Pavement Performance Combining Forecasting Based on BP Neural
Network and Markov Model

doi:10.3969/j.issn.1674-0696.2012.05.19

Abstract

Abstract: 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．

Key words: road engineering, pavement performance, combining forecasting, Markov model, BP neural network

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。

关键词: 道路工程, 路面使用性能, 组合预测, 马尔可夫过程链, BP 神经网络

CLC Number:

U416.216

Zhou Pengfei，Wen Shengqiang，Kang Haigui. Pavement Performance Combining Forecasting Based on BP Neural Network and Markov Model[J]. Journal of Chongqing Jiaotong University(Natural Science), 2012, 31(5): 997-1001.

周鹏飞，温胜强，康海贵. 基于马尔可夫链与神经网络组合的路面使用性能预测[J]. 重庆交通大学学报（自然科学版）, 2012, 31(5): 997-1001.

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Pavement Performance Combining Forecasting Based on BP Neural Network and Markov Model

基于马尔可夫链与神经网络组合的路面使用性能预测

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