基于BP神经网络的路面使用性能预测分析

Prediction of Pavement Performance Based on the Back Propagation Neural Network

以温度、湿度和交通量作为影响因素,取破损率、弯沉作为路面性能预测指标,引入BP神经网络理论,建立了路面使用性能的预估模型。采集已使用多年的5条道路的相应数据建模并进行分析,结果表明,该模型具有较高的可信度,理论上可以用于路面性能的预测。

This paper discussed the deficiencies existed in the current pavement performance prediction methods and establishes a new performance prediction model based on the neural network theory with back propagation （BP） algorithm. The model uses the temperature, humidity and traffic volume as the influence factors and rate of pavement damage, deflection as the pavement performance prediction indices. This model was applied to five existing roads which have extensive data collected. The results are satisfactory.