基于灰色PSO-BP的客运量预测模型

Highway Passenger Quantity Prediction Model Based on Grey System and PSO-BP Neural Network

在灰色预测模型、BF神经网络与粒子群优化算法PSO的基础上建立基于灰色PSO-BP的公路客运量预测模型。并根据陕西省近10 a的公路客运量数据,对GM(1,1)、BP神经网络、灰色PSO-BP网络预测模型的预测结果进行比较,得出基于灰色PSO-BP的客运量预测模型能充分发挥各种算法的优势、提高预测精度,更适合运用在公路客运量预测的领域中。

This paper established a highway passenger capacity prediction model that on the basis of grey PSO- BP, based on the grey forecasting model, the BF neural network and particle swarm optimization algorithm. According to the highway passenger quantity history data of Shaanxi Province of the past 10 years, GM （ 1, 1 ）, the BP neural network, gray PSO-BP neural network prediction model are established using MATLAB. Comparing the prediction result, passenger capacity prediction model based on the grey PSO-BP can give full play to the advantages of all kinds of algorithm and improve the prediction accuracy. It is more suitable for the prediction of the highway passenger quantity.