Traffic Flow Prediction of BP Neural Network Optimized by Artificial Bee Colony Algorithm
LI Wenyue
ZHOU Siyuan
PANG Jingcheng
Abstract：The analysis and prediction model of the urban road short-term traffic flow is established based on a neural network optimized by the Artificial Bee Colony Algorithm.The thresholds and weights of the neural network are optimized by the Artificial Bee Colony Algorithm.Taking the time characteristic of the traffic flow into account, the historical traffic flow is used as the training sample to predict the traffic flow of a day.The contrast of stimulation tests of multi-algorithms shows that the prediction results based on ABC-BP are more accurate than those based on the traditional BP neural network, the wavelet neural network and PSO-BP neural network.
Keywords：Artificial Bee Colony AlgorithmBackPropagation neural networktraffic flow predictionsimulation
Publication Date：2017-01-01
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：6( 34-39 )