In order to study the problems of inadequate maintenance measures, inappropriate maintenance time, and unreasonable use of funds in asphalt pavement maintenance of Highway in China, the maintenance of highway pavement is taken as the research object in this study, and a prediction model is established for preventive maintenance performance of highway by using neural network. Firstly, the performance of pavement is evaluated. The pavement performance prediction model is studied, and some mature prediction models are introduced. It is concluded that for the early built highways, the models are used when the acceptance of maintenance and preventive maintenance concepts is poor and the pavement performance shows a decreasing trend, but for the existing maintenance and preventive maintenance sections, the pavement performance detection shows a wave. The dynamic descent section is not suitable. The results show that the forecasting model proposed in this study is consistent with the development trend of the measured results, and can be used to predict the pavement performance under this model. Therefore, a theoretical basis is provided for the investment of highway maintenance funds and the scientific selection of maintenance schemes. The study has important guiding significance for the future highway management units in the selection of maintenance measures, the determination of maintenance timing, and the size of capital investment.

中文翻译：

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基于马尔可夫链和人工神经网络方法的公路沥青路面性能预测

为研究我国公路沥青路面养护存在养护措施不足、养护时间不合理、资金使用不合理等问题，以公路路面养护为研究对象，建立了预测模型。基于神经网络的高速公路预防性养护性能研究[J]. 首先，对路面的性能进行评估。研究了路面性能预测模型，介绍了一些成熟的预测模型。得出的结论是，对于早期建成的高速公路，在养护和预防性养护理念接受度较差且路面性能呈下降趋势时使用该模型，而对于现有养护和预防性养护路段，路面性能检测显示出较好的性能。海浪。动态下降部分不适合。结果表明，本研究提出的预测模型与实测结果的发展趋势一致，可用于预测该模型下的路面性能。因此，为公路养护资金的投入和养护方案的科学选择提供了理论依据。该研究对未来公路管理单位在养护措施的选择、养护时机的确定、资金投入的大小等方面具有重要的指导意义。为公路养护资金的投入和养护方案的科学选择提供了理论依据。该研究对未来公路管理单位在养护措施的选择、养护时机的确定、资金投入的大小等方面具有重要的指导意义。为公路养护资金的投入和养护方案的科学选择提供了理论依据。该研究对未来公路管理单位在养护措施的选择、养护时机的确定、资金投入的大小等方面具有重要的指导意义。