چکیده مقاله
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
کلیدواژهها
نویسندگان
M Yaghoubi
M Yaghoubi is with the Department of Electrical Engineering at Amirkabir University of Technology, Hafez Ave Tehran Iran Author's phone Number
A Afshar
Department of Electrical Engineering, Amirkabir University of Technology, Hafez Ave
شیوه ارجاع
Yaghoubi, M and Afshar, A,1392,Traffic Flow Forecasting at IntersectionBased on Wavelet Neural Network,The 13th International Conference on Traffic and Transportation Engineering,Tehran
ارائهشده در
مجموعه مقالات سیزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک6 اسفند 1392 · تهران