| 基于ANN和GIS耦合模型的场地地震液化势评价系统研究 |
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| 引用本文： | 汤 皓,陈国兴,李方明.基于ANN和GIS耦合模型的场地地震液化势评价系统研究[J].岩土力学,2006,27(Z1):1007-1012. |
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| 作者姓名： | 汤 皓 陈国兴 李方明 |
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| 作者单位： | 南京工业大学 岩土工程研究所，南京 210009 |
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| 基金项目： | 江苏省自然科学基金项目(No.BK2004124)；南京工业大学博士创新基金项目(No.BCX2006B)。 |
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| 摘 要： | 采用组件式GIS (COMGIS)技术开发了结合BP神经网络分析模型的场地地震液化势评价系统，调用水平成层土地震反应分析程序SHAKE91实现设定地震下地震动影响场的模拟。在VB下调用Matlab神经网络工具箱来完成场地地震液化势评价模型在COMGIS系统中的模块化；利用GIS技术对评价结果，即液化势等级进行空间复合，给出场地潜在的地层液化势空间分布图。研究表明，SHAKE91应用程序在系统菜单下可直接调用，实现地震动影响场计算的模块化；BP神经网络技术应用于场地地震液化势评价中能达到较为理想的效果；系统的GIS空间分析功能可使评价结果与场地信息进行空间匹配，实现目标场地潜在地震液化势的快速评估。
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| 关 键 词： | 人工神经网络模型 组件式GIS 场地地震液化 SHAKE91软件 Matlab软件 |
| 收稿时间： | 2006-04-29 |
Hazard evaluation system for earthquake-induced site liquefaction
potential based on coupling model of ANN and GIS |
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| TANG Hao,CHEN Guo-xin,LI Fang-ming.Hazard evaluation system for earthquake-induced site liquefaction
potential based on coupling model of ANN and GIS[J].Rock and Soil Mechanics,2006,27(Z1):1007-1012. |
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| Authors: | TANG Hao CHEN Guo-xin LI Fang-ming |
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| Institution: | Institute of Geotechnical Engineering, Nanjing University of Technology, Nanjing 210009, China |
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| Abstract: | Component object model GIS (COMGIS) technique is adopted to develop the hazard evaluation system for earthquake-induced site liquefaction potential combined with BP model of artificial neural network (ANN). Firstly, the simulation of site earthquake influence field under scenario earthquake can be generated by calling SHAKE91, a commercial program to analyze seismic response of level layered site. Then, seismic hazard for sandy soil liquefaction can be evaluated by BP model of ANN which is modularized under VB by importing ANN toolbox from Matlab. Thus the analytical results from BP model of ANN can be simulated spatially by GIS; and the spatial distribution of site liquefaction potential also can be graphed. The research shows that: First, SHAKE91 software can be called directly from the system menu to simulate the site earthquake influence field. Second, the relatively perfect results can be obtained when the BP model of ANN is utilized to predict the latent hazard of earthquake-induced site liquefaction. Third, by GIS technique, the evaluated results can be perfectly matched with the site information spatially. Thus the critical site liquefaction hazard area can also be identified. |
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| Keywords: | model of artificial neural network COMGIS earthquake-induced site liquefaction SHAKE91 Matlab |
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