Journal of Intelligent & Fuzzy Systems - Volume 30, issue 4

Authors: Ma, Nana | Zhao, Bin

Article Type: Research Article

Abstract: In this paper, based on a complete residuated lattice, we introduce the concept of fuzzy cut-stable maps and discuss the relationship between fuzzy cut-stable maps and some special maps. We also obtain the extension property of fuzzy cut-stable maps. Furthermore, it is proved that the category of fuzzy complete (continuous) lattices with fuzzy complete homomorphisms is a full reflective subcategory of the category of fuzzy (precontinuous) posets with fuzzy cut-stable maps.

Keywords: Fuzzy poset, fuzzy cut-stable map, Dedekind-MacNeille completion, reflective subcategory

DOI: 10.3233/IFS-151990

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2213-2221, 2016

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: Machine tool selection process has been a critical issue for companies for years, since improper selection of a machine tool might cause many problems, affecting negatively the productivity, precision, flexibility and company’s responsive manufacturing capabilities. On the other hand, selecting the best machine tool from its increasing number of existing alternatives in the market is a multiple-criteria decision making (MCDM) problem in the presence of many quantitative and qualitative attributes. Therefore, most companies have utilized various methods to successfully carry out this difficult and time-consuming process. In this paper, both of the most used MCDM methods; the Analytic Network Process …(ANP) and PROMETHEE II (Preference Ranking Organization Method for Enriching Evaluations) with fuzzy logic (F-ANP and F-PROMETHEE II) are integrated to present a performance analysis on machine tool selection problem. The F-ANP method is used to determine the relative weights of a set of multiple quantitative and qualitative criteria, as the F-PROMETHEE II method is utilized to rank competing alternatives in terms of a set of evaluation criteria in order to reach to the final solution. In addition, a case study is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers. Show more

Keywords: Machine tool selection, fuzzy logic, multiple-criteria decision making, analytic network process, PROMETHEE II

DOI: 10.3233/IFS-151991

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2223-2235, 2016

Authors: Deli, Irfan | Çağman, Naim

Article Type: Research Article

Abstract: In this paper, we give a probabilistic equilibrium solution method of two-person soft games (tps-games). This method can overcome the problem that could not be solved by soft saddle points, soft lower and soft upper values, soft dominated strategies and soft Nash equilibrium. We also prove that every finite tps -game with probabilistic strategies has at least one solution for at least one player. Finally, we give a numerical example which shows that the method can be successfully applied to the game theory.

Keywords: Soft sets, soft games, impact values, probabilistic equilibrium, probabilistic solution methods

DOI: 10.3233/IFS-151992

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2237-2244, 2016

Authors: Huang, Ko-Wei | Chen, Jui-Le | Yang, Chu-Sing | Tsai, Chun-Wei

Article Type: Research Article

Abstract: The DNA fragment assembly (DFA) problem is among the most critical problems in computational biology. Being NP-hard, it can be efficiently solved via meta-heuristic algorithms, such as the gravitation search algorithm (GSA). GSA is a state-of-the-art swarm-based algorithm particularly suitable for solving NP-hard combinatorial optimization problems. This paper proposes a new memetic GSA algorithm called MGSA. MGSA is a type of overlap-layout-consensus model that is based on tabu search for population initialization. In order to increase the diversity of MGSA, we adapted two operator time-varying maximum velocities in the GSA procedure. Finally we also adapted the simulated annealing-based variable neighborhood …search (SA-VNS) to find superior precise solutions. The proposed MGSA algorithm was verified with 19 DNA fragments based on seeking to maximize the overlap score measurements. In comparing the performances of the proposed MGSA and state-of-the-art algorithms, the simulation results demonstrate that the MGSA can achieve the best overlap scores. Show more

Keywords: Gravitation search algorithm, DNA sequence fragment assembly, meta-heuristic algorithm, memetic algorithm

DOI: 10.3233/IFS-151994

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2245-2255, 2016

Authors: Zhou, Lintao | Sun, Kaibiao | Li, Hongxing

Article Type: Research Article

Abstract: In this paper, a new method for the representation of concept in factor space by using type-2 fuzzy sets, and the composition method of states of factors is developed. A general model of multifactorial decision making based on type-2 fuzzy sets is formulated, and the comprehensive evaluation problem based on type-2 fuzzy sets is analyzed. Finally, two applied instances are given to demonstrate the effectiveness of the proposed methods.

Keywords: Factor space, type-2 fuzzy sets, multifactorial decision making, comprehensive evaluation

DOI: 10.3233/IFS-151995

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2257-2266, 2016

Authors: Hosseini, E. | Jafarian, A.

Article Type: Research Article

Abstract: Artificial neural networks modeling is one of the most prominent techniques for solving more complicated mathematical problems that can not be solved in the traditional computing environments. The work described here intends to offer an efficient bivariate fuzzy interpolation methodology based on the artificial neural networks approach. It has several notable features including high processing speeds and the ability to learn the solution to a problem from a set of examples which categorizes them in line of intelligent systems. To do this, a multilayer feed-forward neural architecture is depicted for constructing a fully fuzzy interpolating polynomial of arbitrary degree. Then, …a back-propagation supervised learning optimization algorithm will be applied for estimating the unknown fuzzy coefficients of the solution polynomial. Finally, the advantage of our technique is illustrated by using some practical examples to show the ability of the improved algorithm in solving rigorous problems. Show more

Keywords: Bivariate fully fuzzy polynomial, artificial neural network, approximate solution, criterion function, learning algorithm

DOI: 10.3233/IFS-151996

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2267-2275, 2016

Authors: Liu, Han | Gegov, Alexander | Cocea, Mihaela

Article Type: Research Article

Abstract: Due to the vast and rapid increase in data, data mining has become an increasingly important tool for the purpose of knowledge discovery in order to prevent the presence of rich data but poor knowledge. Data mining tasks can be undertaken in two ways, namely, manual walkthrough of data and use of machine learning approaches. Due to the presence of big data, machine learning has thus become a powerful tool to do data mining in intelligent ways. A popular approach of machine learning is inductive learning, which can be used to generate a rule set (a set of rules) using …a particular algorithm. Inductive learning can involve a single base algorithm learning from a single data set following a standard learning approach. In this approach, the learning algorithm can generate a single rule set such as decision trees. On the other hand, the inductive learning can also involve a single base algorithm learning from multiple data sets following an ensemble learning approach. In this approach, the learning algorithm can generate multiple rule sets such as random forests. The latter approach is usually designed to reduce overfitting of models that usually arises when the former approach is adopted. In this context, the ensemble learning approach usually enables the improvement of the overall accuracy in prediction. The aim of this paper is to introduce a new approach of ensemble learning called Collaborative Rule Generation. In the new approach, the inductive learning involves multiple base algorithms learning from a single data set to generate a single rule set, which aims to enable each rule to have a higher quality. This paper also includes an experimental study validating the Collaborative Rule Generation approach and discusses the results in both quantitative and qualitative ways. Show more

Keywords: Data mining, machine learning, ensemble learning, rule based systems, rule based classification, if-then rules

DOI: 10.3233/IFS-151997

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2277-2287, 2016

Authors: Yang, Weifeng | Xia, Xiaohong | Pan, Baoliu | Gu, Chunsheng | Yue, Jiangang

Article Type: Research Article

Abstract: Taking the geological conditions of a typical coal mine as an example, a fuzzy comprehensive estimation model is developed for judgment of mine water and sand inrush caused by underground mining. According to the geological prototype, three basic conditions of water and sand inrush disaster induced by mining under thin bedrock and thick loose aquifer are revealed. Using analytic hierarchy process (AHP) to determine the weights of evaluation index factors, nine evaluation factors are chosen, and then the degree of membership of evaluation factors is determined through qualitative and quantitative two ways. The dangers of water and sand inrush in …the study area are quantitatively analyzed. The risks are divided into four ranks, through calculating, the hazard level of water and sand inrush disaster in study area is 3, it is high risk. The fuzzy system is efficient and easy to use, and the evaluation results are in good accordance with the reality, and provide the decision basis for the safety production of the coal mine. Show more

Keywords: Fuzzy comprehensive evaluation, mine water and sand inrush, analytic hierarchy process, evaluation index factor

DOI: 10.3233/IFS-151998

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2289-2295, 2016

Authors: Mondal, Sanjib | Pal, Madhumangal

Article Type: Research Article

Abstract: Eigenvalues and eigenvectors are one of the important topics over bipolar fuzzy linear algebra. In order to develop the bipolar fuzzy linear space we introduce in this article, the similarity relations, eigenvalues and eigenvectors of bipolar fuzzy matrices (BFMs). Idempotent, diagonally dominant and spectral radius of BFMs are considered here. Also, some properties and results of eigenvalues and eigenvectors for BFMs are investigated.

Keywords: Relation, bipolar fuzzy matrix, vector, eigenvalue, eigenvector, spectral radius

DOI: 10.3233/IFS-152000

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2297-2307, 2016

Authors: Bodaghi, Abasalt

Article Type: Research Article

Abstract: The aim of this article is to extend the applications of a fixed point method to provide the intuitionistic fuzzy versions of Hyers-Ulam stability for the generalized forms of cubic and quartic functional equations. This way shows that the concept of stability is related to some fixed point of a suitable operator.

Keywords: Cubic functional equation, Hyers-Ulam stability, intuitionistic fuzzy normed space, quartic functional equation

DOI: 10.3233/IFS-152001

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 4, pp. 2309-2317, 2016