concept lattice from...

The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA), an effective...

After analyzing the common attacks for some software systems, a dynamic software behavior verification model related with the unchecked input data based on software analysis and dynamic slicing technology is proposed. Regarding a statement as a basic analysis unit, and the information flow as the main...

For the fuzzy systems with the kernel-shaped fuzzy sets of if part, we estimate the rates of the uniform approximation for continuous functions. Results are given associatively with the rates of convergence of the sequence (logk/k)a.

The Truck and Trailer Routing Problem consists of a heterogeneous fleet composed of trucks and trailers to serve a set of customers. This problem has been solved previously considering accurate data available. But in a real-world the available knowledge about some data and parameters involves a vague...

The concept of T-normed fuzzy TM-subalgebras is introduced by applying the notion of t-norm to fuzzy TM-algebra and its properties are investigated. The ideas based on minimum t-norm are generalized to all widely accepted t-norms in a fuzzy TM-subalgebra.The characteristics of an idempotent T-normed...

This paper investigates the consensus decision making problem of the interval-valued fuzzy preference relation with distribution characteristics. The proposed group consensus decision making model is constructed by considering the scenarios in which the DMs are respectively equally and non-equally weighted...

In this paper, based on the off-axis circle criterion, a sufficient condition with a simple graphical explanation is derived to analyze the global asymptotic stability of a type of Takagi-Sugeno (T-S) fuzzy control systems in case of different constant reference inputs. Three numerical examples are given...

Software fault prediction techniques are helpful in developing dependable software. In this paper, we proposed a novel framework that integrates testing and prediction process for unit testing prediction. Because high fault prone metrical data are much scattered and multi-centers can represent the whole...

The objective of this study is to provide an effective multi criteria decision making (MCDM) approach with group decision making to evaluate different smart phone alternatives according to consumer preferences. The choice of the most appropriate phone is a very complex decision, involving several perspectives....

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...

The traceability is of paramount importance and considered as a prerequisite for businesses for long-term functioning in today's global supply chain. The implementation of traceability can create visibility by the systematic recall of information related to all processes and logistics movement....