Spatial Interpolation of Traffic Data by Genetic Fuzzy System
説明
We propose a method to interpolate traffic data of roads using genetic fuzzy systems (GFSs). In Japan, car navigation equipment provides drivers with real-time traffic information about principal roads. The information enables giving route guidance. In a previous study, the problem of the method lies in the following two facts because a human designs membership functions of fuzzy c-means (FCM) experientially. One fact is that the design cost is high; the other is that tuning membership functions optimally is difficult. We automatically tune membership functions using a genetic algorithm (GA). The membership functions are encoded as a chromosome of GA, and the average of mean daily errors calculated from actual traffic data is used as a fitness function. Experiments using actual traffic data and an actual road map indicate that our method is more effective than the conventional method.
収録刊行物
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- 2006 International Symposium on Evolving Fuzzy Systems
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2006 International Symposium on Evolving Fuzzy Systems 280-285, 2006-09-01
IEEE