A hybrid neural network and freight volumes application

Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local minimum, the genetic algorithm and simulated annealing algorithm with the overall search capability have been put forward to optimize authority value and threshold value of BP nerve network. In this paper, a new neural network model which is optimized by genetic algorithm and simulated annealing algorithm has been established and applied into the freight volumes forecast. The result shows that the optimized neural network has significant advantages inspect of fast convergence speed, good generalization ability and not easy to yield minimal local results. In generally, the optimized neural network exhibits good representation and strong prediction ability, and is a helpful tool in the future freight volumes prediction.