• 한국경영과학회지
• /
• 제26권1호
• /
• pp.15-32
• /
• 2001

It is well known that the web design is composed of several factors which are interacting with each other. However, the current approach to web design had been focused on modifying specific factors without considering its impact on other factors. In this sense, we propose more holistic approach to the web design by using fuzzy cognitive map. For this purpose, we form an illustrative fuzzy cognitive map for the web design which is based on the literature, and analyzed and impact of change in a specific factor on other factors. Especially, to improve the output analyzability, we suggested an advanced version of fuzzy cognitive map called stratified fuzzy cognitive map. After simulating the fuzzy cognitive map for web design, we could conclude that our approach is robust and effective compared to the traditional web design approach.

• 한국전자거래학회:학술대회논문집
• /
• 한국전자거래학회 2004년도 e-Biz World Conference
• /
• pp.134-149
• /
• 2004

This paper is aimed at proposing a fuzzy inference mechanism to enhancing the quality of cognitive map-based inference. Its main virtue lies in the two mechanisms： (1) a mechanism for avoiding a synchronization problem which is often observed during inference process with traditional cognitive map, and (2) a mechanism for fuzzifying decision maker's subjective judgment. Our proposed fuzzy inference mechanism (FIM) is basically based on the cognitive map stratification algorithm which can stratify a cognitive map into number of strata and then overcome the synchronization problem successfully. Besides, the proposed FIM depends on fuzzy membership function which is administered by decision maker. With an illustrative B2B negotiation problem, we applied the proposed FIM, deducing theoretical and practical implications. Implementation was conducted by Matlab language.

• Transactions on Control, Automation and Systems Engineering
• /
• 제1권1호
• /
• pp.62-68
• /
• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.860-863
• /
• 1997

FCM(Fuzzy Cognitive Map) is a fuzzy signed directed graph for representing causal reasoning which has fuzziness between causal concepts. Authors have already proposed FCM-based fault diagnostic scheme. However, the previously proposed scheme has the problem of lower diagnostic resolution. In order to improve the diagnostic resolution, a new diagnostic scheme based on extended FCM which incorporates the concept of fuzzy number into FCM is developed in this paper. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and pattern matching scheme are also proposed.

• 한국콘텐츠학회논문지
• /
• 제8권12호
• /
• pp.1-9
• /
• 2008

인과관계의 지식을 모델링하고 표현하며 추론하는 주요 형식화 방법의 하나인 퍼지인식도(Fuzzy Cognitive Map)는 주로 인과지식공학에 많이 사용되고 있다. 인과관계의 자연스럽고 쉬운 의사결정의 이해와 전후관계의 자연스러운 설명이라는 장점에도 불구하고 인과관계의 지식 모델링과 표현은 구현에 있어서 수학적인 적용의 모호함과 복잡한 알고리즘으로 인해 상호작용에 기반 한 구축 시스템을 찾아보기 어렵다. 본 논문에서는 인과지식 추론을 위한 퍼지 인식도의 구축 지원 시스템을 제시한다. 본 논문에서 제안하는 인과관계 추론 시스템은 다중 전문가의 지식을 반영하기 위해 지식을 점진적으로 반영하여 퍼지 인식도를 구축한다. 또한 전문가와의 상호작용을 통해 구현된 퍼지 인식도의 구조를 동적으로 디스플레이함으로써 사용자 지향적인 환경을 제공한다.

• 한국시뮬레이션학회논문지
• /
• 제3권2호
• /
• pp.37-47
• /
• 1994

This paper examines the use of fuzzy cognitive maps to help understand manufacturing strategy processes. This technique is illustrated through a case study of a manufacturing strategy formulation. Advantages of fuzzy cognitive maps are highlighted by comparing the level of understanding before and after the technique was used. The merit from the use of fuzzy cognitive maps for manufacturing strategy formulation is also discussed. (Manufacturing Strategy Formulation, Fuzzy Cognitive Map, Strategy Process Model, Feedback)

• 지능정보연구
• /
• 제1권2호
• /
• pp.33-55
• /
• 1995

포지인식도(Fuzzy Cognitive Map : FCM)는 추상적이고 비구조적이며 동적인 응용영역에서 전문가의 인과관계 지식(causal knowledge)을 표현하는데 매우 유용한 도구이다. FCM이 기존의 다른 네트워크 형태의 지식표현방법과 다른 차이점은 대상 문제의 개념변수들을 퍼지집합으로 묘사하고, 개념 변수간의 관계를 퍼지 인과관계로 다룬다는 것이다. 그런데 FCM의 특성이 아직 충분히 논의되지 않은 상태에서는 FCM의 적용에 있어 오류가 일어날 수 있다. 본 논문의 목적은 첫째, FCM의 특성과 의미를 보다 명확히 하여 이론적인 측면을 보강하고자 한다. 이를 위해 논리적관계(implication)와는 다른 인과관계의 정의를 다시 확인하고, 이정의에 기초한 퍼지 인과관계의 특성을 파악하고, 퍼지 인과관계와 대비되는 퍼지 부분인과관계 및 단방향 개념변수를 새로이 정의함으로써 FCM구축에 있어 잘못된 이해가 없게 하며, 둘째, FCM에서는 추론 방식이 갖추어야 할 원칙을 명시하고 이에 따라 이러한 원칙을 준수하는 새로운 추론 방식을 제시한다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
• /
• pp.247-250
• /
• 2003

Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

• 한국지능시스템학회논문지
• /
• 제20권1호
• /
• pp.123-128
• /
• 2010

어떤 한 프로젝트를 성공할 가능성을 높이기 위해서는 그 성과에 영향을 줄 수 있는 요소들에 대해 정의할 필요가 있다. 인지도는 관련있는 요소들의 인과관계를 조사함으로써 분석하는데 널리 사용되고 있다. 퍼지인지도는 인관관계의 연결강도를 통해 피드백의 개념을 추가한 인지도의 확장 개념을 가지고 있다. 프로젝트 성과는 입력 자원, 수행가능성, 타인의 관심 정도 등에 의해 영향을 받는다. 본 논문에서는 프로젝트의 성과와 이런 요소들간의 인과관계의 정도를 조사 분석하기 위해 퍼지인지도를 활용하여 기업프로젝트의 성공을 위한 모델을 개발하고자 한다.

• 지능정보연구
• /
• 제5권2호
• /
• pp.79-97
• /
• 1999

Knowledge management (KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization knowledge is at the heart of KM success. As a vehicle of acquiring organizational knowledge in a distributed decision-making environment, we applied a fuzzy cognitive map (FMM) technique and proved its effectiveness in a distributed knowledge management environment. Our approach was applied to the financial statement analysis problem, yielding a robust result.