SVR with hybrid chaotic genetic algorithm for short-term traffic flow forecasting

Abstract

Accurate forecast of traffic flow is crucial to effective and proactive traffic management systems in the context of intelligent transportation systems and dynamic traffic assignment. This paper presents an application of a supervised statistical learning technique called support vector regression (SVR) with hybrid chaotic genetic algorithm (CGAs) for urban… (More)
DOI: 10.1109/ICNC.2012.6234768

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