• Title/Summary/Keyword: Fuzzy Index

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Evaluation of the Probability of Failure in Rock Slope Using Fuzzy Reliability Analysis (퍼지신뢰도(fuzzy reliability) 해석기법을 이용한 암반사면의 파괴확률 산정)

  • Park, Hyuck-Jin
    • 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.

The Fuzzy Power Function of a Test (검정에 관한 퍼지 검정력 함수의 성질)

  • Gang, Man-Gi;Jeong, Ji-Yeong;Park, Yeong-Rye;Choe, Gyu-Tak
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.183-186
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    • 2007
  • We introduction some properties for fuzzy power function of performance of a test. First we define fuzzy type I error and type II error for the probability of the two types of error. And we show that an fuzzy error probability of one kind can only be reduced at cost of increasing the other fuzzy error probability.

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Fuzzy Reliability Analysis Models for Maintenance of Bridge Structure Systems (교량구조시스템의 유지관리를 위한 퍼지 신뢰성해석 모델)

  • 김종길;손용우;이증빈;이채규;안영기
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.10a
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    • pp.103-114
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    • 2003
  • This paper aims to propose a method that helps maintenance engineers to evaluate the damage states of bridge structure systems by using a Fuzzy Fault Tree Analysis. It may be stated that Fuzzy Fault Tree Analysis may be very useful for the systematic and rational fuzzy reliability assessment for real bridge structure systems problems because the approach is able to effectively deal with all the related bridge structural element damages in terms of the linguistic variables that incorporate systematically experts experiences and subjective judgement. This paper considers these uncertainties by providing a fuzzy reliability-based framework and shows that the identification of the optimum maintenance scenario is a straightforward process. This is achieved by using a computer program for LIFETIME. This program can consider the effects of various types of actions on the fuzzy reliability index profile of a deteriorating structures. Only the effect of maintenance interventions is considered in this study. However. any environmental or mechanical action affecting the fuzzy reliability index profile can be considered in LIFETIME. Numerical examples of deteriorating bridges are presented to illustrate the capability of the proposed approach. Further development and implementation of this approach are recommended for future research.

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Study of Seismic Resistance Performance Evaluation Method for Existing Mid-Low Story RC Structure Buildings by Applying Fuzzy Theory (퍼지이론을 적용한 기존 중저층 철근콘크리트 건축물의 내진성능평가기법 연구)

  • Kim, Dong-Hee;Kim, Hyun-Su
    • Journal of Korean Association for Spatial Structures
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    • v.17 no.2
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    • pp.53-62
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    • 2017
  • This study aims to establish a seismic resistance performance evaluation method that makes sure to secure the seismic resistance performance of the existing mid-low story reinforced concrete structures. This study focuses on the development of the seismic resistance performance evaluation method for the overall seismic resistance performance evaluation on the buildings by applying fuzzy theory. This seismic resistance performance evaluation method considers the mutual relations among the type of force, the type of member, the type of story, and the states of deterioration of the buildings. The total seismic resistance performance index from this method was calculated by the intensity weight of each evaluation item, fuzzy measure, fuzzy integration. Moreover, the evaluation methodology was established in this study to identify the performance level of the Immediate Occupancy, Life Safe, Collapse Prevention by applying the fuzzy theory.

A Novel Line Stability Index for Voltage Stability Analysis and Contingency Ranking in Power System Using Fuzzy Based Load Flow

  • Kanimozhi, R.;Selvi, K.
    • Journal of Electrical Engineering and Technology
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    • v.8 no.4
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    • pp.694-703
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    • 2013
  • In electric power system, the line stability indices adopted in most of the instances laid stress on variation of reactive power than real power variation of the transmission line. In this paper, a proposal is made with the formulation of a New Voltage Stability Index (NVSI) which originates from the equation of a two bus network, neglecting the resistance of transmission line, resulting in appreciable variations in both real and reactive loading. The efficacy of the index and fuzzy based load flow are validated with IEEE 30 bus and Tamil Nadu Electricity Board (TNEB) 69 bus system, a practical system in India. The results could prove that the identification of weak bus and critical line in both systems is effectively done. The weak area of the practical system and the contingency ranking with overloading either line or generator outages are found by conducting contingency analysis using NVSI.

An Improved Method of Method of Fuzzy Approximate Reasoning by Combining Self-Organizing Feature Map and Fuzzy Logic (자기조직화 특성지도와 퍼지로직을 결합한 개선된 형태의 퍼지근사추론에 관한 연구)

  • 이건창;조형래
    • Journal of the Korean Operations Research and Management Science Society
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    • v.23 no.1
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    • pp.143-159
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    • 1998
  • This paper proposes a new type of fuzzy approximate reasoning method that combines a self organizing feature map and a fuzzy logic. Previous methods considered only input part to determine the number of fuzzy rules, while this paper considers both input and output parts simultaneously. Our approach proved to improve the inference performance. We also developed a new index for avoiding overlearning which guarantees more accurate results. Experimental results showed that our approach surpasses the performance of Takagi & Hayashi (1991) approach.

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VS-FCM: Validity-guided Spatial Fuzzy c-Means Clustering for Image Segmentation

  • Kang, Bo-Yeong;Kim, Dae-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.1
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    • pp.89-93
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    • 2010
  • In this paper a new fuzzy clustering approach to the color clustering problem has been proposed. To deal with the limitations of the traditional FCM algorithm, we propose a spatial homogeneity-based FCM algorithm. Moreover, the cluster validity index is employed to automatically determine the number of clusters for a given image. We refer to this method as VS-FCM algorithm. The effectiveness of the proposed method is demonstrated through various clustering examples.

Interval-Valued Fuzzy Cosets

  • Lee, Keon-Chang;Hur, Kul;Lim, Pyung-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.646-655
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    • 2012
  • First, we prove a number of results about interval-valued fuzzy groups involving the notions of interval-valued fuzzy cosets and interval-valued fuzzy normal subgroups which are analogs of important results from group theory. Also, we introduce analogs of some group-theoretic concepts such as characteristic subgroup, normalizer and abelian groups. Secondly, we prove that if A is an interval-valued fuzzy subgroup of a group G such that the index of A is the smallest prime dividing the order of G, then A is an interval-valued fuzzy normal subgroup. Finally, we show that there is a one-to-one correspondence the interval-valued fuzzy cosets of an interval-valued fuzzy subgroup A of a group G and the cosets of a certain subgroup H of G.

FURTHER RESULTS OF INTUITIONISTIC FUZZY COSETS

  • HUR, KUL;KANG, HEE WON;KIM, DAE SIG
    • Honam Mathematical Journal
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    • v.27 no.3
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    • pp.369-388
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    • 2005
  • First, we prove a number of results about intuitionistic fuzzy groups involving the notions of intuitionistic fuzzy cosets and intuitionistic fuzzy normal subgroups which are analogs of important results from group theory. Also, we introduce analogs of some group-theoretic concepts such as characteristic subgroup, normalizer and Abelian groups. Secondly, we prove that if A is an intuitionistic fuzzy subgroup of a group G such that the index of A is the smallest prime dividing the order of G, then A is an intuitionistic fuzzy normal subgroup. Finally, we show that there is a one-to-one correspondence the intuitionistic fuzzy cosets of an intuitionistic fuzzy subgroup A of a group G and the cosets of a certain subgroup H of G.

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Fuzzy Identification by Means of an Auto-Tuning Algorithm and a Weighted Performance Index

  • Oh, Sung-Kwun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.6
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    • pp.106-118
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    • 1998
  • The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

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