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| 基于改进神经网络的水泥路面使用性能预测模型 | |
| 引用本文： | 周文献,李明利,孙立军. 基于改进神经网络的水泥路面使用性能预测模型[J]. 同济大学学报(自然科学版), 2006, 34(9): 1191-1195 |
| 作者姓名： | 周文献 李明利 孙立军 |
| 作者单位： | 1. 同济大学,道路与交通工程教育部重点实验室,上海,200092;上海市公路管理处,上海,200063 2. 同济大学,污染控制与资源化研究国家重点实验室,上海,200092 3. 同济大学,道路与交通工程教育部重点实验室,上海,200092 |
| 摘 要： | 为了克服传统水泥路面使用性能预测方法的缺陷和误差反向传播(BP)神经网络的不足,利用动量方法改进了BP神经网络收敛性,建立了水泥路面使用性能预测模型.采用广东水泥路面调查数据对模型进行了训练和验证,并对模型训练方法进行了优化.分析表明,该模型具有较好的实用性和预测精度. |
| 关 键 词： | 水泥混凝土路面 路面使用性能 神经网络 预测模型 |
| 文章编号： | 0253-374X（2006）09-1191-05 |
| 收稿时间： | 2005-06-20 |
| 修稿时间： | 2005-06-20 |
Portland Cement Concrete Pavement Performance Prediction Model Based on Improved Neural Network |
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| ZHOU Wenxian,LI Mingli,SUN Lijun. Portland Cement Concrete Pavement Performance Prediction Model Based on Improved Neural Network[J]. Journal of Tongji University(Natural Science), 2006, 34(9): 1191-1195 | |
| Authors: | ZHOU Wenxian LI Mingli SUN Lijun |
| Affiliation: | 1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 200092, China; 2. Highway Administration of Shanghai ,Shanghai 200063 ,China; 3. State Key Laboratory of Resource Reuse and Pollution Control, Tongji University, Shanghai 200092, China |
| Abstract: | In order to deal with the deficiency of traditional prediction method of pavement performance and the insufficiency of Back-Propagation(BP) neural network,a prediction model based on the improved neural network with momentum Back-Propagation(MOBP) is developed.The model is validated and trained with pavement performance data of Guangdong province,and the training method is also optimized.According to the theoretical analysis and practical verification,the approach is completely feasible. |
| Keywords: | portland cement concrete pavement pavement performance neural network prediction model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |