• 제목/요약/키워드: Rule-Generation

검색결과 379건 처리시간 0.026초

오차를 고려한 송전선 보호 거리계전 정정룰에 대한 고찰 (Examination with Transmission Line Distance Relay Setting Rule Considering Error)

  • 조성진;최면송;현승호;김종욱;이주왕;조범섭;유영식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 A
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    • pp.12-15
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    • 2002
  • Korea Power System Protection Setting Rule was used from the rectify 1990's. Thereafter transmission voltage is raised the voltage into 765kV, and introduction to new technology of Power System, and was many of variation but, it is using. The present is using Digital type distance relay for 765kV transmission line protection. If impedance value of transmission line were to value lower than setting, this would be operating and relay setting rule is for 85% into Zone 1 self section, and Zone 2 is a 125%, Zone 3 is a 225%. Which's $15{\sim}25%$ include current transformer error 5%, potential transformer 5%, relay calculation error 5% and margin factor from the field experience. This paper is discussed transmission protective relay and relay setting rule of high voltage power system and we verify the correctness relay setting rule with distance relay using Matlab simulation.

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A Transformation-Based Learning Method on Generating Korean Standard Pronunciation

  • Kim, Dong-Sung;Roh, Chang-Hwa
    • 한국언어정보학회:학술대회논문집
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    • 한국언어정보학회 2007년도 정기학술대회
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    • pp.241-248
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    • 2007
  • In this paper, we propose a Transformation-Based Learning (TBL) method on generating the Korean standard pronunciation. Previous studies on the phonological processing have been focused on the phonological rule applications and the finite state automata (Johnson 1984; Kaplan and Kay 1994; Koskenniemi 1983; Bird 1995). In case of Korean computational phonology, some former researches have approached the phonological rule based pronunciation generation system (Lee et al. 2005; Lee 1998). This study suggests a corpus-based and data-oriented rule learning method on generating Korean standard pronunciation. In order to substituting rule-based generation with corpus-based one, an aligned corpus between an input and its pronunciation counterpart has been devised. We conducted an experiment on generating the standard pronunciation with the TBL algorithm, based on this aligned corpus.

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A Rule Merging Method for Fuzzy Classifier Systems and Its Applications to Fuzzy Control Rules Acquisition

  • Inoue, Hiroyuki;Kamei, Katsuari
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.78-81
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    • 2003
  • This paper proposes a fuzzy classifier system (FCS) using hyper-cone membership functions (HCMFs) and rule reduction techniques. The FCS can generate excellent rules which have the best number of rules and the best location and shape of membership functions. The HCMF is expressed by a kind of radial basis function, and its fuzzy rule can be flexibly located in input and output spaces. The rule reduction technique adopts a decreasing method by merging the two appropriate rules. We applay the FCS to a tubby rule generation for the inverted pendulum control.

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Development of a Knowledge Discovery System using Hierarchical Self-Organizing Map and Fuzzy Rule Generation

  • Koo, Taehoon;Rhee, Jongtae
    • 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.

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오차를 고려한 765kV 변압기 보호 계전 정정룰 고찰 (Investigation into Transformer Protective Relay Setting Rule Considering Error Ratio)

  • 배영준;이승재;최면송;강상희;김상태;최정이;정창현;유영식;조범섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 A
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    • pp.229-231
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    • 2002
  • The digital current differential relaying scheme is widely used for primary protection of 765(kV) power transformer. The current differential relay pickup the internal fault at the threshold which is set at 30% of rating current. Margin of 30% include current transformer error 5%, relay error 5%, on load tap changer error 7% and margin factor 140% obtained from the field experience. In this paper transformer protection relay and relay setting rule of high voltage power system are discussed. And we verify the correctness of relay setting rule with current differential relay using Matlab simulation.

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유전자알고리즘을 이용한 탐색공간분할 학습방법에 의한 규칙 생성 (Rule Generation by Search Space Division Learning Method using Genetic Algorithms)

  • 장수현;윤병주
    • 한국정보처리학회논문지
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    • 제5권11호
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    • pp.2897-2907
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    • 1998
  • 학습 예(training examples)로 부터 규칙을 생성하는 문제는 큰 탐색 공간상에서 많은 지역최소치를 가지고 있는 최적화 문제로 귀결되므로 복잡하고 어려운 문제로 알려져 있다. 이러한 생성규칙을 만들기 위한 여러 가지 학습방법들이 제안되었으며, 그 중 한가지 학습방법이 유전자알고리즘을 연산모델로 사용하는 것이다. 그러나 전통적인 유전자알고리즘은 전역해 부근에서 수렴속도가 떨어지고, 추출된 규칙의 효율성에 문제가 있다. 본 논문에서는 유전자알고리즘의 학습과정에서 포착되는 염색체의 스키마를 분석하여 탐색공간을 부분해(subsolution)를 구할 수 있는 공간들로 분할함으로써, 보다 일반화된 분류 규칙집합을 찾는 방법을 제안하였다. 또한, 실험을 통하여 기존의 기계학습 방법을 사용한 경우와 효율을 상호 비교하여 제안한 방법을 타당성을 입증하였다.

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올바른 연관성 규칙 생성을 위한 의사결정과정의 제안 (Decision process for right association rule generation)

  • 박희창
    • Journal of the Korean Data and Information Science Society
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    • 제21권2호
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    • pp.263-270
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    • 2010
  • 데이터마이닝은 방대한 양의 데이터 속에서 쉽게 드러나지 않는 유용한 정보를 체계적이고도 자동적으로 찾아내는 기법이다. 데이터마이닝의 중요한 목표 중의 하나는 여러 변수들 간의 관계를 발견하고 결정하는 것이다. 연관성 규칙은 항목 집합으로 표현된 트랜잭션에서 각 항목간의 연관성을 반영하는 규칙으로서, 항목 집합간의 관계를 지지도, 신뢰도, 순수 신뢰도 등과 같은 흥미도 측도에 의해 명확히 수치화함으로써 두 개 이상의 항목집합간의 관련성을 표시해주기 때문에 현업에서 많이 활용되고 있다. 본 논문에서는 기존에 많이 활용되고 있는 흥미도 측도인 신뢰도와 순수 신뢰도의 문제점을 보완하여 연관성 규칙을 올바르게 생성하기 위한 새로운 의사결정과정을 제안하고자 한다. 본 논문에서 제안하는 의사결정과정은 특히 스트리밍 데이터베이스에서의 연관성 규칙을 탐색하는 데 효율적이다.

차세대 웹을 위한 SWRL 기반 역방향 추론엔진 SMART-B의 개발 (Development of an SWRL-based Backward Chaining Inference Engine SMART-B for the Next Generation Web)

  • 송용욱;홍준석;김우주;윤숙희;이성규
    • 지능정보연구
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    • 제12권2호
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    • pp.67-81
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    • 2006
  • 현재의 웹이 HTML을 바탕으로 인간 사용자와의 인터페이스에 초점을 맞추고 있는데 비하여, 차세대 웹은 XML 및 XML 기반 각종 표준들을 바탕으로 소프트웨어 에이전트간의 상호작용에 초점을 맞추어 나가고 있다. 차세대 웹에서 소프트웨어 에이전트의 두뇌 역할을 수행하기 위하여 추론엔진은 차세대 웹의 표준 언어인 시맨틱 웹 - (Semantic Web)을 충실히 이해할 수 있어야 한다. 이를 위한 기초 작업의 일환으로 OWL(Web Ontology Language) 과 RuleML(Rule Markup Language)을 조합한 SWRL(Semantic Web Rule Language)이 W3C에 제안된 바 있다. 본 연구에서는 SWRL을 규칙 표현 방법으로 사용하고, OWL을 사실 표현 방법으로 사용하는 역방향 추론엔진인 SMART-B(SeMantic web Agent Reasoning Tools -Backward chaining inference engine)를 개발하고자 하였다. 이를 위하여 SWRL 기반 역방향 추론을 위한 요구 기능을 분석하고, 기존 역방향 추론 알고리즘에 차세대 시맨틱 웹의 요구 기능을 반영한 역방향 추론 알고리즘을 설계하였다. 또한, 유비쿼터스 환경에서의 각종 플랫폼간의 독립성과 이식성을 확보하고 기기간의 성능 차이를 극복할 수 있도록 사실 베이스 및 규칙 베이스의 관리도구와 역방향 추론 엔진 등을 Java 프로그래밍 언어를 이용하여 단위 컴포넌트의 형태로 개발하였다.

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전력계통의 단기 발전계획 기원용 전문가시스템 (An Expert System for Short-Term Generation Scheduling of Electric Power Systems)

  • Yu, In-Keun
    • 대한전기학회논문지
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    • 제41권8호
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    • pp.831-840
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    • 1992
  • This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

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초상화로봇을 위한 표정 변환 및 드로잉규칙 생성 (Facial Expression Transformation and Drawing Rule Generation for the Drawing Robot)

  • 김문상;민선규;최창석
    • 대한기계학회논문집
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    • 제18권9호
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    • pp.2349-2357
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    • 1994
  • This paper presents a facial expression transformation algorithm and drawing rule generation algolithm for a portrait drawing robot which was developed for the '93 Taejeon EXPO. The developed algorithm was mainly focused on the robust automatic generation of robot programs with the consideration that the drawing robot should work without any limitation of the age, sex or race for the persons. In order to give more demonstratin effects, the facial expression change of the pictured person was performed.