基于RS-SVM的地下管线震害预测方法研究
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摘要
通过对地下管线系统防灾规划基础资料的分析,构建了适合大城市地下管线抗震可靠性破坏程度评价因素集,并以粗糙集(RS)理论作为前置处理系统优化此指标结构;然后基于粗糙集(RS)理论与支持向量机(SVM)的优势互补,利用最小二乘支持向量机(LS-SVM)对地下管线系统震害破坏等级进行仿真模拟.最后,以泉州市地下管线实际情况为例进行分析并将该模型预测结果与地下管线震害分析的理论法计算结果以及BP神经网络模型预测结果对比分析,验证了所提方法的有效性.
Based on the analysis of the foundation information of underground pipelines system,a suit of indexes' system was set up to evaluate the earthquake damage degree of metropolitan underground pipelines system,and then taking RS for former disposal system to optimize the indexes structure.The LS-SVM model was used to evaluate the earthquake damage degree of underground pipelines based on the complementary superiority of RS and SVM each other.Finally,taking the underground pipelines in Quanzhou as an example,after doing lots of prediction experiments and comparing with other common prediction methods such as the theory method and BP neural network algorithm,the method proposed in the paper proved to be effective and feasible.
Based on the analysis of the foundation information of underground pipelines system,a suit of indexes' system was set up to evaluate the earthquake damage degree of metropolitan underground pipelines system,and then taking RS for former disposal system to optimize the indexes structure.The LS-SVM model was used to evaluate the earthquake damage degree of underground pipelines based on the complementary superiority of RS and SVM each other.Finally,taking the underground pipelines in Quanzhou as an example,after doing lots of prediction experiments and comparing with other common prediction methods such as the theory method and BP neural network algorithm,the method proposed in the paper proved to be effective and feasible.
引文
[1]韩阳.城市地下管网系统的地震可靠性研究[D].大连:大连理工大学,2002Han Yang.Study on seismic reliability of urban buried pipeline network systems[D].Dalian:Dalian University ofTechnology,2002
[2]李昕,周晶,陈键云.基于神经网络方法的地下管道系统地震可靠性分析[J].世界地震工程,2001,27(4):107-111Li Xin,Zhou Jing,Chen Jianyun.Seismic reliability analysis of underground pipeline system using artificial neuralnetworks[J].World Information On Earthquake Engineering,2001,27(4):107-111
[3]韩阳,王威.给水管网实时故障诊断的支持向量机模型[J].给水排水,2007,33(2):109-112Han Yang,Wang Wei.SVM model for realtime diagnostic of water distribution network[J].Water&WastewaterEngineering,2007,33(2):109-112
[4]唐发明,王仲东,陈绵云.基于RS理论的支持向量机分类模型[J].测控技术,2005,24(3):62-64Tang Faming,Wang Zhongdong,Chen Mianyun.Classification model of support vector machine based on rough set theory[J].Ordnance Industry Automation,2005,24(3):62-64
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[7]马东辉,苏经宇,郭小东,等.泉州市规划区城市基础设施系统抗震易损性的研究[R].北京工业大学抗震减灾研究所,2004Ma Donghui,Su Jingyu,Guo Xiaodong,et al.Study on the seismic vulnerability of urban infrastructure system inQuanzhou City[R].Institute of Earthquake Resistance and Disaster Reduction of Beijing University ofTechnology,2004
[8]王威.城市(群)防震减灾能力评估方法的研究[D].郑州:河南工业大学,2007Wang Wei.Study on evaluation methods of cities′(urban agglomerations′)ability reducing earthquake disasters[D].Zhengzhou:Henan University of Technology,2007
[9]薛定宇,陈阳泉.高等应用数学问题的MATLAB求解[M].北京:清华大学出版社,2004Xue Dingyu,Chen Yangquan.The problem solution of higher applied mathematics by MATLAB[M].Beijing:TsinghuaPublishing House,2004
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[11]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2007Feisi technology products R&D center.Neural network theory and realization of MATLAB R2007[M].Beijing:Publishing House of Electronics Industry,2007
[2]李昕,周晶,陈键云.基于神经网络方法的地下管道系统地震可靠性分析[J].世界地震工程,2001,27(4):107-111Li Xin,Zhou Jing,Chen Jianyun.Seismic reliability analysis of underground pipeline system using artificial neuralnetworks[J].World Information On Earthquake Engineering,2001,27(4):107-111
[3]韩阳,王威.给水管网实时故障诊断的支持向量机模型[J].给水排水,2007,33(2):109-112Han Yang,Wang Wei.SVM model for realtime diagnostic of water distribution network[J].Water&WastewaterEngineering,2007,33(2):109-112
[4]唐发明,王仲东,陈绵云.基于RS理论的支持向量机分类模型[J].测控技术,2005,24(3):62-64Tang Faming,Wang Zhongdong,Chen Mianyun.Classification model of support vector machine based on rough set theory[J].Ordnance Industry Automation,2005,24(3):62-64
[5]Vapnik V.Statistical learning theory[M].New York:Wiley,1998
[6]张文修,吴志伟,梁吉业,等.粗糙集理论与方法[M].北京:科学出版社,2001Zhang Wenxiu,Wu Zhiwei,Liang Jiye,et al.Rough set theory and its application[M].Beijng:Science Press,2001
[7]马东辉,苏经宇,郭小东,等.泉州市规划区城市基础设施系统抗震易损性的研究[R].北京工业大学抗震减灾研究所,2004Ma Donghui,Su Jingyu,Guo Xiaodong,et al.Study on the seismic vulnerability of urban infrastructure system inQuanzhou City[R].Institute of Earthquake Resistance and Disaster Reduction of Beijing University ofTechnology,2004
[8]王威.城市(群)防震减灾能力评估方法的研究[D].郑州:河南工业大学,2007Wang Wei.Study on evaluation methods of cities′(urban agglomerations′)ability reducing earthquake disasters[D].Zhengzhou:Henan University of Technology,2007
[9]薛定宇,陈阳泉.高等应用数学问题的MATLAB求解[M].北京:清华大学出版社,2004Xue Dingyu,Chen Yangquan.The problem solution of higher applied mathematics by MATLAB[M].Beijing:TsinghuaPublishing House,2004
[10]Suykens J A K,Van Gestel T.Least squares support vector machines[M].Singapore World Scientific,2002
[11]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2007Feisi technology products R&D center.Neural network theory and realization of MATLAB R2007[M].Beijing:Publishing House of Electronics Industry,2007
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