| 基于SVM多类分类的滑坡区域危险性评价方法研究 |
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| 引用本文： | 姜琪文,许强,何政伟.基于SVM多类分类的滑坡区域危险性评价方法研究[J].地质灾害与环境保护,2005,16(3):328-330. |
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| 作者姓名： | 姜琪文 许强 何政伟 |
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| 作者单位： | 成都理工大学地质灾害防治与地质环境保护国家专业实验室,成都,610059 |
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| 基金项目： | 教育部霍英东教育基金会高等院校青年教师基金;教育部优秀青年教师资助计划 |
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| 摘 要： | 近年来，随着新理论、新技术得发展，提出了许多新模型和方法应用于滑坡区域危险性评价中。支持向量机（support vector machine，SVM）是新一代的学习算法，已有前人利用SVM应用于滑坡灾害预测中。然而大多只是利用了SVM的两分类算法，得到的结果只有稳定不稳定两种．这对滑坡区域评价来说是远远不够的。本文尝试利用SVM的多类分类算法进行滑坡危险性区域评价，取得了较好的结果。
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| 关 键 词： | 滑坡 区域评价 |
| 文章编号： | 1006-4362（2005）03-0328-03 |
| 收稿时间： | 2005-06-03 |
| 修稿时间： | 2005-06-032005-06-21 |
STUDY ON LANDSLIDE HAZARD ZONATION BASED ON MULTI-CLASSIFICATION SUPPORT VECTOR MACHINE |
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| JIANG Qi-wen,XU Qiang,HE Zheng-wei.STUDY ON LANDSLIDE HAZARD ZONATION BASED ON MULTI-CLASSIFICATION SUPPORT VECTOR MACHINE[J].Journal of Geological Hazards and Environment Preservation,2005,16(3):328-330. |
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| Authors: | JIANG Qi-wen XU Qiang HE Zheng-wei |
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| Abstract: | Many new models have been applied to landslide hazard zonation since 1990s. Support vector machine (SVM) as a novel learning algorithm has been used in the fields of geohazards, but in most of them, c-SVM algorithm is used to make sample data into two classification. This paper uses multi-classification algorithm of support vector machine to produce landslide hazard zonation figure and the evaluation results indicate that it is effective and reasonable. |
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| Keywords: | SVM |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
