| 砂土液化的广义回归神经网络判别法 |
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| 引用本文： | 李标, 黄强, 席文熙, 慎乃齐. 2008: 砂土液化的广义回归神经网络判别法. 工程地质学报, 16(S1): 411-414. |
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| 作者姓名： | 李标 黄强 席文熙 慎乃齐 |
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| 作者单位： | 1.中国地质大学北京工程技术学院 北京 100083;;2.中国地质大学北京信息工程学院 北京 100083 |
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| 摘 要： | 本文阐述了广义回归神经网络的特点,综合考虑了影响砂土液化的主要因素,利用我国台湾和土耳其科贾埃利地区震害调查资料,建立了预测砂土液化的广义回归神经网络模型。应用多元回归预处理优化输入样本数据后,用广义回归神经网络对砂土液化判别,计算结果与实际情况基本吻合。研究表明,广义回归神经网络是进行砂土液化判别预测的有效手段,计算数据经过多元回归预处理后,大幅度提高了预测准确度。
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| 关 键 词： | 砂土液化判别 广义回归神经网络 多元线性回归 |
APPLYING GRNN METHOD TO EVALUATE SAND LIQUEFACTION |
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| LI Biao, HUANG Qiang, XI Wenxi, SHEN Naiqi. 2008: APPLYING GRNN METHOD TO EVALUATE SAND LIQUEFACTION. JOURNAL OF ENGINEERING GEOLOGY, 16(S1): 411-414. |
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| Authors: | LI Biao HUANG Qiang XI Wenxi SHEN Naiqi |
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| Affiliation: | 1.School of Engineering and Technology, China University of Geosciences, Beijing 100083;;2.School of Information and Technology, China University of Geosciences, Beijing 100083 |
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| Abstract: | In this paper, we describe the characteristic of general regression neural network. Then the model of predicting the occurrence of liquefaction is proposed after considering the main factors. The supporting data is derived from the results of field tests of the two major earthquakes that took place in Turkey and Taiwan in 1999. After utilizing the multiple regression pretreatment to optimize the input data, the study uses the GRNN to implement the training and validation phase. The results have a higher degree of consistent with the actual situation and clearly demonstrate the capability of the proposed model to assess the liquefaction of soils. Then multiple linear regression is proved to improve the accuracy of forecasts as a good pretreatment method. |
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| Keywords: | Sand liquefaction General |
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