Genetic network programming with estimation of distribution algorithms and its application to association rule mining for traffic prediction

Xianneng Li, Shingo Mabu, Huiyu Zhou, Kaoru Shimada, Kotaro Hirasawa

研究成果: Conference contribution

9 引用 (Scopus)

抜粋

In this paper, a novel evolutionary paradigm combining Genetic Network Programming (GNP) and Estimation of Distribution Algorithms (EDAs) is proposed and used to find important association rules in time-related applications, especially in traffic prediction. GNP is one of the evolutionary optimization algorithms, which uses directed-graph structures. EDAs is a novel algorithm, where the new population of individuals is produced from a probabilistic distribution estimated from the selected individuals from the previous generation. This model replaces random crossover and mutation to generate offspring. Instead of generating the candidate association rules using conventional GNP, the proposed method can obtain a large number of important association rules more effectively. The purpose of this paper is to compare the proposed method with conventional GNP in traffic prediction systems in terms of the number of rules obtained.

元の言語English
ホスト出版物のタイトルICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
ページ3457-3462
ページ数6
出版物ステータスPublished - 2009
イベントICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka
継続期間: 2009 8 182009 8 21

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Fukuoka
期間09/8/1809/8/21

    フィンガープリント

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

これを引用

Li, X., Mabu, S., Zhou, H., Shimada, K., & Hirasawa, K. (2009). Genetic network programming with estimation of distribution algorithms and its application to association rule mining for traffic prediction. : ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 3457-3462). [5334374]