AdaBoost_BP神经网络在铁路货运量预测中的应用

Application of AdaBoost_BP neural network in prediction of railway freight volumes

为提高BP神经网络预测模型的预测准确性,将AdaBoost算法和BP神经网络相结合,提出了一种AdaBoost_BP神经网络预测模型。将该预测模型应用于我国1999年—2009年铁路货运量的历史统计数据,进行有效性验证,结果表明该模型对铁路货运量预测是有效、可靠的,且具有较高的预测精度,可应用于实际预测。

In order to improve prediction accuracy of BP neural network model, a prediction model is presented based on combined AdaBoost algorithm and BP neural network. The efficiency of the proposed prediction model is proved by predicting the railway freight volume statistical data from the 1999 to 2009 in China. The computer simulations have shown that this model is effective and suitable, has higher forecasting accuracy, and is applicable to practice.