| 基于粗糙集和RBF神经网络的高速公路路面使用性能评价研究 |
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| 引用本文： | 尚保玉,郭顺生,郭钧.基于粗糙集和RBF神经网络的高速公路路面使用性能评价研究[J].武汉理工大学学报(交通科学与工程版),2011(6). |
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| 作者姓名： | 尚保玉 郭顺生 郭钧 |
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| 作者单位： | 武汉理工大学机电工程学院; |
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| 基金项目： | 国家科技国际合作项目(批准号:2006DFA73180); 湖北省国际合作项目(批准号:2007CA008)资助 |
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| 摘 要： | 利用可辨识矩阵对影响路面使用性能评价的宽泛指标集进行分类、约简,得出对路面使用性能评价最有影响的数据指标,建立RBF神经网络模型,并把处理后的数据指标作为RBF神经网络的输入进行训练、仿真.通过实例,给出了该方法的具体实现过程.与没有采用指标约简的RBF神经网络进行结果对比,该方法在路面使用性能评价上更具有实用性、有效性和可靠性.
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| 关 键 词： | 粗糙集 可辨识矩阵 RBF神经网络 路面使用性能 评价模型 |
Research on Highway Pavement Performance Evaluation Based on Rough Set and RBF Neural Network |
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| Shang Baoyu Guo Shunsheng Guo Jun.Research on Highway Pavement Performance Evaluation Based on Rough Set and RBF Neural Network[J].journal of wuhan university of technology(transportation science&engineering),2011(6). |
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| Authors: | Shang Baoyu Guo Shunsheng Guo Jun |
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| Institution: | Shang Baoyu Guo Shunsheng Guo Jun(Sch.of Mechanical and Electronic Engineering Wuhan Univ.of Tech.,Wuhan 430070,China) |
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| Abstract: | In traditional highway pavement performance evaluation process,there are many disadvantages of method in using a single neural network,such as poor precision and low speed and so on.Therefore,a new way of highway pavement performance evaluation which uses rough set and RBF neural network was proposed.Firstly,it uses the discernible matrix to class and simplify the index which affects the pavement performance evaluation to get the most influential data index.Then it establishes the RBF neural network model t... |
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| Keywords: | rough set discernibility matrix RBF neural network evaluation pavement performance evaluation model |
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