Prediction for Traffic Flow of BP Neural Network based on DE Algorithm

Yue Hou; Hai Yan Li

doi:10.4028/www.scientific.net/AMR.671-674.2951

Paper Titles

Study on Layout Planning of Transfer Hub Integration of Urban Passenger Transit
p.2928

The Characteristic of Viewpoint’s Time-Transients in Traffic Operation
p.2937

The Design of Intelligent Street Lighting Control System
p.2941

Traffic Parameters Prediction Method Based on Rolling Time Series
p.2946

Prediction for Traffic Flow of BP Neural Network based on DE Algorithm
p.2951

The Research of Optimal Allocation of Port Berth and Quay Crane Based on Heuristic Algorithm
p.2956

Analysis on Important Parameters Design of Aircraft
p.2961

Study on Safety Evacuation Time for Passengers in Subway Station and Its Application
p.2965

An Automated Progress Tracking System for Industrial Facility Construction Projects
p.2973

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 671-674Prediction for Traffic Flow of BP Neural Network...

Prediction for Traffic Flow of BP Neural Network based on DE Algorithm

Abstract:

A prediction algorithm for traffic flow prediction of BP neural based on Differential Evolution(DE) is proposed to overcome the problems such as long computing time and easy to fall into local minimum by combing DE and neural network . In the algorithm, DE is used to optimize the thresholds and weights of BP neural network, and the BP neural network is used to search for the optimal solution. The efficiency of the proposed prediction method is tested by the simulation of real traffic flow. The simulation results show that the proposed method has higher precision compared with the traditional BP neural network，so prove it is feasible and effective in the practical prediction of traffic flow.