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The Development of Genetic Fuzzy System for Estimating Link Traveling Speed  

Youn, Yeo-Hun (Department of Industrial Systems and Information Engineering, Korea University)
Lee, Hong-Chul (Department of Industrial Systems and Information Engineering, Korea University)
Kim, Yong-Sik (Department of Industrial Systems and Information Engineering, Korea University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.29, no.1, 2003 , pp. 32-40 More about this Journal
Abstract
In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.
Keywords
genetic fuzzy; genetic algorithm; case base reasoning;
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