• Title/Summary/Keyword: fuzzy probability theory

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A Study on the Design of Safety Work and the Measure of Safety for Accident Prevention (재해 예방을 위한 안전작업의 설계 및 안전도 측정에 관한 연구)

  • 이근희;김도희
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.17 no.31
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    • pp.177-186
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    • 1994
  • Most causes of accidents are due to physical unsafety conditions and human unsafety actions. The design of safety work by ergonomics method is one of the methodes which effectively reduce these unsafety conditions and unsafety actions. This paper presents considerations in design of safety work. And when we try to analyze the accident event by means of probability, there exist some problems because of fuzziness in physical unsafety conditions' components and human unsafety actions' components which are the causes of basic event. For this reason, it is impossible for input probability of basic event to define a crisp value. In consideration of the uncertain probability of components, this paper deals with the Fuzzy set theory by membership value and suggests calculation procedure and analysis of disaster event.

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A novel evidence theory model and combination rule for reliability estimation of structures

  • Tao, Y.R.;Wang, Q.;Cao, L.;Duan, S.Y.;Huang, Z.H.H.;Cheng, G.Q.
    • Structural Engineering and Mechanics
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    • v.62 no.4
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    • pp.507-517
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    • 2017
  • Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.

Risk Assessment using Fuzzy Linguistic Variables in Korean (한국어 퍼지 언어변수를 이용한 리스크 평가)

  • Lim, Hyeon-Kyo;Byun, Sanghun;Kim, Hyunjung
    • Journal of the Korean Society of Safety
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    • v.30 no.4
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    • pp.151-158
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    • 2015
  • Usually risk assessment is performed for the safety of diverse industries though, many kinds of risks cannot be analyzed effectively by using classical probability models due to lack of experience data and impreciseness of human decision making. For these reasons, fuzzy risk assessment utilizing subjective judgment and experience of skillful experts has been considered as a solution. In this study, to comprehend the relationship between conventional fuzzy theory and human conceptual images on risks, linguistic variables were reviewed with reference to fuzzy membership functions, especially in the Korean language. As interviewees, about a hundred people including students as well as safety engineers voluntarily participated. The research results showed that most people were in favor of adjective expressions decorated with adverbs rather than naive expressions such as "high" or "low", and that directly translated linguistic variables were not appropriate for the Korean people in risk assessment as far. Therefore, with consideration of the selection tendency by the Korean people in linguistic variables, it could be concluded that 5 level expressions would be most favorable for linguistic variables in risk assessments in Korea.

ON THE STOCHASTIC OPTIMIZATION PROBLEMS OF PLASTIC METAL WORKING PROCESSES UNDER STOCHASTIC INITIAL CONDITIONS

  • Gitman, Michael B.;Trusov, Peter V.;Redoseev, Sergei A.
    • Journal of applied mathematics & informatics
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    • v.6 no.1
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    • pp.111-126
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    • 1999
  • The article is devoted to mathematical modeling of prob-lems of stochastic optimization of the plastic metal working. Classifi-cation and mathematical statements of such problems are proposed. Several calculation techniques of the single goal function are pre-sented. The probability theory and the Fuzzy numbers were applied for solution of the problems of stochastic optimization.

An Analysis of Human Reliability Represented as Fault Tree Structure Using Fuzzy Reasoning (Fault Tree구조로 나타낸 인간신뢰성의 퍼지추론적해석)

  • 김정만;이동춘;이상도
    • Proceedings of the ESK Conference
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    • 1996.04a
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    • pp.113-127
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    • 1996
  • In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

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Fuzzy reliability analysis of laminated composites

  • Chen, Jianqiao;Wei, Junhong;Xu, Yurong
    • Structural Engineering and Mechanics
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    • v.22 no.6
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    • pp.665-683
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    • 2006
  • The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.

Comparative study of Probabilistic Load Flow and Fuzzy Load Flow (확률적 전력조류계산과 퍼지 전력조류계산과의 비교 연구)

  • Jung, Young-Soo;Shim, Jae-Hong;Kim, Jin-O
    • Proceedings of the KIEE Conference
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    • 1997.07c
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    • pp.1100-1102
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    • 1997
  • This paper presents a generalized multi-parameter distribution method for the convolution of linear combination of random variables to calculate system load flow in a conventional probabilistic approach and also presents a conceptual possibilistic approach using fuzzy set theory to manage uncertainties. The probability distribution function is transformed into an appropriate possibilistic representation under the compromise between the transformation consistency and the human updating experience. The IEEE 25-bus system is used to demonstrate the capability of the proposed algorithm.

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An Improved Dempster-Shafer Algorithm Using a Partial Conflict Measurement

  • Odgerel, Bayanmunkh;Lee, Chang-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.308-317
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    • 2016
  • Multiple evidences based decision making is an important functionality for computers and robots. To combine multiple evidences, mathematical theory of evidence has been developed, and it involves the most vital part called Dempster's rule of combination. The rule is used for combining multiple evidences. However, the combined result gives a counterintuitive conclusion when highly conflicting evidences exist. In particular, when we obtain two different sources of evidence for a single hypothesis, only one of the sources may contain evidence. In this paper, we introduce a modified combination rule based on the partial conflict measurement by using an absolute difference between two evidences' basic probability numbers. The basic probability number is described in details in Section 2 "Mathematical Theory of Evidence". As a result, the proposed combination rule outperforms Dempster's rule of combination. More precisely, the modified combination rule provides a reasonable conclusion when combining highly conflicting evidences and shows similar results with Dempster's rule of combination in the case of the both sources of evidence are not conflicting. In addition, when obtained evidences contain multiple hypotheses, our proposed combination rule shows more logically acceptable results in compared with the results of Dempster's rule.

Development of the Shortest Route Search Algorithm Using Fuzzy Theory (퍼지 추론을 이용한 최단 경로 탐색 알고리즘의 개발)

  • Jung, Yung-Keun;Park, Chang-Ho
    • Journal of Korean Society of Transportation
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    • v.23 no.8 s.86
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    • pp.171-179
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    • 2005
  • This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

Development of New Management Prediction Support System based on Non-stochastic Model

  • Kaino, Toshihiro;Hirota, Kaoru;Mitsuta, Akimichi;Miura, Yasuyuki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.7-10
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    • 2003
  • In the field of financial technology, it is the U.S. initiative, and Japan is obliged to flattery in many respect. Currently Japan is in a too much defenseless situation that the economic structure is based on U.S. theory, In the conventional stochastic theory, it is also face that the prediction sometimes does not hit in the actual problem because it assumes a known probability distribution, none of which illustrates the real situation. A new research and development of management prediction support system is proposed based on fuzzy measures, that deals with the ambiguous, subjective evaluation by the people living in the real world well. Especially, the system will support venture, small and medium companies.

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