| 支持向量回归方法在震级预测中的应用 |
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| 引用本文： | 于波.支持向量回归方法在震级预测中的应用[J].防灾科技学院学报,2007,9(1):59-62. |
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| 作者姓名： | 于波 |
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| 作者单位： | 厦门市地震局,福建厦门,361003 |
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| 摘 要： | 本文阐述了支持向量回归(SVR)理论及其特性,提出了基于SVR的次年最大震级的预测方法,并对所选样本进行训练和预测,结果与实际值符合较好,理论分析和实例结果验证了基于SVR的震级预测方法比BP神经网络具有更高的预测精度和可靠性.
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| 关 键 词： | 支持向量回归 震级 预测 BP神经网络 |
| 文章编号： | 1673-8047（2007）01-0059-04 |
| 修稿时间： | 2006-11-13 |
An Application of SVR in Predicting the Magnitude of an Earthquake |
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| Yu Bo.An Application of SVR in Predicting the Magnitude of an Earthquake[J].Journal of Institute of Disaster-prevention Science and Technology,2007,9(1):59-62. |
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| Authors: | Yu Bo |
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| Institution: | Xiamcn Seismological Bureau, Xiamen, Fujian 361003 |
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| Abstract: | This article introduces the basic theory and characteristics of Support Vector Regression(SVR) and advances a method to predict the next year biggest earthquake based on SVR.This method has been applied to our selected data set,and the forecasts are in good agreement with the measurement results.The comparison indicates that the accuracy and reliability of the SVR method are better than those of BP neural network method. |
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| Keywords: | Support Vector Regression earthquake magnitude predicting BP neural network method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
