A Hybrid Method for Short-Term Traffic Congestion Forecasting Using Genetic Algorithms and Cross Entropy.
IEEE Transactions on Intelligent Transportation Systems(2016)
摘要
This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based systems (FRBSs). It is a hybridization of a genetic algorithm (GA) and the cross-entropy (CE) method, which is here called GACE. It is used to predict congestion in a 9-km-long stretch of the I5 freeway in California, with time horizons of 5, 15, and 30 min. A comparative study of different levels of hybridi...
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关键词
Genetic algorithms,Fuzzy logic,Traffic control,Artificial neural networks,Forecasting,Entropy,Predictive models
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