Generalized Time Related Sequential Association Rule Mining and Traffic Prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Zhou:2009:cec,

• author = "Huiyu Zhou and Shingo Mabu and Kaoru Shimada and Kotaro Hirasawa",
• title = "Generalized Time Related Sequential Association Rule Mining and Traffic Prediction",
• booktitle = "2009 IEEE Congress on Evolutionary Computation",
• year = "2009",
• editor = "Andy Tyrrell",
• pages = "2654--2661",
• address = "Trondheim, Norway",
• month = "18-21 " # may,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-2959-2",
• file = "P045.pdf",
• DOI = "doi:10.1109/CEC.2009.4983275",
• abstract = "Time Related Association rule mining is a kind of sequence pattern mining for sequential databases. In this paper, we introduce a method of Generalized Association Rule Mining using Genetic Network Programming (GNP) with time series processing mechanism in order to find time related sequential rules efficiently. GNP represents solutions as directed graph structures, thus has compact structure and implicit memory function. The inherent features of GNP make it possible for GNP to work well especially in dynamic environments. GNP has been applied to generate time related candidate association rules as a tool using the database consisting of a large number of time related attributes. The aim of this algorithm is to better handle association rule extraction from the databases in a variety of time-related applications, especially in the traffic volume prediction problems. The generalized algorithm which can find the important time related association rules is described and experimental results are presented considering a traffic prediction problem.",
• keywords = "genetic algorithms, genetic programming, genetic network programming, directed graph structure, genetic network programming, road network, sequence pattern mining, sequential database, time related association rule mining, time series processing mechanism, traffic volume prediction problem, data mining, directed graphs, road traffic, time series, traffic engineering computing",
• notes = "CEC 2009 - A joint meeting of the IEEE, the EPS and the IET. IEEE Catalog Number: CFP09ICE-CDR. Also known as \cite{4983275}",

}

Genetic Programming entries for Huiyu Zhou Shingo Mabu Kaoru Shimada Kotaro Hirasawa

Citations