摘要
在分析路面使用性能影响因素的基础上,结合马尔可夫过程链预测与BP神经网络预测的优势,提出一种组合预测模型;探讨了模型组合形式及参数确定方法;结合河南某高速公路工程实测资料进行了实证分析。结果表明:通过预测模型的合理组合与参数的优选,能够有效地提高预测精度。
Based on the analysis of important effects of the pavement performance,a pavement performance combining method is proposed with neural network and Markov process.The model combining forms are discussed and the parameters optimization is suggested.Then using actual survey datum of a highway in Henan,experiments are studied and the results show that the proposed combining model is capable to improve pavement performance forecasting by choosing suitable combining forms and their parameters.
出处
《重庆交通大学学报（自然科学版）》
CAS
北大核心
2012年第5期997-1001,共5页
Journal of Chongqing Jiaotong University(Natural Science)
基金
国家自然科学基金项目(71101014)
河南交通厅科技计划项目(200912)
