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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages3457-3462
Number of pages6
Publication statusPublished - 2009
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka
Duration: 2009 Aug 182009 Aug 21

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
CityFukuoka
Period09/8/1809/8/21

Keywords

  • Estimation of Distribution Algorithms (EDAS)
  • Genetic Network Programming (GNP)
  • Time-related association rule mining

ASJC Scopus subject areas

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

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  • Cite this

    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. In ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 3457-3462). [5334374]