摘要
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，采用因子分析法提炼出较少的线性无关的主要因素，建立预测城市汽车保有量的RBF神经网络模型。最后通过实例分析，对RBF神经网络因子分析法计算结果和全要素神经网络模拟结果比较，得出RBF神经网络因子分析法在运算效率、运算精度上的优越性。
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, factor analysis method is imposed to epurate lesser non-linear factors, and the RBF neural network model to forecast the urban auto- mobile population is established. Finally, through a case, the result by RBF neural network simulation factor analysis is compared with multinomial fitting RBF neural network simulation. The conclusion is that the method of RBF neural network simulation factor analysis is superior both in efficiency and precision.
出处
《交通科技与经济》
2011年第1期67-70,共4页
Technology & Economy in Areas of Communications
关键词
汽车保有量
预测
RBF神经网络
因子分析
automobile population
forecasting
RBF neural network
factor analysis
