• Structural Engineering and Mechanics
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• v.25 no.2
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• pp.147-160
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• 2007

In this paper, a dynamic analysis based on the fuzzy set theory is presented as a possible complementary tool to the classical stochastic methods for dynamic analyses. Material parameters of a structure are influenced by uncertainties and therefore they are considered to be fuzzy quantities with given distributions, that means fuzzy numbers with given membership functions. The fuzzy dynamic analysis is conducted with help of fuzzy arithmetic defined on the so-called ${\alpha}$-cuts. The results of the analysis are also obtained in the form of fuzzy numbers, which compared to the stochastic methods is less computationaly expensive while at the same time they still provide information about the distribution of a quantity. This method is demonstrated on an analysis of a two-dimensional frame subjected to possible seismic load, where the uncertain eigenmodes and eigenfrequencies are used in the modal analysis.

• Journal of Information Technology Applications and Management
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• v.19 no.3
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• pp.19-30
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• 2012

Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper is aimed to present a fuzzy decision making approach to deal with the material selection in engineering design problems. A fuzzy multi criteria decision-making model is proposed for solving the material selection problem. The proposed model makes use of fuzzy TOPSIS (Technique for Order reference by Similarity to Ideal Solution) with trapezoidal numbers for evaluating the criteria and ranking the alternatives. And result is compared with fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multi criteria Optimisation and Compromise Solution) which is proposed by Jeya Girubha and Vinodh [2012]. The present paper is aimed to also improve literature of fuzzy decision making for material selection problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.85-89
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• 2007

Many authors considered the computational aspect of sup-min convolution when applied to weighted average operations. They used a computational algorithm based on a-cut representation of fuzzy sets, nonlinear programming implementation of the extension principle, and interval analysis. It is well known that $T_W$(the weakest t-norm)-based addition and multiplication preserve the shape of L-R type fuzzy numbers. In this paper, we consider the computational aspect of the extension principle by the use of $T_W$ when the principle is applied to fuzzy weighted average operations. We give the exact solution for the case where variables and coefficients are L-L fuzzy numbers without programming or the aid of computer resources.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.9-15
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• 1998

In this paper, we introduce new results of law large numbers for mutually T-related fuzzy numbers, when T is Archimedean t-norm and spreads are random variables, and generalize earlier result of Fullr[FSS 45(1992) 299-303].

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.231-236
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• 2003

Recently, Oussalah 〔Fuzzy Sets and Systems 128(2002) 247-260〕 investigated some theoretical results about some invariance properties concerning the relationships between the defuzzification outcomes and the arithmetic of fuzzy numbers. But, in this note we introduce some explicit calculations of the resulting fuzzy set or possibility distribution when the matter is the determination of the defuzzified value pertaining to the result of some manipulation of fuzzy quantities under t-norm based fuzzy arithmetic operations.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.607-617
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• 1996

This paper shows that fuzzy set theory can be useful in modeling and solving job scheduling problems with uncertain processing times. The processing times are considered as fuzzy numbers(fuzzy intervals or time intervals) and the fuzzy Delphi method is used to estimate a reliable time interval of each processing time. Based on these time estimates, we then propose an efficient methodology for calculating the optimal sequence and the fuzzy makespan.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.115-124
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• 2004

This paper presents a weighted fuzzy backward reasoning algorithm for rule-based systems based on weighted fuzzy Petri nets. The fuzzy production rules in the knowledge base of a rule-based system are modeled by weighted fuzzy Petri nets, where the truth values of the propositions appearing in the fuzzy production rules and the certainty factors of the rules are represented by fuzzy numbers. Furthermore, the weights of the propositions appearing in the rules are also represented by fuzzy numbers. The proposed weighted fuzzy backward reasoning generates the backward reasoning path from the goal node to the initial nodes and then evaluates the certainty factor of the goal node. The algorithm we proposed can allow the rule-based systems to perform weighted fuzzy backward reasoning in more flexible and human-like manner.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.94-104
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• 2004

This paper proposed a new method to evaluate service quality attribute of perceived service quality in public sectors, using triangle fuzzy numbers and hamming distance. Our method measured the ratio of the expected and perceived service for the customers' perceived service quality. By using fuzzy numbers, This method not only overcomes linguistic variable problems but also provides more objective and direct information for service quality attributes. The discrepancy rate between expected service and perceived service that is perceived service quality is evaluated by hamming distance. To evaluate the discrepancy rate from hamming distance, we induced general solutions to compute the intersection area between two triangle fuzzy numbers and the weak or strong attributes in public sectors are clarified.

• Advances in Computational Design
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• v.2 no.1
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• pp.29-42
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• 2017

This study presents algorithms for determining the fuzzy critical loads of planar steel frame structures with fixity factors of beam - column and column - base connections are modeled as triangular fuzzy numbers. The finite element method with linear elastic semi-rigid connection and Response Surface Method (RSM) in mathematical statistic are applied for problems with symmetric triangular fuzzy numbers. The ${\alpha}$ - level optimization using the Differential Evolution (DE) involving integrated finite element modeling is proposed to apply for problems with any triangular fuzzy numbers. The advantage of the proposed methodologies is demonstrated through some example problems relating to for the twenty - story, four - bay planar steel frames.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.383-386
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• 1993

In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.