A forecast method for trip production based on BP neural network

Abstract:

Trip production forecast is one of key components of traffic demand analysis,which directly determines the scale and layout of different urban traffic facilities.The mechanism of artificial neural network (ANN) and influential factors of trip production were analyzed.therefore,a four-layer back-propagation neural network (BP neural network) model was set up to forecast the trip production,in which the input neurons are land-uses of different traffic zones and the output is trip production.Meanwhile,the model was calibrated and testified with traffic survey data from the urban integrative transportation planning of Ganzhou city.Furthermore,the results were compared with those obtained from trip production rate method and multiple linear regression method,It is showed that forecast precision of the BP neural network is relatively high.