• 제목/요약/키워드: Minimal set of decision rules

검색결과 9건 처리시간 0.025초

Rough Set-based Incremental Inductive Learning Algorithm Theory and Applications

  • Bang, Won-Chul;Z. Zenn Bien
    • 한국지능시스템학회논문지
    • /
    • 제11권7호
    • /
    • pp.666-674
    • /
    • 2001
  • Classical methods to find a minimal set of rules based on the rough set theory are known to be ineffective in dealing with new instances added to the universe. This paper introduces an inductive learning algorithm for incrementally retrieving a minimal set of rules from a given decision table. Then, the algorithm is validated via simulations with two sets of data, in comparison with a classical non-incremental algorithm. The simulation results show that the proposed algorithm is effective in dealing with new instances, especially in practical use.

  • PDF

Rough Set 이론을 이용한 연역학습 알고리즘 (Inductive Learning Algorithm using Rough Set Theory)

  • 방원철;변증남
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
    • /
    • pp.331-337
    • /
    • 1997
  • In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general descriptions of concepts from specific instances of these concepts. In many real life situations however new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overall set of instances. The method of learning presented here is based on a rough set concept proposed by Pawlak[2]. It is shown an algorithm to fund minimal set of rules using reduct change theorems giving criteria for minimum recalculation and an illustrative example.

  • PDF

Rule Induction Considering Implication Relations Between Conclusions

  • Inuiguchi, Masahiro;Inoue, Masanori;Kusunoki, Yoshifumi
    • Industrial Engineering and Management Systems
    • /
    • 제10권1호
    • /
    • pp.65-73
    • /
    • 2011
  • In rough set literatures, methods for inducing minimal rules from a given decision table have been proposed. When the decision attribute is ordinal, inducing rules about upward and downward unions of decision classes is advantageous in the simplicity of obtained rules. However, because of independent applications of the rule induction method, inclusion relations among upward/downward unions in conclusion parts are not inherited to the condition parts of obtained rules. This non-inheritance may debase the quality of obtained rules. To ensure that inclusion relations among conclusions are inherited to conditions, we propose two rule induction approaches. The performances of the proposed approaches considering the inclusion relations between conclusions are examined by numerical experiments.

INCREMENTAL INDUCTIVE LEARNING ALGORITHM IN THE FRAMEWORK OF ROUGH SET THEORY AND ITS APPLICATION

  • Bang, Won-Chul;Bien, Zeung-Nam
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
    • /
    • pp.308-313
    • /
    • 1998
  • In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general description of concepts from specific instances of these concepts. In many real life situations, however, new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overcall set of instances. The method of learning presented here is base don a rough set concept proposed by Pawlak[2][11]. It is shown an algorithm to find minimal set of rules using reduct change theorems giving criteria for minimum recalculation with an illustrative example. Finally, the proposed learning algorithm is applied to fuzzy system to learn sampled I/O data.

  • PDF

An Application of the Rough Set Approach to credit Rating

  • Kim, Jae-Kyeong;Cho, Sung-Sik
    • 한국지능정보시스템학회:학술대회논문집
    • /
    • 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
    • /
    • pp.347-354
    • /
    • 1999
  • The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

  • PDF

CAM에서의 사례의존규칙을 이용한 실시간 일정계획 (Real Time Scheduling for Computer-Aided Manufacturing ( CAM ) Systems with Instance-Based Rules)

  • 이종태
    • 대한산업공학회지
    • /
    • 제17권2호
    • /
    • pp.63-74
    • /
    • 1991
  • An expert scheduling system on real time basis for computer-aided manufacturing systems has been developed. In developing expert scheduling system, the most time-consuming job is to obtain rules from expert schedulers. An efficient process of obtaining rules directly form the schedules produced by expert schedulers is proposed. By the process, a set of complete and minimal set of rules is obtained. During a real time scheduling, when given information on possible values of elements, the rules produce possible values of decision elements, where logical explanations of the result may be offered in terms of chaining rules. The learning and scheduling processes have been simulated with an automated manufacturing line engaged in the production of circuit boards.

  • PDF

다중 에이전트 기반의 고대 국가 형성 시뮬레이션 (The Multi-Agent Simulation of Archaic State Formation)

  • S. Kim;A. Lazar;R.G. Reynolds
    • 한국시뮬레이션학회:학술대회논문집
    • /
    • 한국시뮬레이션학회 2003년도 춘계학술대회논문집
    • /
    • pp.91-100
    • /
    • 2003
  • In this paper we investigate the role that warfare played In the formation of the network of alliances between sites that are associated with the formation of the state in the Valley of Oaxaca, Mexico. A model of state formation proposed by Marcos and Flannery (1996) is used as the basis for an agent-based simulation model. Agents reside in sites and their actions are constrained by knowledge extracted from the Oaxaca Surface Archaeological Survey (Kowalewski 1989). The simulation is run with two different sets of constraint rules for the agents. The first set is based upon the raw data collected in the surface survey. This represents a total of 79 sites and constitutes a minimal level of warfare (raiding) in the Valley. The other site represents the generalization of these constraints to sites with similar locational characteristics. This set corresponds to 987 sites and represents a much more active role for warfare in the Valley. The rules were produced by a data mining technique, Decision Trees, guided by Genetic Algorithms. Simulations were run using the two different rule sets and compared with each other and the archaeological data for the Valley. The results strongly suggest that warfare was a necessary process in the aggregations of resources needed to support the emergence of the state in the Valley.

  • PDF

러프집합과 계층적 분류구조를 이용한 데이터마이닝에서 분류지식발견

  • 이철희;서선화
    • 한국지능시스템학회논문지
    • /
    • 제12권3호
    • /
    • pp.202-209
    • /
    • 2002
  • 본 논문은 제어 시스템에서 규칙기반과 데이터 마이닝에서의 분류규칙의 명료함에 대해 다룬다. 대용량의 데이터로부터 유용한 정보를 얻어내는 데이터 마이닝은 중요한 이슈가 되고 있다. 인공지능에 기반을 둔 데이터 마이닝 분류기법에는 신경망, 의사결정나무 등 여러가지가 있지만 그 결과는 명확하고 이해하기 쉽고 분류규칙이 간단명료해야 한다. 러프집합이론은 불충분하고 비일관적인 데이터로부터 의미있는 지식을 추출하는데 효과적인 기법이고, 다양한 속성들을 효과적으로 사용함으로써 분류와 근사화에 대한 좋은 해법을 제시한다. 본 논문에서는 러프집합이론의 근사화를 이용하여 알갱이 속에 숨겨져 있는 지식들을 찾아내는데 있어 효과적인 접근을 하였으며, 최상위 레벨에 코어를 적용하여 계층적 분류를 함으로써 대량의 데이터를 효율적으로 처리할 수 있도록 하였다. 제안된 분류방법은 정보시스템의 해석을 용이하게 하고 최소의 분류규칙을 만든다.

중첩 초음파 센서 링의 성능 평가, 최적 설계 및 복합 장애물 탐지 (Performance Evaluation, Optimal Design and Complex Obstacle Detection of an Overlapped Ultrasonic Sensor Ring)

  • 김성복;김현빈
    • 융합신호처리학회논문지
    • /
    • 제12권4호
    • /
    • pp.341-347
    • /
    • 2011
  • 본 논문에서는 유효 빔 폭 개념을 새로이 도입하여 중첩 초음파 센서 링의 성능 평가, 최적 설계, 그리고 복합 장애물 탐지에 대해 기술하도록 한다. 일군의 동종 저지향성 초음파 센서들이 반경이 영이 아닌 원주 상에 일정 간격으로 상호 빔 폭이 중첩되도록 배치된다고 가정한다. 첫째, 중첩 초음파 센서 링의 전역 위치 불확실성을 전체 장애물 탐지 범위 내에서의 국부적 위치 불확실성의 평균값으로 나타낸다. 중첩 초음파 센서 링의 유효 빔 폭을 동일한 전역 위치 불확실성을 갖는 단일 초음파 센서의 빔 폭으로 산정하고 이를 바탕으로 정규화된 장애물 탐지 성능 평가 지수를 정의한다. 둘째, 정의된 성능 평가 지수를 이용하여 장애물 탐지 시 위치 불확실성이 최소화되도록 중첩 초음파 센서 링의 설계 사양을 최적화한다. 주어진 초음파 센서의 사용 개수에 대한 중첩 초음파 센서 링의 최적 반경 그리고 주어진 중첩 초음파 센서 링의 반경에 대한 초음파 센서의 최적 사용 개수를 결정한다. 셋째, 3개의 인접 초음파 센서로부터의 장애물 거리 간의 대소 관계에 의거한 복수 장애물의 위치 불확실성 영역 판정 기준을 제시한다. 제시된 위치 불확실성 영역판정 기준을 이용하여 다양한 형태의 장애물로 구성된 복합 장애물 환경에서의 장애물 윤곽 추출 결과를 보인다.