Prediction Models of Short-Term Traffic Flow Based on Neural Network

Chao Jun Dong; Ang Cui

doi:10.4028/www.scientific.net/AMR.671-674.2908

Paper Titles

Evaluation for BRT Operation Effect Based on Dynamic Bayesian Networks
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Hierarchical Regression Model for Truck Collision Severity Analysis
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Intelligent Vehicle Navigation System Based on Multi-Visual Cognition Information
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Passenger Traffic Plaza Layout Planning Research under the Influence of Integration in City
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Prediction Models of Short-Term Traffic Flow Based on Neural Network
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Research of Air Traffic Flow Forecasts Based on BP Neural Network
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Evaluation on Leading Order Vortex Decay behind an Aircraft Using an Analytical Model
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Research on the Integrated Planning of Urban Passenger Transit Network
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Study on Layout Planning of Transfer Hub Integration of Urban Passenger Transit
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Prediction Models of Short-Term Traffic Flow Based on Neural Network

Abstract:

For the city’s road conditions, a nonlinear regression prediction model based on BP Neural Network was built. The simulation shows it has good adaptability and strong nonlinear mapping ability. Using the wavelet basis function as hidden layer nodes transfer function, a BP-Neural- Network-topology-based Wavelet Neural Network model was proposed. The model can overcome the defects of the BP Neural Network model that easy to fall into local minimum and cannot perform global search. The feasibility of the model was proved using measured data from yingbin avenue in jiangmen city.