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为了使公路预防性养护措施发挥最大效益,延长公路使用寿命,针对路面各使用性能指标存在相互联系的特点,采用人工神经网络对沥青混凝土路面预防性养护时机进行研究,并根据公路预防性养护工程的特点,确定相应的输入指标,建立基于BP神经网络的沥青混凝土路面预防性养护时机的确定模型。通过有效的样本学习,应用该模型实现对专家知识及经验的提取和存储。仿真实例验证了模型的合理性和有效性。为公路预防性养护时机的确定提供新的思路。
In order to maximize the benefits of preventive maintenance measures of the highway and extend the service life of the highway, in view of the interlinkages between the performance indexes of the pavement, the artificial neural network is used to study the preventive maintenance timing of the asphalt concrete pavement. According to the preventive maintenance project of the highway, And determine the corresponding input index to establish the model of preventive maintenance timing of asphalt concrete pavement based on BP neural network. Through effective sample learning, the model is applied to extract and store expert knowledge and experience. Simulation examples verify the rationality and effectiveness of the model. Provide a new idea for the determination of the timing of preventive maintenance of the highway.