离散Hopfield神经网络在沥青路面使用性能评价中的应用

为使沥青路面使用性能评价更加科学合理,提出了基于离散Hopfield神经网络的评价方法,该方法综合了行驶质量、路面破损状况、结构承载力和路面抗滑性能等4个主要内容对路面使用性能的影响。通过设计离散Hopfield神经网络对沥青路面使用性能进行了综合评价,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,且相对于传统的方法操作简单、成本更低、易推广,具有一定的优越性。

Pavement Performance Evaluation by Discrete Hopfield Neural Network

TIn order to make the performance evaluation of asphalt pavement more scientific and reasonable,the author put forward an evaluation method based on Discrete Hopfield Neural Network(DHNN).This method took comprehensive consideration of four affecting factors including pavement ride quality,pavement condition,pavement structure bearing capacity and pavement skid resistance.Then it designed and simulated the DHNN programming to comprehensively evaluate the pavement performance.Finally,the method was verified by an example and the calculation has been compared with the traditional evaluation methods.Results showed that the method was reasonable and effective.Compared with others,this method was simple,cheap and easy to promote and has better superiority.