Journal of Intelligent & Fuzzy Systems - Volume 26, issue 2

Authors: Beheshti, Rahmatollah | Mozayani, Nasser

Article Type: Research Article

Abstract: Holonic multi-agent systems are a special category of multi-agent systems that best fit to environments with numerous agents and high complexity. Like in general multi-agent systems, the agents in the holonic system may negotiate with each other. These systems have their own characteristics and structure, for which a specific negotiation mechanism is required. This mechanism should be simple, fast and operable in real world applications. It would be better to equip negotiators with a learning method which can efficiently use the available information. The learning method should itself be fast, too. Additionally, this mechanism should match the special characteristics of …the holonic multi-agent systems. In this paper, we introduce such a negotiation method. Experimental results demonstrate the efficiency of this new approach. Show more

Keywords: Holonic multi-agent systems, negotiation, semi-cooperative, agreement, regression

DOI: 10.3233/IFS-120757

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 655-666, 2014

Authors: Juang, Yau-Tarng | Yan, Chung-Lin | Huang, Chih-Peng

Article Type: Research Article

Abstract: Based on a fuzzy quadratic Lyapunov function (FQLF), this paper mainly addresses the stability issues of the T-S fuzzy model. Differentiating from existing results with common quadratic Lyapunov functions (CQLF) and leading to stability criteria restricted to finding a common matrix P, this work is based on the FQLF with multiple Pi and expects to attain some less conservative results. Furthermore, the proposed stability criteria will be directly formulated in terms of strict linear matrix inequalities (LMIs), and they thus can readily be evaluated via current LMI solvers. Numerical examples are given to demonstrate the efficiency and the feasibility of …the proposed approach. Show more

Keywords: T-S fuzzy model, linear matrix inequality (LMI), Lyapunov function, fuzzy quadratic Lyapunov function (FQLF)

DOI: 10.3233/IFS-120758

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 667-679, 2014

Authors: Azizipanah-Abarghooee, Rasoul | Narimani, Mohammad Rasoul | Bahmani-Firouzi, Bahman | Niknam, Taher

Article Type: Research Article

Abstract: This paper presents a novel approach to depict Flexible AC Transmission Systems (FACTS) devices effects in power system using multi-objective optimization function. The FACTS devices can play very important roles in power system such as improve power system security, reduce generation cost, decrease transmission loss and improve the voltage stability index. Two more common FACTS devices are the Thyristor Controlled Series Capacitor (TCSC) and Static VAR Compensator (SVC) which can smoothly and rapidly change their apparent reactance and injection power respectively according to the system requirements. Determining the FACTS devices parameters in power system is too complicate and has a …lot of local optima in its search space. In order to overcome above problems a new method, based on SFLA algorithm combined with a new mutation is proposed to increase the efficiency of the SFLA algorithm. Since the proposed problem is a multi-objective problem it is usual to obtain a set of solution instead one solution therefore Pareto method that uses concept of non-dominate solutions is applied to find best compromise solutions. An external repository is considered for saving all non-dominated solution, and also they are sorted by fuzzy set rule to obtain best solutions. For more validation the simulation results are compared with those in other literatures. Show more

Keywords: FACTS devices, fuzzy set, multi-objective optimization, modified SFLA, non-dominated solution

DOI: 10.3233/IFS-120759

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 681-692, 2014

Authors: Ghoseiri, Keivan | Lessan, Javad

Article Type: Research Article

Abstract: The focus of this study was to carry out an evaluation of solid waste disposal site selection in the city Aräk of Iran. Based on published information, different methods have been applied to address this problem, among which Multiple Criteria Decision Analysis (MCDA) has been found to be a fruitful approach. Owing to the imprecision in the objective and subjective factors affecting the problem, for tackling the uncertainty and imprecision in human behavior, in this paper a new fuzzy MCDA approach is applied in an intelligible manner to construct the real decision matrix. Fuzzy Multicriteria Hierarchy Process (FMHP) and ELECTRE …methods are the two successive steps employed to cope with imprecision in the assessment of the criteria and alternatives to select the best site. Given a fuzzy judgment matrix, FMHP produces a real decision matrix that is applied as an input for ELECTRE to build outranking relations among the actions. The integration of FMHP and ELECTRE considers both the fuzziness and partiality of the factors affecting site selection problem into account and avoids compensatory offsets between several criteria with weak and strong values. Finally, the conducted sensitivity analysis indicates the effectiveness of the proposed method as an instrumented decision support model. Show more

Keywords: Waste management, site selection, multiple attributes decision analysis, fuzzy pairwise comparison, fuzzy weights

DOI: 10.3233/IFS-120760

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 693-704, 2014

Authors: Ramathilaga, S. | Jiunn-Yin Leu, James | Huang, Kuo-Kuang | Huang, Yueh-Min

Article Type: Research Article

Abstract: In recent years, various data analysis techniques have been developed for extracting meaningful information from real-world data clustering problems. The results, running time, and clustering validity of the techniques are very important. During few decades, fuzzy clustering algorithms and especially the fuzzy c-means (FCM) algorithm has been widely utilized for solving data clustering problems. The fuzzy c-means algorithm (FCM) can perform well when applied to noise-free datasets, but performs somewhat poorly when applied to data that have been corrupted with noise, mainly because of the use of the non-robust objective function of FCM and the typical Euclidean distance measure of …similarity or dissimilarity. To overcome these shortcomings, this work establishes effective objective functions of fuzzy c-means with the center learning method-based quadratic mean distance, entropy methods, and regularization terms. The effective membership function is derived and center updating by optimizing the proposed effective methods. This work introduces a center learning method to reduce the computational complexity and running time. Also, the proposed methods are applied to artificial data, checkerboard, and real-world datasets to evaluate their performance. The silhouette method is used to find the clustering accuracy of the proposed methods with those of other clustering methods. The experimental results reveal the advantages of the proposed clustering for application to real datasets and random data. They also reveal that the proposed methods outperform the other methods. Show more

Keywords: Fuzzy clustering, image processing

DOI: 10.3233/IFS-120761

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 705-719, 2014

Authors: Jin, Cong | Jin, Shu-Wei

Article Type: Research Article

Abstract: Software fault-prone prediction is one of the active areas of software engineering. It plays a very important role in the analysis of software quality and balance of software cost. Practically, the identification of a module's fault-prone is very important for minimizing cost and improving the effectiveness of the software development process. Software fault-prone prediction helps us to develop dependable software. How to obtain the correlation between software metrics and module's fault-prone, hiding in the observed metrics data, has been focused by many researches. In this paper, we propose the use of a fuzzy integral (FI) for this purpose. FI offers …significant advantages over other approaches due to its ability to naturally represent qualitative characteristic of software fault-prone. Proposed approach was applied on Chidamber-Kemerer (CK) metrics and two datasets of NASA Metrics Data Program from PROMISE repository. Experiments results confirm that proposed approach is very effective for establishing relationship between software metrics and fault-prone. Its implementation doesn't require expert's knowledge. Proposed approach can give useful results for software project managers. Show more

Keywords: Software fault-prone, prediction, fuzzy integral, software metrics

DOI: 10.3233/IFS-120762

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 721-729, 2014

Authors: Kotsiantis, Sotiris

Article Type: Research Article

Abstract: Many data analysis problems involve an investigation of relationships between attributes in heterogeneous databases, where different prediction models can be more appropriate for different regions. We propose a technique of integrating global and local random subspace ensemble. We performed a comparison with other well known combining methods on standard benchmark datasets and the proposed technique gave better accuracy.

Keywords: Ensemble of classifiers, random subspace, combining classifiers

DOI: 10.3233/IFS-120763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 731-739, 2014

Authors: Mhalla, A. | Collart Dutilleul, S. | Craye, E. | Benrejeb, M.

Article Type: Research Article

Abstract: In conventional fault tree analysis, probabilities of the basic events were treated as precise values; sometimes this probability does not correspond to real situations of systems because of ambiguity and the imprecision of some basic events. In order to overcome this disadvantage, a new fuzzy probabilistic method, based on the fuzzy set theory and the Buckley approach, is used in the fault tree analysis for quantifying the basic event uncertainty. According to failure modes, a fault tree of a milk manufacturing unit is constructed. Failure in the milk manufacturing workshop is analysed using the proposed method.

Keywords: Failure rates, fuzzy probabilities, milk production unit, fault tree, uncertainty, diagnosis, maximum time constraints

DOI: 10.3233/IFS-130764

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 741-750, 2014

Authors: Liu, F.-B. | Hu, C.-F.

Article Type: Research Article

Abstract: Diophantine equations have played an important role in many applications of optimization and decision making problems. This work considers solving the system of fuzzy Diophantine equations by using the concept of level sets. It is shown that the system of fuzzy Diophantine equations with concave membership functions can be reduced to a regular convex integer programming problem. A modified p-th power Lagrangian method is introduced to deal with the resulting convex integer programming problem as a sequence of linearly constrained convex integer programming problems. The numerical example included not only illustrates the complete solution process but also specifies parameter values …used in the actual implementation. Show more

Keywords: Diophantine equations, fuzzy optimization, integer programming

DOI: 10.3233/IFS-130765

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 751-758, 2014

Authors: Susitra, D. | Paramasivam, S.

Article Type: Research Article

Abstract: A Non-linear flux linkage model of a Switched reluctance Machine (SRM) has been developed using two different real time applicable modelling techniques and presented in this paper. The techniques are based on Multivariate nonlinear regression (MVNLR) and adaptive neuro fuzzy inference system (ANFIS). The best features of MVNLR and ANFIS are utilized in this research to develop the computationally efficient flux linkage model for SRM. Mathematical models for the phase flux linkage ψ(i, θ) using MVNLR and ANFIS have been successfully arrived, tested and presented for various values of phase currents (Iph) and rotor positions (θ) of a non linear …SRM. It is observed that MVNLR and ANFIS are highly suitable for flux linkage ψ(i, θ) modelling of SRM which is tested to be in good agreement with the training data used for modelling. Show more

Keywords: Non-linear flux linkage model, multivariate non-linear regression technique (MVNLRT), adaptive neuro-fuzzy inference system (ANFIS), switched reluctance machine (SRM)

DOI: 10.3233/IFS-130766

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 759-768, 2014