• Structural Engineering and Mechanics
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• v.55 no.3
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• pp.525-534
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• 2015

A new structural dynamic fuzzy reliability analysis under stochastic loads which are applied several times is proposed in this paper. The fuzzy reliability prediction models based on time responses with and without strength degeneration are established using the stress-strength interference theory. The random loads are applied several times and fuzzy structural strength is analyzed. The efficiency of the proposed method is demonstrated numerically through an example. The results have shown that the proposed method is practicable, feasible and gives a reasonably accurate prediction. The analysis shows that the probabilistic reliability is a special case of fuzzy reliability and fuzzy reliability of structural strength without degeneration is also a special case of fuzzy reliability with structural strength degeneration.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• Journal of the Korea institute for structural maintenance and inspection
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• v.2 no.2
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• pp.151-161
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• 1998

In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of RC highway bridge, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of visual inspection and extensive field load tests are applied to the integrity assessment of a new RC highway bridge, namely, Jichok bridge.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.107-117
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• 1992

Conventional fault tree analysis has several problems as the estimations and tolerances of the failure probability values. To overcome these problems, fuzzy concepts with natural language can be applied to conventional fault tree analysis. And, we propose the evaluation method of the imprecision of top/basic events and possibility importances of basic events.

• Journal of the Korean Society for Railway
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• v.9 no.4 s.35
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• pp.432-440
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• 2006

Prior to the service evaluation, many kinds of its attributes must be identified on the basis of rational decision owing to complexity and ambiguity inherent in logistics service. there are so many evaluation methods but they are not applicable to logistics service the have property of non-additivity and overlapped attributes. Therefore, probability measure can not used to evaluate logistics service but Fuzzy Measure is required. And the method should be easy to calculate it Recently Fuzzy theory has been applied in Various evaluation problem. Fuzzy evaluation based on Fuzzy theory can accommodate fuzziness in judgement with people through introducing Fuzzy Measure. In this paper, Hierarchical Fuzzy Process is applied to evaluate level of logistics service in Korail and the biggest six logistics companies in the korea which is called 3PL Company. Also Fuzzy Relation Equation which is problem identifying evaluation value at these fuzzy evaluation is applied to verify relation between Input and Output data through @-operation. Therefore, we apply this Fuzzy Relation Equation to Hierarchical Fuzzy Process and verify evaluation value which objects of evaluation are able to possess.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.492-500
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• 2003

By means of the transformation from the problem of fuzzy reliability to the problem of general reliability, a model for analyzing fuzzy reliability is introduced in this paper Because of the complexity of the Problem of the fuzzy reliability, generally speaking, the analytical equations for calculating fuzzy reliability indexes of machine part cannot be obtained in most cases. Therefore, in this paper, an approach is given wherein progressions are employed to calculate them, or a simulation approach is used to estimate them by expressing general reliability indexes as progressions. By utilizing the approach put forwards in the paper, the calculating quantity for analyzing the fuzzy reliability will be reduced : even substantially reduced sometimes. Some examples are taken to explain the feasibility of the model and a simulation approach.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.91-97
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• 2002

Let (X, F, g) be a fuzzy measure space. Then for any h$\in$ $L^{0}$ (X) , a$\in$[0 , 1] , and $A\in$F ∫$_{A}$aㆍh($\chi$)┬g＝aㆍ∫$_{A}$h($\chi$)┬g with the t-seminorm ┬(x, y)= xy. And we prove that the Seminormed fuzzy integral has some linearity properties only for ｛0,1｝-classes of fuzzy measure as follow, For any f, h$\in$ $L^{0}$ ($\chi$), any a, b$\in$R+: af＋bh$\in$ $L^{0}$ ($\chi$)⇒ ∫$_{A}$(af＋bh)┬g＝a∫$_{A}$f┬g＋b∫$_{A}$h┬g; if and only if g is a probability measure fulfilling g(A) $\in$｛0, 1｝ for all $A\in$F.n$F.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.763-771
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• 2008

Uncertainties are pervasive in engineering geological problems. Therefore, the presence of uncertainties and their significance in analysis and design of slopes have been recognized. Since the uncertainties cannot be taken into account by the conventional deterministic approaches in slope stability analysis, the probabilistic analysis has been considered as the primary tool for representing uncertainties in mathematical models. However, some uncertainties are caused by incomplete information due to lack of information, and those uncertainties cannot be handled appropriately by the probabilistic approach. For those uncertainties, the theory of fuzzy sets is more appropriate. Therefore, in this study, fuzzy reliability analysis has been proposed in order to deal with the uncertainties which cannot be quantified in the probabilistic analysis due to the limited information. For the practical example, a slope is selected in this study and both the probabilistic analysis and the fuzzy reliability analysis have been carried out for planar failure. In the fuzzy reliability analysis, the dip angle and internal friction angle of discontinuity are considered as triangular fuzzy numbers since the random properties of the variables cannot be obtained completely under the conditions of limited information. In the study, the fuzzy reliability index and the probabilities of failure are evaluated from fuzzy arithmetic and compared to those from the probabilistic approach using Monte Carlo simulation and point estimate method. The analysis results show that the fuzzy reliability analysis is more appropriate for the condition that the uncertainties arise due to incomplete information.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1591-1601
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• 2004

Clustering, a technique for the analysis of the genes, organizes the patterns into groups by the similarity of the dataset and has been used for identifying the functions of the genes in the cluster or analyzing the functions of unknown gones. Since the genes usually belong to multiple functional families, fuzzy clustering methods are more appropriate than the conventional hard clustering methods which assign a sample to a group. In this paper, a Bayesian validation method is proposed to evaluate the fuzzy partitions effectively. Bayesian validation method is a probability-based approach, selecting a fuzzy partition with the largest posterior probability given the dataset. At first, the proposed Bayesian validation method is compared to the 4 representative conventional fuzzy cluster validity measures in 4 well-known datasets where foray c-means algorithm is used. Then, we have analyzed the results of Saccharomyces cell cycle expression data evaluated by the proposed method.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.128-130
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• 1995

This paper presents the optimal operation scheduling on cogeneration systems connected with auxiliary equipment by using the possibility fuzzy theory. The probability fuzzy theory is a method to obtain the possibility of the solution from the fuzzification of coefficients. Simulation is carried out to obtain the boundary of heat production in each time interval. Simulation results shows effectively the flexible operation boundary to establish operation scheduling.