基于自组织特征映射神经网络的路面使用性能评价方法  

Pavement Performance Evaluation Based on SOM Neural Network

作　　者：范嫦娥[1] 李德华[1] 

机构地区：[1]江苏大学汽车与交通工程学院,江苏镇江212013

出　　处：《重庆交通大学学报（自然科学版）》2013年第1期80-82,98,共4页Journal of Chongqing Jiaotong University(Natural Science)

摘　　要：针对目前沥青路面使用性能评价方法的不足,提出了基于自组织特征映射神经网络的评价方法。该方法选择了行驶质量、路面破损状况、结构承载力和路面抗滑性能等4个主要因素,应用自组织特征映射神经网络,对沥青路面使用性能进行综合评价。最后通过实例计算,并将计算结果与传统方法的评价结果进行比较。结果表明:该方法合理有效,且相对于目前常用的方法,具有一定的优越性。At present,the evaluation method of asphalt pavement is insufficient.Thus one evaluation method was put forward based on self-organizing feature map neural network(SOMNN).Four main factors including driving quality,the damage condition of pavement,the bearing capacity of structure and the anti-skidding performance of pavement were selected to evaluate the using performance of asphalt pavement based on the self organization feature map neural network.Finally,an example was calculated to compare the results between the traditional method and the current method.The results show that,compared with the commonly used method,the current method is reasonable and effective.

关 键 词：沥青路面 评价方法 神经网络 路面性能 

分 类 号：U416.217[交通运输工程—道路与铁道工程]