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نویسنده(ها)

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محل انتشار

سیزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک

اطلاعات انتشار

سال

Short–term traffic flow forecasting is a critical function in advanced trafficmanagement systems (ATMS) and advanced traveler information systems(ATIS). Accurate forecasting results are useful to indicate future trafficconditions and assist traffic managers in seeking solutions to congestionproblems on urban freeways and surface streets. In this paper, in order to realizeeffective and efficient traffic forecasting, a traffic flow short–time forecastingmodel is presented based on wavelet neural network(WNN). Compared withother methods, it possesses the advantages of low computational complexity, fastconvergence speed, high goodness–of–fit and so on. Simulation results prove thevalidity of this prediction model and show Wavelet neural network has highconvergence speed and forecasting precision.<\div>

راهنمای دریافت مقاله‌ی «Traffic Flow Forecasting at IntersectionBased on Wavelet Neural Network» در حال تکمیل می‌باشد.

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