• Title/Summary/Keyword: Reasoning Rule

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Development of a Financial Product Factory System (맞춤형 금융상품 설계시스템의 개발)

  • 최성철;이성하;주정은;구상회
    • Journal of Information Technology Applications and Management
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    • v.10 no.4
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    • pp.119-133
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    • 2003
  • 맞춤형 금융상품 설계시스템(Financial Product Factory System)이란 온라인으로 접근하는 고객의 요구사항을 고려하여 고객에게 가장 적합한 금융상품을 실시간으로 설계하여 제공하는 시스템이다. 최근 들어 인터넷 뱅킹 고객의 수가 급증함에 따라 맞춤형 금융상품 설계시스템의 필요성이 대두되고 있으나, 이러한 시스템의 정의나 성격, 필요 기능, 구축 방안에 대한 연구가 되어 있지 않은 실정이다. 본 연구에서는 맞춤형 금융상품 설계시스템의 정의를 내리고, 이 시스템이 갖추어야 할 요구사항을 시스템과 서비스 측면에서 분석한 후, 이 요구사항을 반영하는 시스템의 아키텍처를 제안ㆍ구현한다

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Case-based Block Division Expert System in Shipbuilding (사례기반 추론에 의한 블럭분할 절문가 시스템)

  • 박철우;강신한;김광만;이재원
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.17 no.30
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    • pp.161-165
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    • 1994
  • The shipbuilding industry is one of the domains which need an effective computer application. Particularly the productivity of process planning of a shipbuilding for crude -oil tanker can be greatly enhanced by introducing CAPP(Computer Aied Process Planning). In this paper we describe a prototype expert system which enables block division process planning in shipbuilding. The system determines block division lines of the midship sections of oiltanker. Case-based reasoning(CBR) approach is applied for this purpose instead of rule-based one.

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An Integrating Reasoning of Rule and Case base Using Derivatives and Expansions of Boolean Functions (Bode 함수의 미분 및 전개를 이용한 규칙과 사례의 통합 추론)

  • 박지연;김국보;정환묵
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1995.10b
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    • pp.285-292
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    • 1995
  • 최근 규칙베이스 추론과 사례베이스 추론의 통합화에 의한 추론이 다양하게 시도되 고 있다. 본 논문에서는 규칙과 사례를 동일한 형태로 표현하고, 규칙베이스와 사례베이스를 통합한 새로운 통합 추론 방법을 제안한다. 지식은 논리의 기하학적 모델을 이용하여 정보 를 논리적으로 해석하며, 동일한 형태로 표현된 규칙과 사례를 Boole 함수의 미분 및 전개 방법을 이용하여 추론하는 방법을 제안하고 응용예를 통하여 확인하다.

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Identifiers Extraction of Container Image using Fuzzy Reasoning Rule (퍼지 추론 규칙을 이용한 컨테이너 영상의 식별자 추출)

  • 주이환;김광백
    • Proceedings of the Korea Multimedia Society Conference
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    • 2004.05a
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    • pp.238-242
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    • 2004
  • 운송 컨테이너의 식별자를 추출하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, 검출된 에지 정보에서 영상획득 시 외부 광원에 의해 수직으로 길게 발생하는 잡음들을 퍼지추론 방법을 적용하여 제거한 후에 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출한다. 추출된 컨테이너의 식별자 영역에서 히스토그램 방법과 윤곽선 추적 알고리즘을 각각 이용하여 개별 식별자를 추출한다. 실제 컨테이너 영상을 대상으로 실험 결과, 제안된 컨테이너 식별자 추출 방법이 다양한 컨테이너 영상에 대해 효율적인 것을 확인하였다.

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A Belief Network Approach for Development of a Nuclear Power Plant Diagnosis System

  • I.K. Hwang;Kim, J.T.;Lee, D.Y.;C.H. Jung;Kim, J.Y.;Lee, J.S.;Ha, C.S .m
    • Proceedings of the Korean Nuclear Society Conference
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    • 1998.05a
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    • pp.273-278
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    • 1998
  • Belief network(or Bayesian network) based on Bayes' rule in probabilistic theory can be applied to the reasoning of diagnostic systems. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences.

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Weighted Fuzzy Reasoning Using Weighted Fuzzy Pr/T Nets (가중 퍼지 Pr/T 네트를 이용한 가중 퍼지 추론)

  • Cho, Sang-Yeop
    • The KIPS Transactions:PartB
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    • v.10B no.7
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    • pp.757-768
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    • 2003
  • This paper proposes a weighted fuzzy reasoning algorithm for rule-based systems based on weighted fuzzy Pr/T nets, where the certainty factors of the fuzzy production rules, the truth values of the predicates appearing in the rules and the weights representing the importance of the predicates are represented by the fuzzy numbers. The proposed algorithm is more flexible and much closer to human intuition and reasoning than other methods : $\circled1$ calculate the certainty factors using by the simple min and max operations based on the only certainty factors of the fuzzy production rules without the weights of the predicates[10] : $\circled2$ evaluate the belief of the fuzzy production rules using by the belief evaluation functions according to fuzzy concepts in the fuzzy rules without the weights of the predicates[12], because this algorithm uses the weights representing the importance of the predicates in the fuzzy production rules.

Knowledge Representation and Reasoning using Metalogic in a Cooperative Multiagent Environment

  • Kim, Koono
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.7
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    • pp.35-48
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    • 2022
  • In this study, it propose a proof theory method for expressing and reasoning knowledge in a multiagent environment. Since this method determines logical results in a mechanical way, it has developed as a core field from early AI research. However, since the proposition cannot always be proved in any set of closed sentences, in order for the logical result to be determinable, the range of expression is limited to the sentence in the form of a clause. In addition, the resolution principle, a simple and strong reasoning rule applicable only to clause-type sentences, is applied. Also, since the proof theory can be expressed as a meta predicate, it can be extended to the metalogic of the proof theory. Metalogic can be superior in terms of practicality and efficiency based on improved expressive power over epistemic logic of model theory. To prove this, the semantic method of epistemic logic and the metalogic method of proof theory are applied to the Muddy Children problem, respectively. As a result, it prove that the method of expressing and reasoning knowledge and common knowledge using metalogic in a cooperative multiagent environment is more efficient.

Auto Generation of Fuzzy Control Rule using Neural-Fuzzy Fusion (뉴럴-퍼지 융합을 이용한 퍼지 제어 규칙의 자동생성에 관한 연구)

  • Lim, Kwang-Woo;Kim, Yong-Ho;Kang, Hoon;Jeon, Hong-Tae
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.11
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    • pp.120-129
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    • 1992
  • In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

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A Design of the Expert System for Diagnosis of Abnormal Gait by using Rule-Based Representation (규칙처리 표현방식을 이용한 이상 보행용 전문가 시스템의 설계)

  • Lee, Eung-Sang;Lee, Ju-Hyeong;Lee, Myoung-Ho
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1329-1332
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    • 1987
  • This paper describes a design of the expert system for diagnosis of abnormal gait patients. This system makes the rule-based representation that can easily extend the knowledge-base and naturally represent the uncertainty, and the inference engine that uses forward chaining which covers the reasoning from the first condition to the goal. The results of inferring various maladies using this system are as follows: 1) In cases of progressive muscular dystrophy, cerebral vascular accident, peripheral neuropathic lesion and peroneal nerve injury, the result of inference is the same as that of medical specialists' with 100% accuracy. 2) In cases of Neuritis, Paralysis agitan and Brain tumor, the accuracy of inference is less than 50% compared to that of medical specialists. With above results, we decide that the rule-based representations of some maladies ard accurate relatively, but that the correction and the extention of some rules and some methods of problem solving are required in order to construct the complete expert system for diagnosis of abnormal gait patients.

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Fuzzy Belief Network : Approximate Reasoning System Using The Possiblity (Fuzzy Belief Network : 가능성을 이용한 근사추론 시스템)

  • 조상엽;김기태
    • Korean Journal of Cognitive Science
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    • v.4 no.1
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    • pp.261-294
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    • 1993
  • Most of expert systems,as a rule-based system,should be convenient to modify a rule and to insert a new rule, which is called modularity of rules. When we think correlated evidences in expert systems. conventional systems are too local to recognize the common origin of the information, and they would update the belief of the hypothesis as if it were supposed by independence soureces. In this paper to overcome such drawbacks we propose Fuzzy Belief Network which is based on the Beysian Network which provide the modulartiy between rules. To build Fuzzy Belief Network, we define nodes and links and propose algorithms for data fusion in individual node and for propagation belief value obtained as a result of data fusion.