Backward time related association rule mining in trafficprediction using genetic network programming withdatabase rearrangement

Huiyu Zhou, S. Mabu, K. Shimada, K. Hirasawa
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Abstract

In this paper, we introduce Backward Time Related Association Rule Mining using Genetic Network Programming (GNP) with Database Rearrangement in order to find time related sequential association from time related databases effectively and efficiently. The proposed algorithm and experimental results are described using a traffic prediction problem.
数据库重排遗传网络规划在交通预测中的后向关联规则挖掘
为了从时间相关的数据库中高效地发现时间相关的顺序关联,本文引入了基于数据库重排的遗传网络规划(GNP)的倒向时间相关关联规则挖掘。利用一个流量预测问题描述了该算法和实验结果。
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