BP和RBF神经网络在边坡稳定性评估中的比较研究

Comparative Research on BP and RBF Neural Networks in Slope Stability Assessment

通过实例分析,对BP神经网络和RBF神经网络在边坡稳定性评估中的应用进行了比较研究,结果表明,BP神经网络和RBF神经网络均能很好地对边坡稳定性进行评估,但RBF神经网络比BP神经网络的训练速度更快,效率更高,并且对于同样的精度要求,RBF神经网络对边坡稳定性的评估结果更加准确和适用。

Through case analysis,the application of BP and RBF neural networks in slope stability assessment is studied comparatively.The result shows that both BP and RBF neural networks could be applied for slope stability assessment;however RBF neural network has faster training speed and higher efficiency than BP neural network and for the same requirement on accuracy,the application result of RBF neural network in slope stability assessment is more correct and applicable.