• Title/Summary/Keyword: fuzzy evaluation model

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Modeling for Evaluating the Comfort Sensibility using Fuzzy-Weighted Score (Fuzzy-Weighted Score를 이용한 쾌적감성 평가모형)

  • Jeon, Yong-Woong;Cho, Am
    • IE interfaces
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    • v.18 no.2
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    • pp.158-166
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    • 2005
  • Human-error and mental stress caused by psychophysiological dissonance between people and artificial environments have become a social problem. And it is a common knowledge that comfort environment reduces human-error and mental stress. Comfort sensibility is related to complex interactions between fabric, climatic, physiological and psychological variables. Currently, comfort sensibility has been evaluated by many sensory tests. However, it is difficult to evaluate comfort sensibility because a concrete concept of comfort sensibility is hard to define. In this paper, we propose a model to evaluate the comfort sensibility using Fuzzy-weighted score on an individual's subjective state for the stimulus. To represent the degree of comfort sensibility level for the stimulus, we represent comfort sensibility using 2 dimensional sensibility vector model. And we use the fuzzy-weighted score that is a fuzzy version of the weighted checklist technique computerized for evaluating the subjects. As an example, this model is applied to 1/f fluctuation sound evaluation. The results show that this model can be effectively used to the quantitative evaluation of comfort sensibility for the stimulus.

Fuzzy Closed BCMP Queueing Network Model for Performance Evaluation of Centralized Distributed Processing System (집중형 분산처리시스템의 성능평가를 위한 퍼지 폐쇄형 BCMP 큐잉네트워크모델)

  • Choo, Bong-Jo;Jo, Jung-Bok;Woo, Chong-Ho
    • The KIPS Transactions:PartA
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    • v.9A no.1
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    • pp.45-52
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    • 2002
  • This paper proposes the fuzzy closed RCMP queueing network model using fuzzy set theory for the performance evaluation of centralized distributed processing system with ambiguous system factors in the network environments. This model can derive the measures for system performances such as the job spending time, the system throughput, average job number and server utilizations using fuzzy mean value analysis which can process the fuzzy factors. Computer simulation has been performed centralized distributed system with fuzzy service requirement time for verifying the effectiveness of derived equations of performance evaluation according to the numbers of clients, and the results were analyzed. The proposed model provides more and flexible realistic than performance evaluation of conventional method when we evaluated system performance with ambiguous factors.

Fuzzy Rule-Based Method for Air Threat Evaluation (적기의 위협 평가 자동화를 위한 퍼지 규칙 방법론)

  • Choi, Byeong Ju;Kim, Ji Eun;Kim, Jin Soo;Kim, Chang Ouk
    • Journal of the Korea Institute of Military Science and Technology
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    • v.19 no.1
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    • pp.57-65
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    • 2016
  • Threat evaluation is a process to estimate the threat score which enemy aerial threat poses to defended assets. The objective of threat evaluation is concerned with making an engagement priority list for optimal weapon allocation. Traditionally, the threat evaluation of massive air threats has been carried out by air defence experts, but the human decision making is less effective in real aerial attack situations with massive enemy fighters. Therefore, automation to enhance the speed and efficiency of the human operation is required. The automatic threat evaluation by air defense experts who will perform multi-variable judgment needs formal models to accurately quantify their linguistic evaluation of threat level. In this paper we propose a threat evaluation model by using a fuzzy rule-based inference method. Fuzzy inference is an appropriate method for quantifying threat level and integrating various threat attribute information. The performance of the model has been tested with a simulation that reflected real air threat situation and it has been verified that the proposed model was better than two conventional threat evaluation models.

Fuzzy Indexing and Retrieval in CBR with Weight Optimization Learning for Credit Evaluation

  • Park, Cheol-Soo;Ingoo Han
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.491-501
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    • 2002
  • Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

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The emotional evaluation of color pattern based on information fusion (정보융합 기법을 이용한 칼라 패턴의 감성 평가)

  • 김성환;엄경배;이준환
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.23-27
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    • 2000
  • In this paper, we propose an emotional evaluation model based on information fusion. This model can transform the physical features of a color pattern to the emotional features. Our proposed model consists of the fuzzy logic system and neural network model. The evaluation values produced by them were fused. The model shows comparable performances to the neural network and fuzzy logic system for the approximation of the nonlinear transforms. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

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A Mathematical model for web site service quality evaluation based on AHP and fuzzy methodology

  • Liu, Yi-wen;Kwon, Young-Jik
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.5
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    • pp.119-131
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    • 2006
  • This paper proposes a mathematical model for web site service quality evaluation, which first applies analytic hierarchy process(AHP) to determine the weights of evaluation indexes of web site service quality and then analyzes web site service synthetically by means of fuzzy methodology. In this case, experts' knowledge cannot only be used but its subjective component can be eliminated. Hence, the web site service quality can be analyzed and evaluated more reasonably. After establishing this model, the experiment results will be given, which verify the feasibility and validity of the proposed model. The model proposed here is very simple and easy to implement and can provide a useful way to help developers evaluate their web site service quality efficiently.

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Development on Fuzzy-AHP Ranking Risk Assessment Model for the monitoring systems (관제시스템 구축을 위한 Fuzzy-AHP 위험 순위 평가 모델 개발)

  • Chung, Sung-Hak;Park, Tae-Joon
    • Journal of the Korea Safety Management & Science
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    • v.13 no.2
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    • pp.51-59
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    • 2011
  • The objective of this study is to develop an evaluation model for the National highway risky areas. Thus, for the purposes of doing this, National highway risky area evaluated targeting to provide determination ranking and suggesting rival-superiority factors as well as under-inferiority factors in ten National highway risky areas. This study developed for modules of risky areas evaluation, using fuzzy set theory and analytic hierarchy process for evaluation model of National highway risky area in transport environment. The preceding studies assess risk analysis through analysis of causal relationships by National highway safety sector not only handles rating scale development suitable for assessment area by referring to accident frequency model but also geometric structures model. As result of this study, this model of Fuzzy Ahp Risk Analysis (FARA) apply for programmable design in real time processing through easily derive strategy for improvement activities to provide a decision-making effectively. Furthermore, this study contributes frame for improvements of National highway construction for renovation's priority strategy as well as future's policy schemes.

Optimal Inspection Policy By Fuzzy Goal Programming (Fuzzy Goal Programming을 이용한 최적 검사 정책)

  • 유정상
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.34
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    • pp.185-191
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    • 1995
  • In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the outgoing quality and the average total inspection cost A fuzzy goal programming model and its solution procedure are proposed for the managers whose management objectives on the two evaluation criteria are not rigorous. To study the sensitivity of quality characteristic dependence on the resulting inspection plans, a numerical example is solved several times for a dependent model.

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Fuzzy-AHP-Based Technology Evaluation Model for venture firms (Fuzzy-AHP에 기반을 둔 벤처기업의 기술력 평가 모델)

  • Joun, Hyang-Soon;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.14 no.7
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    • pp.363-371
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    • 2016
  • Technology evaluation for technology innovation of venture firms should take the rapidly changing corporate environment, the ambiguity of language used in evaluation, and the inaccuracy of evaluation index into consideration. In this paper, targeting the absorptive capacity and technological entrepreneurship which are typical evaluation factors of venture firms, an ACTEM model to calculate the importance, priority, and dynamic capability of factors, applying Fuzzy-AHP was proposed. The fuzzy theory was introduced to compensate for the ambiguity of cognitive judgments when calculating weighted values for the factors that made up an assessment scale. An assessment criteria framework for absorptive capacity, technological entrepreneurship, and dynamic capability, which were not considered in previous studies on the evaluation and measurement of technological prowess, so that the users could have a realistic alternative to choose. The study compared the ACTEM model with the old AHP assessment method and found that "knowledge acquisition" and "producing ability" were the highest in absorptive capacity and technological entrepreneurship, respectively, thus demonstrating its validity.

Evaluation of the Performance and Reliability of a Real-time Power System Described by a DES Model using Fuzzy-Random Variables (퍼지-랜덤 변수를 이용한 DES 모델링을 통한 실시간 전력 시스템의 성능 및 신뢰도 평가)

  • Min, Byeong-Jo;Lee, Seok-Ju;Kim, Hak-Bae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.7
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    • pp.363-369
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    • 2000
  • To flexibly evaluate performance and reliability of an electric power system in the aspect of the real-time system which is intrinsically characterized by stringent timing constraints fails catastrophically if its control input is not updated by its digital controller computer within a certain time limit called the hard deadline, we propose fuzzy-random variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas as well.

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