• 제목/요약/키워드: Fuzzy Decision Making

검색결과 420건 처리시간 0.029초

A Multimodal Emotion Recognition Using the Facial Image and Speech Signal

  • Go, Hyoun-Joo;Kim, Yong-Tae;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권1호
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    • pp.1-6
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    • 2005
  • In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.

Fuzzy Forecast of Nonlinear Time-series Data

  • Kuc, Tae-Yong;Tefsuya, Muraoka
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.85.3-85
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    • 2001
  • The field of forecasting is considered as an application of time-series analysis even if the data is linear or nonlinear. To obtain the forecasted values from observed data exerts a big influence on the decision-making support system or the control of machine etc. The nonlinear data appear as the random enumerated data. However we sometimes find that the pattern of past appearance repeats itself when we try to observe these data locally. From this point of view, we propose a way of forecasting nonlinear data from the pattern of past appearance using fuzzy theory. The advantages of the method are that we can forecast the next data by small numbers of previous data, and react to some differences, considering the ambiguous mature of the given data.

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Risk Assessment and Decision-Making of a Listed Enterprise's L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory

  • Cheng, Zhang;Huang, Nanni
    • Journal of Information Processing Systems
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    • 제16권2호
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    • pp.318-328
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    • 2020
  • Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

퍼지인식도를 이용한 다수 전문가지식 결합 알고리즘 개발에 관한 연구 (A Study on the Development of Multiple Experts' Knowledge Combining Algorithm by Using Fuzzy Cognitived Map)

  • 이건창;주석진;김현수
    • 한국경영과학회지
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    • 제19권1호
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    • pp.17-40
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    • 1994
  • The objectives of this paper are to apply fuzzy cognitive map (FCM)- related techniques to (1) extract causal knowledge from a specific problem-domain and (2) perform a series of causal analysis in complicated decision making area. We propose a set operation-based augmentation (SOBA) algorithm to combine multiple FCMs developed by multiple experts. Based on the SOBA knowledge acquisition algorithm, we can obtain a causal knowledge base fairly representing multiple experts' knowledge about a problem domain. The causal knowledge base built by SOBA algorithm can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if-then) knowledge base. We applied out method to stock market analysis problem whichis a typical of highly unstructured problems in OR/MS fields.

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DFDA를 이용한 에어 크리너의 분해성 평가 ( 한일 차량용을 중심으로 ) (Disassembility Assessment of Air-cleaner by DFDA ( For Korea-Japan Passenger-Vehicle ))

  • 김하수;강희용;양성모;진정선
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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    • pp.428-433
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    • 2000
  • A disassembility assessment has mostly depend on the subjective decision making from the qualitative element. The work of disassembly is already classified with given disassemble points from the symbolic chart method. It is not useful in the practical assessment because it is not specified. The new method of design for disassembility assessment(DFDA) is practical to introduce the fuzzy number as the conversion of quantitative element from qualitative. It is appled to compare the usefulness of air-cleaner in Korea-Japan passenger-vehicle.

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FSM을 이용한 해기사 신규채용 및 선사선택에 관한 의식구조분석 (Structural Analysis of Consciousness on the Shipping Companies, Employment of Marine Junior Officers and their Choosing these Companies, Using Fuzzy Structural Modeling)

  • 양원재;박계각;전승환
    • 한국항해학회지
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    • 제24권1호
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    • pp.35-45
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    • 2000
  • Recently, in the shipping companies have been employing prudently in order to prevent from sea accidents occurred by human factors. Also the students of merchant marine universities are choosing prudently the shipping companies when taking a job. But many qualitative and quantitative factors are considered in decision making for the employment and the choice of a company. FSM(Fuzzy Structural Modeling) has been widely used in modeling the system composed of such qualitative and quantitative factor. In this paper, a case study is discussed for the analysis of the consciousness of the employment of shining companies and students' choice of such company in maritime university using FSM. Also this paper proposed the planes for educating and recruitment guiding the student in maritime university.

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클라우드 서비스 파트너 역량 분석 프레임워크 개발 (A Development of Cloud Service Partner Competency Analysis Framework)

  • 박원주;서광규
    • 반도체디스플레이기술학회지
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    • 제21권3호
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    • pp.69-73
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    • 2022
  • The application of cloud computing to many industrial domains is rapidly increasing, and domestic and foreign cloud service providers are actively conducting business. In the domestic cloud market, it is necessary to establish an ecosystem with partner operators that work closely with private cloud service providers. In this paper, to create such an environment, we propose a framework that can evaluate the capabilities of partners required for cloud service providers to establish specific business strategies. The framework proposed in this study establishes criteria for evaluating partners' competencies and applies a decision-making model such as fuzzy AHP for evaluation. Eventually this will help not only to expand the domestic cloud market but also to strengthen the competitiveness of domestic cloud partners through the growth of the domestic cloud market.

AIS 에러 데이터 관리기법에 대한 연구 (Building an Algorithm for Compensating AIS Error Data)

  • 김도연;홍태호;정중식;이상재
    • 한국지능시스템학회논문지
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    • 제24권3호
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    • pp.310-315
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    • 2014
  • 최근 국내외 해상환경은 국제 해상 물동량 증가 및 활발한 해상 레저 활동으로 인하여 교통량이 증가함으로써 해양 사고의 발생 빈도가 높아지고 있는 추세이다. 이러한 해양사고를 줄이기 위해서 선교에는 항해사의 부담을 감소시키며 정확한 의사결정을 지원하기 위하여 다양한 종류의 항행 안전장비가 존재하고 있다. 그러한 장비들 중에서 선박자동식별장치의 경우 선박 자신의 정보를 송출하고 동시에 다른 선박의 정보를 받아들여 주위 상황판단에 도움을 주는 매우 중요한 시스템이나, 오류가 발생했을 경우 잘못된 정보를 주기적으로 송출하기 때문에 해당 정보를 이용하는 육상 관제사나 항행 중인 항해사의 의사결정에 지장을 주는 경우가 자주 발생한다. 이 연구는 AIS로부터 수신되는 선박 정보들의 신뢰도 및 정확도 향상을 위한 AIS 에러 데이터 및 필드 보정 알고리즘을 제안한다.

다중 매트릭스 분석 기법을 이용한 최적 건축공법 선정 의사결정지원 모델 (Decision Making Model using Multiple Matrix Analysis for Optimum Construction Method Selection)

  • 이종식;임명관
    • 한국건축시공학회지
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    • 제16권4호
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    • pp.331-339
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    • 2016
  • 건축물의 고층화, 복합화, 대형화에 따라 다양한 공법이 개발되고 있어 주요 공종에 대한 공법 선정의 중요성이 대두되고 있다. 그러나 프로젝트의 특성을 충분히 고려하지 못하고 있고 주요 공법의 선정을 위한 객관적 기준이나 자료 또한 부족한 실정이며, 실무자의 경험과 직관에만 의존하여 선정이 이루어지고 있는 점이 지적되어 왔다. 이러한 문제점을 해소하기 위해 퍼지, AHP, CBR 등 인공지능이론을 이용한 주요 공종의 공법 선정을 위한 다양한 연구가 진행되었다. 그러나 실무에서 공법 선정 시 공종별 특성 및 현장별 조건을 고려하여 주요 공종마다 각기 다른 여러 가지 공법 선정 모델을 적용하기는 어렵다. 이에 본 연구에서는 매트릭스 분석과 선형변환을 이용하여, 실무에서 활용이 용이한 범용적인 성격의 의사결정지원 모델을 제시하고, 사례 연구를 통해 흙막이 공법 선정 과정에 적용하여 연구모델의 정합성을 검증하였다.

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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    • 제16권4호
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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.