• 한국지능시스템학회논문지
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• 제12권5호
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• pp.405-410
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• 2002

본 논문은 수학적으로 모델링하기 어려운 비선형 시스템을 위한 새로운 계층적 규칙 기반 퍼지 시스템 모델링 기법을 제안한다. 제안된 기법은 퍼지 규칙 기반 구조를 상위 규칙 기반과 하위 규칙 기반으로 나누어 계층화시키는 새로운 모델링 방법이다. 본 논문에서 제안한 계층적 퍼지 규칙을 적용함으로써 퍼지 규칙을 효율적이고 논리적으로 이용할 수 있음은 물론, 퍼지 규칙의 효율적, 논리적 사용은 퍼지 시스템의 정확성을 높일 수 있고 구조를 명료화시킬 수 있음을 보인다. 유전알고리즘은 제안된 퍼지 규칙의 파라미터 최적화 과정에 이용된다. 마지막으로, 복잡한 비선형 시스템에 대한 퍼지 모델링 결과를 통해서 제안된 기법의 타당성 및 효용성을 검증하고 타 기법의 결과와 비교한다.

• 한국정보처리학회논문지
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• 제5권8호
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• pp.2075-2082
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• 1998

규칙 기반 지식표현은 전문가 시스템의 지식을 저장하고 조작하는 기법중 가장 많이 사용되는 기법이다. 그런데 이 방법으로 표현된 지식의 양은 점점 많아지며, 그 관계가 복잡해지고 내용이 변경될 수 있기 때문에 지식베이스의 일관성 및 완결성을 유지하는 검증 시스템이 필요하다. 따라서 본 논문에서는 새로운 규칙이 첨가될 때 야기될 수 있는 오류를 구조적 측면과 의미론적 측면에서 검증한 후 자체 수정하거나 자체 수정이 불가능할 경우 전문가가 수정하도록 하여 일관성과 완결성이 확증된 후 새로운 규칙이 추가되어질 수 있도록 함으로써 전문가 시스템의 신뢰도를 높이고 효율성을 제고할 수 있는 검증시스탬이 제안되었다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전력기술부문
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• pp.255-257
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• 2007

Korea electricity market consists of two payment systems, capacity and energy. Capacity payments are given to the generators according to its hourly availability considering hourly and seasonal weighting factors. Energy payments are settled at the marginal generation cost based on generator variable cost. In 2007, base load energy market is closed and single capacity payment system is begun to apply in electricity market. In this revised market rule, energy price cap for base load generators is newly introduced. We analyze impact of market rule revision in 2007 on base load generators and suggest improvement scheme to enforce market system in this study.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1111-1116
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• 1993

In this study, we discuss the design of the expert system for the scheduling of the FMC(Flexible Manufacturing Cell) consisting of the several versatile machines. Due to the NP property, the scheduling problem of several machine FMC is very complex task. Thus we proposed the two heuritstic shceduling algorithms for solving the problem and constituted the algorithm based of solving the problem and constituted the algorithm base of ISS(Intelligent Scheduling System) using them. By the rules in the rule base, the best alternative among various algorithms in algorithm base is selected and applied in controlling the FMC. To show the efficiency of ISS, the scheduling output of ISS and the existent dynamic dispatching rule were tested and compared. The results indicate that the ISS is superior to the existent dynamic dispatching rules in various performance indexes.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.153-156
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• 2005

In this paper, a framework for implementing UFIS (Unified Fuzzy rule-based knowledge Inference System) is presented. First, fuzzy clustering and fuzzy rules deal with the presence of the knowledge in DB (DataBase) and its value is presented with a value between 0 and 1. Second, RDB (Relational DB) and SQL queries provide more flexible functionality fur knowledge management than the conventional non-fuzzy knowledge management systems. Therefore, the obtained fuzzy rules offer the user additional information to be added to the query with the purpose of guiding the search and improving the retrieval in knowledge base and/ or rule base. The framework can be used as DM (Data Mining) and ES (Expert Systems) development and easily integrated with conventional KMS (Knowledge Management Systems) and ES.

• 상하수도학회지
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• 제21권2호
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• pp.215-224
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• 2007

The purpose of this study was to estimates water supply reliability indices of the water supply by Allocation Rules(AR) for parallel reservoirs. Rule (A) can be considered it as only current storage, Rule(B) can be considered it as current storage and inflow and Rule(C) can be considered it as current storage, inflow and water supply capacity. First, conditions of water supply are divided by Condition I for the monthly constant water supply and Condition II for the monthly varied water supply. Second, results of allocation coefficients are revealed the smallest different at Rule(C). The analysis of water supply showed that the capability of water supply is superior to the Rule(B), it is superior to the Rule(C) on the base of the balance of water supply. The reliability analysis was highly showed at the Rule(B) and Rule(C). A methodology for the analysis of water supply was developed and applied to the parallel reservoir system from this research, The operation rule for the parallel reservoir can be slightly modified and successfully applied to the different kinds of the parallel reservoir system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.579-583
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• 1991

A fuzzy logic controller with rule modification capability is proposed to overcome the difficulty of obtaining control rules from the human operators. This new SOC algorithm modifies control rules by a fuzzy inference machine utilizing data base. Computer simulation results show good performances on both a linear system and a nonlinear system.

• 한국경영과학회지
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• 제30권2호
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• pp.185-199
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• 2005

With the growth of internet shopping malls, there is increasing interest in comparison shopping mall. However most comparison sites compare only book prices by collecting simple XML data and do not provide .the exact comparison Including precise shipping costs. Shipping costs vary depending on each customer's address, the delivery method, and the category of selected goods, so rule based system is required in order to calculate exact shipping costs. Therefore, we designed and implemented comparison shopping mall which compares not only book prices but also shipping costs using rule based inference. By adopting the extensible Rule Markup language (XRML) approach, we proposed the methodology of extracting delivery rules from Web pages of each shopping mall. The XRML approach can facilitate nearly automatic rule extraction from Web pages and consistency maintenance between Web pages and rule base. We developed a ConsiderD system which applies our rule acquisition methodology based on XRML. The objective of the ConsiderD system is to compare the exact total cost of books including the delivery cost over Amazon.com, BarnesandNoble.com, and Powells.com. With this prototype, we conducted an experiment to show the potential of automatic rule acquisition from Web pages and illustrate the effect of delivery cost.

• 한국경영과학회지
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• 제25권4호
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• pp.81-95
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• 2000

A knowledge-based system with fuzzy production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of real system when we make inferences with a knowledge-based system. This paper proposes a strategy of dynamic inferencing for a knowledge-based system with fuzzy production rules. The strategy suggested in this paper applies weights of attributes of conditions of a rule in the knowledge-base. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by AHP(Analytic Hierarcy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with MIN operator, into a single DM for the rule. In this way, overall DM for a rule changes depending on the importance of attributes of the rule. As a result, the dynamic nature of a real system can be incorporated in an inference with fuzzy production rules.