Journal of Intelligent & Fuzzy Systems - Volume 25, issue 3

Authors: La Scalia, Giada

Article Type: Research Article

Abstract: This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The job processing times are formulated by triangular fuzzy membership functions using their statistical distributions. This study proposes to solve a Fuzzy Binary Linear Problem (FBLP) with fuzzy coefficients in the objective function and in a constraint. Finally, the effect of …the unbalancing of a station in a real case study has been investigated in order to consider different scenarios. In particular, four different scenarios were studied considering the balanced and unbalanced line with deterministic and stochastic job processing times. The results obtained showed that the use of a fuzzy approach allows to take in account the effect of the job processing time variability demonstrating the validity of the proposed model. Show more

Keywords: Fuzzy binary linear programming, assembly line balancing problem

DOI: 10.3233/IFS-120656

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 517-524, 2013

Authors: Akbari, Mohammad Ghasem | Arefi, Mohsen

Article Type: Research Article

Abstract: A nonparametric approach for testing statistical hypotheses based on intuitionistic fuzzy data is presented. According to the proposed approach, first, a confidence interval based on intuitionistic fuzzy data is defined, which are then used to make a procedure for testing statistical hypotheses. To evaluate statistical hypotheses, a new criteria, called degree of acceptance (DA), has been proposed.

Keywords: Bootstrap method, degree of acceptance (DA), intuitionistic fuzzy confidence interval, intuitionistic fuzzy number, intuitionistic fuzzy set, Yao-Wu signed distance

DOI: 10.3233/IFS-2012-0657

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 525-534, 2013

Authors: Muhammad, Mustapha | Buyamin, Salinda | Ahmad, Mohamad N. | Nawawi, Sophan W.

Article Type: Research Article

Abstract: A two wheeled inverted pendulum (TWIP) mobile robot is an under-actuated mechanical system, which is inherently open-loop unstable with highly nonlinear dynamics. This property attracts the interest of researchers worldwide in recent years. This paper presents the development of a linearized model of the TWIP mobile robot based on its nonlinear dynamical model using Takagi-Sugeno (T-S) fuzzy modeling technique, which can allow the application of linear control techniques in analyzing and efficiently controlling such under-actuated nonlinear system. The complete nonlinear dynamical equations of motion of the TWIP mobile robot were first derived using Kane's Method. Based on the nonlinear dynamical …equations of motion, a T-S fuzzy model of the TWIP robot was then developed using local approximation technique. To validate the proposed model, simulations study was carried out and the results show that the proposed model approximates the original nonlinear TWIP mobile robot in the pre-specified domains to certain degree of accuracy. Show more

Keywords: Kane's method, mathematical model, Takagi-Sugeno (T-S) fuzzy model, two-wheeled inverted pendulum (TWIP)

DOI: 10.3233/IFS-120658

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 535-546, 2013

Authors: Tadic, Danijela | Gumus, Alev Taskin | Arsovski, Slavko | Aleksic, Aleksandar | Stefanovic, Miladin

Article Type: Research Article

Abstract: There is no defined methodological approach that would rank the quality goals of a process in uncertain environments, which is one of the basic problems in process management. In this paper, the considered problem is stated as a multi-criteria decision problem. The criteria present performances which are defined by the knowledge and experience of the decision makers. The fuzzy rating weights of each pair of the considered criteria and uncertain criteria values for the defined quality goals are described by linguistic expressions which are modeled by triangular fuzzy numbers. The weights vector of criteria is calculated by the fuzzy Analytic …Hierarchical Process (AHP). The extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank quality goals. The proposed model is illustrated by an example. Show more

Keywords: Quality goals of realization process, fuzzy sets, fuzzy TOPSIS, fuzzy AHP

DOI: 10.3233/IFS-120659

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 547-556, 2013

Authors: Kaya, Ersin | Koçer, Barış | Arslan, Ahmet

Article Type: Research Article

Abstract: In this paper, a genetic algorithm-based search method, which builds ideal rule set for fuzzy rule-based classification systems (FRBCSs), is developed. In FRBCSs, ideal rule set means a set of rules which ensure high classification accuracy with small rule count and small rule length. The related studies in the literature point out that rule set grows exponentially with input attribute count. This growth complicates the searching process and lowers the success rate. Through the proposed method, successive results are obtained for datasets with large input attribute counts using a special coding technique. The proposed method is tested for various datasets …and results are compared against the method which uses candidate rule set. Show more

Keywords: Fuzzy rule-based classification, genetic algorithm, generating fuzzy rules

DOI: 10.3233/IFS-120661

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 557-566, 2013

Authors: Wang, Jian-qiang | Li, Kang-jian | Zhang, Hong-yu | Chen, Xiao-hong

Article Type: Research Article

Abstract: In this paper, after analyzing on shortcomings of the existing score functions of intuitionistic fuzzy set (IFS), a new score function based on relative entropy is presented. The risk attitudes of the decision makers are also defined. Examples have been given to show the validity of this score function. Meanwhile, the definition of the intuitionistic normal fuzzy number and their operational laws and intuitionistic normal fuzzy weighted arithmetic averaging operator are proposed. As for the intuitionistic normal fuzzy multi-criteria decision-making problems in which criteria weights remain fixed and the criteria values of alternatives are in the form of intuitionistic normal …fuzzy numbers. An intuitionistic normal fuzzy multi-criteria decision-making approach based on the relative score function is proposed. Finally, an example is provided to show the feasibility and validity of the approach. Show more

Keywords: Intuitionistic fuzzy multi-criteria decision-making, intuitionistic normal fuzzy numbers, relative entropy, score function

DOI: 10.3233/IFS-120662

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 567-576, 2013

Authors: Parchami, Abbas | Mashinchi, Mashaallah

Article Type: Research Article

Abstract: In quality control, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which specification limits are two fuzzy sets. In such a fuzzy environment, the product is not qualified with a two valued Boolean view, but to some degree depending on the quality level of the product and the strictness of the decision maker. This matter can be cause to a justified judgment in decision making on manufacturing processes. The generalized process capability indices $C_{\widetilde{p}}$, $C_{\widetilde{pk}}$ and $C_{\widetilde{pm}}$ can be helpful and necessary for measuring the fuzzy quality in an in-control process. In …this paper, the generalized Taguchi index $C_{\widetilde{pm}}$ is proposed to provide an assessment of the ability of the fuzzy process to be clustered around the target value. Considering fuzzy specification limits we present four approximate 100(1 − γ)% confidence intervals for the generalized process capability index $C_{\widetilde{pm}}$ in this paper. Then, we obtain several fast computable 100(1 − γ)% confidence intervals for $C_{\widetilde{pm}}$, where the fuzzy specification limits are linear, normal or elliptic. An industrial example is given to show the performance of the proposed method. Show more

Keywords: Fuzzy quality, fuzzy limits, Taguchi process capability index, confidence interval

DOI: 10.3233/IFS-120664

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 577-585, 2013

Authors: Hedayati, H.

Article Type: Research Article

Abstract: Following Fuzzy implicative and Boolean filters of R0 -algebras, Inf Sci 171 (2005), 61–71, the notion of normal intuitionistic fuzzy filter of R0 -algebras is introduced. Some methods are created to construct new intuitionistic fuzzy filters. Also some characteristic properties and equivalent conditions of this notion are investigated. Specially, it is shown that under certain conditions, a normal intuitionistic fuzzy filter is two-valued.

Keywords: R$_{\rm 0}$-algebra, filter, (normal) intuitionistic fuzzy filter, maximal intuitionistic fuzzy filter

DOI: 10.3233/IFS-120665

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 587-593, 2013

Authors: Surekha, B. | Rao, D. Hanumantha | Rao, G.K. Mohan | Vundavilli, Pandu R. | Parappagoudar, M.B.

Article Type: Research Article

Abstract: This paper introduces an intelligent system for the prediction of mechanical properties of silica-based resin bonded sand core system. The properties of sand cores, such as tensile strength, compression strength, shear strength and permeability depends upon various process parameters, namely percentage of resin, of hardener, number of strokes and curing time. In the present paper, Mamdani-based fuzzy logic (FL) approach is used to perform forward modeling, in which the outputs are expressed as the functions of input variables. Moreover, the performance of FL system depends on the knowledge base (KB), which consists of rule base and data base. Three different …approaches have been developed in the present work. Manually constructed FL system is developed in the first approach, whereas in approach 2, genetic algorithm (GA) is used to optimize the data base and rule base of FL system developed in Approach 1. On the other hand in Approach 3, automatic evolution of rule is considered along with the use of GA to optimize data base and rule base. It is important to note that the developed fuzzy model uses triangular membership functions for fuzzification and centroid area method for de-fuzzification process. The developed FL system eliminates the need of extensive experimental work in selecting the most influential process parameters. The performances of all three approaches have been tested with the help of twenty test cases. It is to be noted that all three approaches, developed can be effectively used in foundry for making prediction. The results showed that the Approach 3 has outperformed the remaining two, in terms of prediction accuracy. Show more

Keywords: Resin bonded sand core, fuzzy logic, genetic algorithm

DOI: 10.3233/IFS-120666

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 595-604, 2013

Authors: Bellaaj, Hatem | Ketata, Rouf | Chtourou, Mohamed

Article Type: Research Article

Abstract: This paper presents a new approach for fuzzy rule base reduction using similarity concepts and interpolation techniques. The algorithm consists on: First, measure similarity between rules for the best choice of which of them will be deleted. This operation is done without modification of membership functions. Second, if a new input data is presented to the fuzzy system, interpolation techniques will be used to take into account this arriving data. The main idea of this work is to improve accuracy of the fuzzy system after reduction step. A comparative study between three interpolation methods is done. A mathematical case is …treated to show the performance of the proposed method. Show more

Keywords: Fuzzy system, fuzzy rule base reduction, similarity, interpolation

DOI: 10.3233/IFS-120667

Citation: Journal of Intelligent & Fuzzy Systems, vol. 25, no. 3, pp. 605-613, 2013