• 한국멀티미디어학회논문지
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• 제11권12호
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• pp.1739-1748
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• 2008

When we conduct a data mining procedure on sample data sources, several rules are generated. But some rules are redundant or logically disjoint and therefore they can be removed. We suggest a new rule minimization algorithm inspired from logic synthesis to improve comprehensibility and eliminate redundant rules. The method can merge several relevant rules into one based on data mining and logic synthesis without high loss of accuracy. In case of two or more rules are candidates to be merged, we merge the rules with the attribute having the lowest information gain. To show the proposed method could be a reasonable solution, we applied the proposed approach to a problem domain constructing user preferred ontology in anti-spam systems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.145-150
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• 1997

In this paper is studied a method of fuzzy logic control based on possibly inconsistent if-then rules representing uncertain knowledge or imprecise data. In most cases of practical applications adopting fuzzy if-then rule bases, inconsistent rules have been considered as ill-defined rules and, thus, not allowed to be in the same rule base. Note, however, that, in representing uncertain knowledge by using fuzzy if-then rules, the knowledge sometimes can not be represented in literally consistent if-then rules. In this regard, when it is hard to obtain consistent rule base, we propose the weighted rule base fuzzy logic control depending on output performance using neural network and we will derive the weight update algorithm. Computer simulations show the proposed method has good performance to deal with the inconsistent rule base fuzzy logic control. And we discuss the real application problems.

• 철학연구
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• 제139권
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• pp.1-21
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• 2016

문장 서술의 일관성이나 진 위를 신속 정확히 파악하기 위해서 컴퓨터의 힘을 빌릴 수 있다. 따라서 문장논리의 컴퓨터프로세싱으로 문장 전체 서술의 일관성이나 진 위를 신속 정확히 파악하기 위한 연구가 있을 만하다. 이런 필요에 따라 본 연구에서는 컴퓨터프로세싱과정을 기획하고, 그 프로세싱에 필요한 테이블을 작성하고, 그리고 5개 논리규칙의 테이블을 우선 개발하여 활성화해본다. 그래서 차후 연구에서 10개의 기본추론규칙과 11개의 파생추론규칙 각각의 테이블을 개발하고, 그 다음 개발된 테이블들을 활성화하여 구축한 DB 위에 서버 프로그래밍 JSP와 클라이언트 프로그래밍 JAVA를 이용하여 문장논리규칙을 프로세싱하는 토대를 마련한다. 2장에서 프로세싱과정의 기획은 먼저 논리연산테이블을 탐색해서 논리규칙과 추론규칙을 공식으로 구분하고, 공식에 사용할 조합을 구분해서 순번으로 열거하는 작업을 하도록 하여, 변수 테이블, 논리기호 테이블, 입력처리 테이블을 작성한다. 그래서 차후 연구에서 주어부와 술어부를 활성화한 DB 위에 서버 프로그래밍 JSP와 클라이언트 프로그래밍 JAVA를 이용하여 문장의 참 거짓을 판명하도록 준비한다. 3장에서는 2장에서 작성 준비한 테이블을 참고해서 문장논리를 위해 명제적 계산, 문장논리 계산 혹은 진술논리 계산에 사용되는 5개의 논리규칙 즉, 이중부정규칙, 드모르간규칙, 교환규칙, 결합규칙 그리고 분배규칙 모두의 테이블을 개발하고, 마지막 4장에서는 개발한 테이블의 활성화로 DB 구축과 더불어 논리규칙 프로세싱하는 단계까지 이론적 구상을 해본다.

• 한국지능시스템학회논문지
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• 제7권5호
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• pp.46-50
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• 1997

퍼지논리 제어에서 정적인 퍼지규칙은 플랜트나 환경 파라메터의 중대한 변화에 대처할 수 없다. 이러한 문제를 해결하기 위하여 지금까지 스스로 조직화하는 퍼지제어 및 신경망에 기초한 뉴로퍼지등의 기법이 도입되었다.그러나 이러한 기존 방법들은 동적으로 변화된 퍼지 규칙이 완전하지 않거나 모순될 수 있음으로 해서 퍼지 제어기를 위험한 상황에 처하게 할수도 있다. 본 논문에서는 예측 신경망을 사용하여 새로운 적응퍼지 제어기법을 제안한다.제안된 퍼지제어기는 비록 제어 플랜트나 환경 파라메터가 변화할지라도 초기의 완전하고 모순되지 않은 퍼지 규칙과 계속해서 학습하는 예측 신경망의 예측에러를 이용하여 제어출력을 안전하게 적응적으로 변화시켜간다. 직류 서보모터의 위치제어문제를 이용하여 실험해본 결과 제안한 방법이 적응면에서 매우 유용함을 보였다.

• 한국안전학회지
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• 제19권1호
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• pp.49-55
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• 2004

This study presents an analysis of comparison of P-type fire detection system with fuzzy logic-applied fire detection system. The fuzzy logic-applied fire detection system has input variables obtained by fire experiment of small scale with K-type temperature sensor and optical smoke sensor. And the antecedent part of fuzzy rules consists of temperature and smoke density, and the consequent part consists of fire probability. Also triangular fuzzy membership function is used for input variables and fuzzy rules. To calculate the final fire probability a centroid method is introduced. A fire experiment is conducted with controlling wood crib layer, cigarette to simulate actual fire and false alarm situation. The results show that peak fire probability is 25[%] for non-fire and is more than 80[%] for fire situation, respectively. The fuzzy logic-applied fire detection system suggested here is able to distinguish fire situation and non-fire situation very precisely.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1370-1373
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• 1993

In controlling a system having many variables to control and multi objectives to satisfy such as a roof crane system, it is often difficult to obtain fuzzy If-Then rules in usual ways. As an alternative, we can more easely obtain rules in such a manner that we obtain each independent group of rules using partial variables for a partial objective. In this case, obtained rules can be conflicting with each other and conventional inference methods cannot handle such rules effectively. In this paper, we propose a roof crane controller with optimal velocity profile generator and a fuzzy logic controller with an inference method suitable for such conflicting rules.

• 인터넷정보학회논문지
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• 제3권1호
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• pp.51-59
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• 2002

기존의 규칙베이스 검증 알고리즘은 명제논리 수준에 대응하는 지식표현에 대한 것들이었다. 실 세계어서 규칙베이스를 구성할 때는 술어논리 수준에 대응하는 규칙을 사용하여 규칙베이스를 구성한다. 그러므로 본 논문에서는 규칙을 술어논리 수준에서 자연스럽게 표현할 수 있는 Pr/T 네트를 이용한 규칙베이스의 검증 알고리즘을 제안한다.

• 한국산업융합학회 논문집
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• 제27권2_1호
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• pp.249-256
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• 2024

Traditional methods for monitoring targets rely heavily on probabilistic data association (PDA) or Kalman filtering. However, achieving optimal performance in a densely congested tracking environment proves challenging due to factors such as the complexities of measurement, mathematical simplification, and combined target detection for the tracking association problem. This article analyzes a target tracking problem through the lens of fuzzy logic theory, identifies the fuzzy rules that a fuzzy tracker employs, and designs the tracker utilizing fuzzy rules and Kalman filtering.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.7-12
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• 2005

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper. The expert system which introduces fuzzy logic in order to process uncertainties is called fuzzy expert system. The fuzzy expert system, however, has a potential problem which may lead to inappropriate results due to the ignorance of some information by applying fuzzy logic in reasoning process in addition to the knowledge acquisition problem. In order to overcome these problems, We construct fuzzy inference network by extending the concept of reasoning network in this paper. In the fuzzy inference network, the propositions which form fuzzy rules are represented by nodes. And these nodes have the truth values representing the belief values of each proposition. The logical operators between propositions of rules are represented by links. And the traditional propagation rule is modified.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.93-99
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• 2003

One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC's. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC's) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC's are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.