基于模糊神经网络的道路毁损程度评价方法

为深入研究道路毁损程度评价问题,将模糊理论与人工神经网络技术结合起来，提出了基于模糊神经网络的道路毁损程度评价方法。确定道路毁损程度评估的3个指标,并通过样本学习训练,获取评价专家的经验知识和直觉思维。将训练好的网络用于316国道震后某路段的毁损程度评估,并与已有评价方法的评估结果相比较。结果表明，采用模糊神经网络对道路毁损程度进行评估可降低评价过程中的人为因素影响,保证评价结果的客观性,提高评估效率。

Method of road damage degree assessment based on Fuzzy-neural network

A fuzzy neural network for the assessment of road damage degree is set up through the combination of the fuzzy theory and the neural network, which is based on in depth study of the existing methods for the road damage degree evaluation. Three evaluative indexes of the road damage degree were proposed, and the expert experience included in this model by training the fuzzy neural network. The approach was illustrated for the damage degree evaluation of national road No.316 and compared with the existing assessment result. The result shows that the method is practical and is of high efficiency to assess the damage degree of highway system.