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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2009.8
- 수록면
- 3,468 - 3,473 (6page)
이용수
초록· 키워드
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In this paper, a method of time-related classas sociation rule mining is proposed based on Genetic Network Programming(GNP) combined with Estimation of Distribution Algorithms(EDAs). The reare two important points in this paper: The first important point is to combine GNP with Estimation of Distribution Algorithms which are a novel evolution strategy. The second important point is that three kinds of probability models have been put for ward for generating new individuals. The aim of this paper is to extract more interesting association rules and to improve the traffic prediction accuracy by combining Genetic Network Proramming with Estimation of Distribution Algorithms. We applied the proposed data mining algorithm to traffic system sin order to predict the traffic volume in future. The simulation results show that our proposed method is effective compared with the conventional method based on GNP.
목차
Abstract
1.INTRODUCTION
2.GENETIC NETWOR KPROGRAMMING
3.ESTIMATION OF DISTRIBUTION ALGORITHMS
4.ASSOCIATION RULES MINING
5.SIMULATION
6.CONCLUSION
REFERENCES
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