基于BP人工神经网络的公路软土地基沉降预测

采用BP人工神经网络,利用杭瑞高速公路软土地基实测沉降数据直接建模,进行了软土地基最终沉降量的预测,将预测结果与曲线拟合法中的双曲线法、指数曲线法、三点法的预测结果进行了对比分析。证明神经网络法能避免传统方法计算过程中各种人为因素的干扰,计算精度高,泛化性强,简便易行。

Settlement Prodiction of Soft-clay Ground Based on Artificial Neural Network

The paper established the model directly based on measured data of freeway,and predicted settlement of soft-clay ground,with the artificial networks （ANN）. A perfect effectiveness is obtained through comparing and analyzing the result by some methods of curve fitting method such as hyperbolic method,exponential method,and three-point method. It proved that the neural network method can avoid the mistake due to human factor in traditional methods and can simulate engineering precisely,widely and easily.