• 제목/요약/키워드: Fuzzy Associative Memory

검색결과 28건 처리시간 0.022초

Fault Diagnostic System Based on Fuzzy Time Cognitive Map

  • Lee, Kee-Sang;Kim, Sung-Ho
    • Transactions on Control, Automation and Systems Engineering
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    • 제1권1호
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    • pp.62-68
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    • 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.

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퍼지 추론 네트워크를 이용한 절삭 가공 공정의 춤질관리를 위한 공정 분석 시스템 (A process analysis system using Fuzzy reasoning networks for quality control of cutting)

  • 홍준희;대원성부
    • 한국정밀공학회지
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    • 제12권6호
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    • pp.64-71
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    • 1995
  • The objective of this paper is to realize an analysis system that is capable of controlling the quality of an entire cutting process by including a 3 coordinate measuring machine in the process line. Fuzzy reasoning networks based on fuzzy associative memories has been intro- duced in the measuring process, the control limits for the control process have been obtained, and the efficiency and reliability of the system have been determined by examining the simu- lated reasoning control values.

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퍼지연상기억장치에 기반한 협력 추천 방법 (A Collaborative Recommendation Method based on Fuzzy Associative Memory)

  • 이동섭;고일주;김계영
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권8호
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    • pp.1054-1061
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    • 2004
  • 최근 인터넷의 발전으로 정보의 접근이 용이할 뿐 아니라 그 양 또한 기하급수적으로 증가하고 있다. 정보의 홍수 속에서 원하는 정보만을 자동으로 추출할 수 있는 기술은 정보검색에 소요되는 시간과 노력을 절약할 수 있는 매우 중요한 연구이다. 본 논문에서는 관심 범위가 유사한 사용자에게 양질의 정보를 자동으로 추천하기 위하여 협력적 여과방법에 관하여 제안한다. 제안하는 방법의 기본적인 배경은 사용자는 선택항목의 선호도를 입력하고, 여과 장치는 이 선호도에 근거하여 추천집합을 자동으로 생성하는 것이다. 선호도로부터 추천집합을 추론하기 위하여 본 논문에서 퍼지 연상기억장치에 기반한 방법을 제안한다. 제안된 방법은 웹 서버상에서 기술문서 특히, 정보기술문서를 검색하는 분야에 대하여 구현하였으며 그 결과를 보인다.

퍼지 이론을 이용한 학습오인 진단 시스템 설계 및 구현 (A Design and Implementation of Diagnosis System of Learning Misconception by Using Fuzzy Theory)

  • 이현노;라상숙;최영식
    • 디지털융복합연구
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    • 제4권2호
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    • pp.143-151
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    • 2006
  • The purpose of this paper is to make a design and implementation of a diagnosis system of learning misconception of students who learn 'be' verb in the English language by using fuzzy theory. In this system, a fuzzy cognitive map exposes the fact that students' perception and misunderstanding about 'the English' language have an intertwined relationship, and diagnoses causes of misconceptions of students by using fuzzy memory associative memory. It suggests that since most existing systems of rule based expert system have had several limitations, this system will be applied to diagnose learners' misconception of learning in varieties of education areas.

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퍼지 이론을 이용한 영어학습 진단 시스템 설계 및 구현 (A Design and Implementation of Diagnosis System of Learning Misconception by Using Fuzzy Theory)

  • 이현노;라상숙;최영식
    • 한국디지털정책학회:학술대회논문집
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    • 한국디지털정책학회 2006년도 춘계학술대회
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    • pp.451-459
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    • 2006
  • The purpose of this paper is to make a design and implementation of a diagnosis system of learning misconception of students who learn 'be' verb in the English language by using fuzzy theory. In this system, a fuzzy cognitive map exposes the fact that students' perception and misunderstanding about 'the English' language have an intertwined relationship, and diagnoses causes of misconceptions of students by using fuzzy memory associative memory. It suggests that since most existing systems of rule based expert system have had several limitations, this system will be applied to diagnose learners' misconception of learning in varieties of education areas.

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뉴럴-퍼지패턴매칭에 의한 단어인식에 관한 연구 (A Study on Word Recognition Using Neural-Fuzzy Pattern Matching)

  • 이기영;최갑석
    • 전자공학회논문지B
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    • 제29B권11호
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    • pp.130-137
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    • 1992
  • This paper presents the word recognition method using a neural-fuzzy pattern matching, in order to make a proper speech pattern for a spectrum sequence and to improve a recognition rate. In this method, a frequency variation is reduced by generating binary spectrum patterns through associative memory using a neural network, and a time variation is decreased by measuring the simillarity using a fuzzy pattern matching. For this method using binary spectrum patterns and logic algebraic operations to measure the simillarity, memory capacity and computation requirements are far less than those of DTW using a conventional distortion measure. To show the validity of the recognition performance for this method, word recognition experiments are carried out using 28 DDD city names and compared with DTW and a fuzzy pattern matching. The results show that our presented method is more excellent in the recognition performance than the other methods.

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Hybrid Fuzzy Association Structure for Robust Pet Dog Disease Information System

  • Kim, Kwang Baek;Song, Doo Heon;Jun Park, Hyun
    • Journal of information and communication convergence engineering
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    • 제19권4호
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    • pp.234-240
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    • 2021
  • As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

퍼지개념을 이용한 고성능 고장진단 시스템의 설계 (Design of High Efficient Fault Diagnostic System by Using Fuzzy Concept)

  • 이쌍윤;김성호;권오신;주영훈
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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    • pp.247-251
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    • 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 and verified its usefulness. However, the previously proposed scheme has the problem of lower diagnostic resolution as in the case of other qualitative approaches. In order to improve the diagnostic resolution, a concept of fuzzy number is introduced into the basic FCM-based fault diagnostic algorithm. By incorporation the fuzzy number into fault FCM models, quantitative information such as the transfer gain between the state variables can be effectively utilized for better diagnostic resolution. Furthermore, an enhanced TAM(Temporal Associative Memory) recall procedure and modified and modified pattern matching scheme are also proposed.

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개선된 퍼지연상기억장치에 기반한 장면전환 검출 (Shot Transition Detection based on Improved Fuzzy Association Memory)

  • 이동하;고일주;김계영;최형일
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제29권8호
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    • pp.565-572
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    • 2002
  • 학습과 추론을 위하여 유용한 방법으로 퍼지연상기억장치가 있다. 본 논문에서는 보다 효과적으로 추론결과를 유도하기 위하여 퍼지연상기억장치를 학습하는 단계에서 오류 역전파를 통하여 노드들 사이의 연결가중치를 재조정하는 방법과 퍼지규칙들을 간결화하는 방법을 제안한다. 제안된 방법은 비디오 데이타의 장면전환을 검출하는 분야에 적용하여 성능평가를 수행한다.

순환 퍼지연상기억장치를 이용한 음성경계 추출 (Word Boundary Detection of Voice Signal Using Recurrent Fuzzy Associative Memory)

  • 마창수;김계영;최형일
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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    • pp.235-237
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    • 2003
  • 본 논문에서는 음성인식을 위한 전처리 단계로 음성인식의 대상을 찾아내는 음성경계 추출에 대하여 기술한다. 음성경계 추출을 위한 특징 벡터로는 시간 정보인 RMS와 주파수 정보인 MFBE를 사용한다. 사용하는 알고리즘은 학습을 통해 규칙을 생성하는 퍼지연상기억장치에 음성의 시간 정보를 적용하기 위해 순환노드를 추가한 새로운 형태의 순환 퍼지연상기억장치를 제안한다.

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