International Journal of Computational Intelligence Systems

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1147 articles

A Multi-Criteria Group Decision-Making Approach Based on Improved BWM and MULTIMOORA with Normal Wiggly Hesitant Fuzzy Information

Chengxiu Yang, Qianzhe Wang, Weidong Peng, Jie Zhu
Multi-criteria group decision-making (MCGDM) problems are widespread in real life. However, most existing methods, such as hesitant fuzzy set (HFS), hesitant fuzzy linguistic term set (HFLTS) and inter-valued hesitant fuzzy set (IVHFS) only consider the original evaluation data provided by experts but...

Optimal Walking Gait Generator for Biped Robot Using Modified Jaya Optimization Technique

Ho Pham Huy Anh, Tran Thien Huan
This paper treats the optimization of the biped walking trajectory that can be used as a reference trajectory for control. The biped robot is modeled as a kinetic chain of 11 links connected by 10 joints. The inverse kinematics of the biped is derived for the specified positions of the hips and feet....


Vahid Seydi Ghomsheh, Mohamad Teshnehlab, Mahdi Aliyari Shoorehdeli, Mojtaba Ahmadieh Khanesar
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Jesus Alcal´a-Fdez, Jose M. Alonso
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Tianrui Li, Pawan Lingras, Yuefeng Li, Joseph Herbert
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Wuhong Wang, Klaus Bengler
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Tianrui Li, Yang Xu
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Spontaneous Concept Learning with Deep Autoencoder

Serge Dolgikh
Pages: 1 - 12
In this study we investigate information processing in deep neural network models. We demonstrate that unsupervised training of autoencoder models of certain class can result in emergence of compact and structured internal representation of the input data space that can be correlated with higher level...


Pavel Anselmo Alvarez, Rafael Bello Perez
Pages: 1 - 2

Implications of Fuzziness for the Practical Management of High-Stakes Risks

Mark Jablonowski
Pages: 1 - 7
High-stakes (dangerous, catastrophic) risks take on a wider profile as progress unfolds. What are the impacts of technological and social change on the risk landscape? Due to the complexities and dynamics involved, we can only answer these questions approximately. By using the concept of fuzziness, we...

A New Clonal Selection Immune Algorithm with Perturbation Guiding Search and Nonuniform Hypermutation

Xinchao Zhao, Zaijin Zou, Shuliang Zhao, Guoshuai Zhao, Shaozhang Niu, Guoli Liu
Pages: 1 - 17
A new clonal selection immune algorithm with perturbation guiding search and non-uniform hypermutation (nCSIA) is proposed based on the idea of perturbed particle swarm algorithm and non-uniform mutation. The proposed algorithm proportional clones antibody based on the affinity, adaptively adjusts the...

Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

Huaxiong Li, Xianzhong Zhou
Pages: 1 - 11
Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers....

Comparing Circular Histograms by Using Modulo Similarity and Maximum Pair-Assignment Compatibility Measure

Pasi Luukka, Mikael Collan
Pages: 1 - 12
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,...

Computational intelligence in decision making

Macarena Espinilla, Javier Montero, J. Tinguaro Rodríguez
Pages: 1 - 5
In this preface we stress the relevance of the traditional collaboration between Engineering and any field of Mathematics in order to build intelligent decision-aid tools, as it is illustrated by the twelve papers contained in this Special Issue. These papers, selected by means of a standard peer review...

Almost Automorphic Solutions to Cellular Neural Networks With Neutral Type Delays and Leakage Delays on Time Scales

Changjin Xu, Maoxin Liao, Peiluan Li, Zixin Liu
Pages: 1 - 11
In this paper, cellular neural networks (CNNs) with neutral type delays and time-varying leakage delays are investigated. By applying the existence of the exponential dichotomy of linear dynamic equations on time scales, a fixed point theorem and the theory of calculus on time scales, a set of sufficient...

A Finite Equivalence of Verifiable Multi-secret Sharing

Hui Zhao, Mingchu Li, Kouichi Sakurai, Yizhi Ren, JonathanZ. Sun, Fengying Wang
Pages: 1 - 12
We give an abstraction of verifiable multi-secret sharing schemes that is accessible to a fully mechanized analysis. This abstraction is formalized within the applied pi-calculus by using an equational theory which characterizes the cryptographic semantics of secret share. We also present an encoding...

Near-Duplicate Web Page Detection: An Efficient Approach Using Clustering, Sentence Feature and Fingerprinting

J. Prasanna Kumar, P. Govindarajulu
Pages: 1 - 13
Duplicate and near-duplicate web pages are the chief concerns for web search engines. In reality, they incur enormous space to store the indexes, ultimately slowing down and increasing the cost of serving results. A variety of techniques have been developed to identify pairs of web pages that are “similar”...

A Novel Role-based Access Control Model in Cloud Environments

Jun Luo, Hongjun Wang, Xun Gong, Tianrui Li
Pages: 1 - 9
In Cloud environments, the relationship between resources and users is more ad hoc and dynamic. The role-based access control (RBAC) model is an appropriate access control model for Cloud environments. When using the RBAC model in Cloud environments, some new elements should be considered. This paper...

Bare bones particle swarm optimization with adaptive chaotic jump for feature selection in classification

Chenye Qiu
Pages: 1 - 14
Feature selection (FS) is a crucial data pre-processing process in classification problems. It aims to reduce the dimensionality of the problem by eliminating irrelevant or redundant features while achieve similar or even higher classification accuracy than using all the features. As a variant of particle...

Some Measures Relating Partitions Useful for Computational Intelligence

Ronald R. Yager
Pages: 1 - 18
SOME MEASURES RELATING PARTITIONS USEFUL FOR COMPUTATIONAL INTELLIGENCE We investigate a number of measures relating partitions. One class of measures we consider are congru- ence measures. These measures are used to calculate the similarity between two partitionings. We provide a number of examples...

A Desirability Function-Based Relatively Optimal Interval Core Model and an Algorithm for Fuzzy Profit Allocation Problems of Enterprise Strategy Alliance

Fei Guan, Qiang Zhang
Pages: 1 - 13
Enterprise strategic alliance is a win-win business competition mode that has been developed in both academia and industry. How to allocate total profit fairly in an uncertain environment, however, is an important factor affecting the stability of the strategic alliance. To handle this problem, this...

Motion Deblurring for Single Photograph Based on Particle Swarm Optimization

Jing Wei, Zhao Hai, Song Chunhe, Zhu Hongbo
Pages: 1 - 11
This paper addresses the issue of non-uniform motion deblurring for a single photograph. The main difficulty of spatially variant motion deblurring is that, the deconvolution algorithm can not directly be used to estimate blur kernel, due to the kernel of different pixels are different with each other....

NIP - An Imperfection Processor to Data Mining datasets

JoséM. Cadenas, M. Carmen Garrido, Raquel Martínez
Pages: 3 - 17
Every day there are more techniques that can work with low quality data. As a result, issues related to data quality have become more crucial and have consumed a majority of the time and budget of data mining projects. One problem for researchers is the lack of low quality data in order to test their...

Feature Selection for Multi-label Learning: A Systematic Literature Review and Some Experimental Evaluations

Newton Spolaôr, Huei Diana Lee, Weber Shoity Resende Takaki, Feng Chung Wu
Pages: 3 - 15
Feature selection can remove non-important features from the data and promote better classifiers. This task, when applied to multi-label data where each instance is associated with a set of labels, supports emerging applications. Although multi-label data usually exhibit label relations, label dependence...

A Comprehensive Literature Review of 50 Years of Fuzzy Set Theory

Cengiz Kahraman, Basar Öztaysi, Sezi Cevik Onar
Pages: 3 - 24
Fuzzy sets have a great progress in every scientific research area. It found many application areas in both theoretical and practical studies from engineering area to arts and humanities, from computer science to health sciences, and from life sciences to physical sciences. In this paper, a comprehensive...

A joint optimization strategy for scale-based product family positioning

Yangjian Ji, Tianyin Tang, Chunyang Yu, Guoning Qi
Pages: 3 - 14
With the development of modern technologies and global manufacturing, it becomes more difficult for companies to distinguish themselves from their competitors. In order to keep their competitive advantages, companies must properly position their product families by offering a right product portfolio...

Adaptive Input Selection and Evolving Neural Fuzzy Networks Modeling

Alisson Marques Silva, Walmir Caminhas, Andre Lemos, Fernando Gomide
Pages: 3 - 14
This paper suggests an evolving approach to develop neural fuzzy networks for system modeling. The approach uses an incremental learning procedure to simultaneously select the model inputs, to choose the neural network structure, and to update the network weights. models with larger and smaller number...

Implicit parameter estimation for conditional Gaussian Bayesian networks

Aida Jarraya, Philippe Leray, Afif Masmoudi
Pages: 6 - 17
The Bayesian estimation of the conditional Gaussian parameter needs to define several a priori parameters. The proposed approach is free from this definition of priors. We use the Implicit estimation method for learning from observations without a prior knowledge. We illustrate the interest of such an...

Fuzzy Specification in Real Estate Market Decision Making

Victoria Lopez, Matilde Santos, Javier Montero
Pages: 8 - 20
In this paper we present a software tool designed as a decision aid system for all actors being involved when buying or selling real state, client and realtor, where a main objective for the commercial is to concentrate the client preferences into few alternatives. Since the required previous analysis...

Cardinal, Median Value, Variance and Covariance of Exponential Fuzzy Numbers with Shape Function and its Applications in Ranking Fuzzy Numbers

S. Rezvani
Pages: 10 - 24
In this paper, the researcher proposed a method to cardinal, median value, variance and covariance of exponential fuzzy numbers with shape function . The covariance used in this method is obtained from the exponential trapezoidal fuzzy number, first by finding mathematical expectation and then calculating...

Reduct Driven Pattern Extraction from Clusters

Shuchita Upadhyaya, Alka Arora, Rajni Jain
Pages: 10 - 16
Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern. From data mining perspective, pattern learning from clusters is as important as cluster...

A DC programming approach for feature selection in the Minimax Probability Machine

Liming Yang, Ribo Ju
Pages: 12 - 24
This paper presents a new feature selection framework based on the -norm, in which data are summarized by their moments of the class conditional densities. However, discontinuity of the -norm makes it difficult to find the optimal solution. We apply a proper approximation of the -norm and a bound on...

Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering

Pawan Lingras, Manish Joshi
Pages: 12 - 28
Researchers have proposed several Genetic Algorithm (GA) based crisp clustering algorithms. Rough clustering based on Genetic Algorithms, Kohonen Self-Organizing Maps, K-means algorithm are also reported in literature. Recently, researchers have combined GAs with iterative rough clustering algorithms...

Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks

Jalal Sadoon Hameed Al-bayati, Burak Berk Üstündağ
Pages: 12 - 23
Apple leaf disease is the foremost factor that restricts apple yield and quality. Usually, much time is taken for disease detection with the existing diagnostic techniques; therefore, farmers frequently miss the best time for preventing and treating diseases. The detection of apple leaf diseases is a...


Ebru Turanoğlu, İhsan Kaya, Cengiz Kahraman
Pages: 13 - 29
Acceptance sampling is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. The parameters of acceptance sampling plans are sample sizes and acceptance numbers. In some cases,...

Germinal Center Optimization Algorithm

Carlos Villaseñor, Nancy Arana-Daniel, Alma Y. Alanis, Carlos López-Franco, Esteban A. Hernandez-Vargas
Pages: 13 - 27
Artificial immune systems are metaheuristic algorithms that mimic the adaptive capabilities of the immune system of vertebrates. Since the 1990s, they have become one of the main branches of computer intelligence. However, there are still many competitive processes in the biological phenomena that can...

FISDeT: Fuzzy Inference System Development Tool

Giovanna Castellano, Ciro Castiello, Vincenzo Pasquadibisceglie, Gianluca Zaza
Pages: 13 - 22
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...

A generalization of the Perona-Malik anisotropic diffusion method using restricted dissimilarity functions

C. Lopez-Molina, B. De Baets, J. Cerron, M. Galar, H. Bustince
Pages: 14 - 28
There exists a large number of techniques for content-aware smoothing. Despite its simplicity, the Perona-Malik Anisotropic Diffusion method is among the most employed ones. In this work we study this method in detail and propose a generalization of its diffusion scheme using restricted dissimilarity...

Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making

Hai Wang
Pages: 14 - 33
Group decision making problems which organize a group of experts to evaluate a set of alternatives with respect to several criteria are commonly discussed recently. Hesitant fuzzy linguistic term sets, characterized by a set of consecutive linguistic terms, act as a new model for qualitative settings...

A simulation study of outpatient scheduling with multiple providers and a single device

Xiao-Dan Wu, Mohammad T. Khasawneh, Dian-Min Yue, Ya-Nan Chu, Zhan-Ting Gao
Pages: 15 - 25
Effective outpatient appointment scheduling aims at reducing patient waiting time and operational costs, and improving resource utilization, especially given the stochastic nature of patient arrivals. Unlike many western developed countries, China faces challenges due to imperfect appointment systems...

Forecasting Direction of Trend of a Group of Analogous Time Series Using F-Transform and Fuzzy Natural Logic

Vilém Novák, Irina Perfilieva
Pages: 15 - 28
We present an idea to group time series according to similarity of their local trends and to predict future direction of the trend of all of them on the basis of forecast of only one representative. First, we assign to each time series an adjoint one, which consists of a sequence of the F1-transform...

A Multiple Attribute Decision Making Approach Based on New Similarity Measures of Interval-valued Hesitant Fuzzy Sets

Yi Liu, Jun Liu, Zhiyong Hong
Pages: 15 - 32
Hesitant fuzzy sets, as an extension of fuzzy sets to deal with uncertainty, have attracted much attention since its introduction, in both theory and application aspects. The present work is focused on the interval-valued hesitant fuzzy sets (IVHFSs) to manage additional uncertainty. Now that distance...

Gray Scale Edge Detection using Interval-Valued Fuzzy Relations

Agustina Bouchet, Pelayo Quirós, Pedro Alonso, Virginia Ballarin, Irene Díaz, Susana Montes
Pages: 16 - 27
Gray scale edge detection can be modeled using Fuzzy Sets and, in particular, Interval-Valued Fuzzy Sets. This work is focused on studying the performance of several Interval-Valued Fuzzy Sets construction methods for detecting edges in a gray scale image. These construction methods are based on considering...

Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis

Xin Xu, Rob Law, Tao Wu
Pages: 17 - 26
The significant economic contributions of the tourism industry in recent years impose an unprecedented force for data mining and machine learning methods to analyze tourism data. The intrinsic problems of raw data in tourism are largely related to the complexity, noise and nonlinearity in the data that...