지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.11 No.3
- 발행연도
- 2011.9
- 수록면
- 135 - 142 (8page)
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초록· 키워드
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Unlike using the sequence-based representation for a chromosome in previous genetic algorithms for Bayesian structure learning, we proposed a matrix representation-based genetic algorithm. Since a good chromosome representation helps us to develop efficient genetic operators that maintain a functional link between parents and their offspring, we represent a chromosome as a matrix that is a general and intuitive data structure for a directed acyclic graph(DAG), Bayesian network structure. This matrix-based genetic algorithm enables us to develop genetic operators more efficient for structuring Bayesian network: a probability matrix and a transpose-based mutation operator to inherit a structure with the correct edge direction and enhance the diversity of the offspring. To show the outstanding performance of the proposed method, we analyzed the performance between two well-known genetic algorithms and the proposed method using two Bayesian network scoring measures.
목차
Abstract
1. Introduction
2. The Proposed Method
3. Experiments
4. Conclusions
References
참고문헌 (23)
참고문헌 신청
Judea Pearl / 1989 / Probability Reasoning in intelligent systems; Networks of Plausible Inference / Morgan Kaufmann Publishers
Gregory F.Cooper / 1992 / A Bayesian Method for the Induction of Probabilistic Networks from Data / Machine Learning 9(4):309~347
Steffen L.Lauritzen / 1988 / Local Computations with Probabilitities on Graphical Structures and Their Application to Expert Systems / Journal of the Royal Statistical Society.Series B(Methodological) 50(2):157~224
Edward Herskovits / 1990 / Kutato:An Entropy-Driven System for Construction of Probabilistic Expert Systems from Databases
Remco R.Bouckaert / 1993 / Probabilistic Network Construction Using the Minimum Description Length Principle / Lecture Notes in Computer Science :41~48
Gregory F.Cooper / 1992 / A Bayesian Method for the Induction of Probabilistic Networks from Data / Machine Learning 9(4):309~347
Steffen L.Lauritzen / 1988 / Local Computations with Probabilitities on Graphical Structures and Their Application to Expert Systems / Journal of the Royal Statistical Society.Series B(Methodological) 50(2):157~224
Edward Herskovits / 1990 / Kutato:An Entropy-Driven System for Construction of Probabilistic Expert Systems from Databases
Remco R.Bouckaert / 1993 / Probabilistic Network Construction Using the Minimum Description Length Principle / Lecture Notes in Computer Science :41~48
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