基于BP神经网络的城市汽车保有量预测

汽车保有量预测对城市交通的发展方向有直接的参考意义,通过分析影响城市汽车保有量的因素,找出了城市人口、GDP、公共交通服务水平等九个主要的因素,并对这些因素进行分析。同时建立了预测城市汽车保有量的BP神经网络模型。为了保证模型的收敛,在进行实例分析的时候引入主成分分析法将九个因素减少为五个因素,并进行了预测,预测精度比较高。

The Forecast of Urban Vehicle Ownership about BP Neural Network

The forecast of the vehicle ownership has the direct significance to the urban transportation development direction,by analyzing the effect to the urban vehicle ownership;the author has found the urban population,GDP,public transit service level,etc.nine primary factors.The BP neural network is set up to forecast the ownership.In order to guarantee the model convergence,the major factor analysis method is used to reduce the factors from nine to five and make forecast with good forecasting precision.