基于预警隶属度函数多模型融合的滑坡预警方法

doi:10.13278/j.cnki.jjuese.20170215

吉林大学学报(地球科学版) ›› 2019, Vol. 49 ›› Issue (2): 477-484.doi: 10.13278/j.cnki.jjuese.20170215

基于预警隶属度函数多模型融合的滑坡预警方法

林剑¹, 张奇飞¹, 龙万学², 张红伟¹

1. 湖南科技大学知识处理与网络化制造实验室, 湖南湘潭 411201;
2. 贵州省交通规划勘察设计研究院股份有限公司, 贵阳 550001

收稿日期:2017-12-28 出版日期:2019-03-26 发布日期:2019-03-28
作者简介:林剑(1964-),男,教授,主要从事模式识别、地质灾害信息处理研究,E-mail:lj2110015@163.com
基金资助:
交通运输部科技成果推广项目（2014316802080）；国家自然科学基金项目（41471067）；湖南省教育厅重点项目（15A062）；湖南科技大学研究生创新基金项目（CX2017B623）

Multi-Model Fusion Method for Landslide Early Warning Based on Early Warning Membership Function

Lin Jian¹, Zhang Qifei¹, Long Wanxue², Zhang Hongwei¹

1. Laboratory of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China;
2. Guizhou Transportation Planning Survey Design Academy Co., LTD, Guiyang 550001, China

Received:2017-12-28 Online:2019-03-26 Published:2019-03-28
Supported by:
Supported by Project of Transportation Department Scientific and Technological Achievements Promotion (2014316802080), National Natural Science Foundation of China (41471067), Project of Hunan Province Education Department(15A062) and Graduate Innovation Fund of Hunan University of Science and Technology (CX2017B623)

摘要/Abstract

摘要： 不同的滑坡预报模型存在预报同一滑坡可能提前也有可能延迟、预报精度差异较大的问题，而且，融合多模型预警方法未能充分体现个体模型预报特征，其融合预警精度不高。在分析模型可靠性的基础上，区分预报提前和延迟2种情况，设计不同的发生滑坡隶属度函数，以最低风险原则确定滑坡预警隶属度函数，利用模糊积分实现多模型融合滑坡预警。利用16个已知滑坡对预报模型进行可靠性评价，另选4个已知滑坡分别进行滑坡发生3 d前和1 d前多模型融合预警验证实验，结果表明，多模型融合预警虚警率比多个单一模型平均虚警率分别降低16.6%和25.0%。实验表明利用预警隶属函数进行多模型滑坡预警能提高预警精度20.0%左右。

关键词: 滑坡预警, 预警隶属度函数, 模糊积分, 多滑坡预报模型融合

Abstract: Different landslide prediction models have the problem of predicting the same landslide in advance or delay, and the prediction accuracy is quite different. At present, the fusion multi-model early-warning method fails to fully reflect the characteristics of individual model prediction, and the fusion early-warning accuracy is not high. On the basis of analyzing the reliability of these models, two landslide occurrence membership functions of delay and advance were designed respectively. According to the principle of minimum risk, the membership function of landslide warning was determined, and multi-model fusion of landslide early warning was realized by fuzzy integral. Sixteen known landslides were used to evaluate the reliability of the prediction models, and the other four known landslides were used to carry out the fusion early warning experiment of the landslide three days before and one day before the landslide occurrence, and the false alarm rate of multi-model fusion early warning was reduced by 16.6% and 25% respectively, compared with the average false alarm rate of multiple single models. The experiment shows that using early warning membership function for multi-model landslide early warning can improve the early warning accuracy for about 20%.

Key words: landslide early warning, early warning membership function, fuzzy integral, multi landslide prediction model fusion

中图分类号:

P642.22

林剑, 张奇飞, 龙万学, 张红伟. 基于预警隶属度函数多模型融合的滑坡预警方法[J]. 吉林大学学报(地球科学版), 2019, 49(2): 477-484.

Lin Jian, Zhang Qifei, Long Wanxue, Zhang Hongwei. Multi-Model Fusion Method for Landslide Early Warning Based on Early Warning Membership Function[J]. Journal of Jilin University(Earth Science Edition), 2019, 49(2): 477-484.

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基于预警隶属度函数多模型融合的滑坡预警方法

Multi-Model Fusion Method for Landslide Early Warning Based on Early Warning Membership Function

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