System Development & Application
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1459-1463

Uncertain PAHT clustering algorithm in landslide hazard prediction application

Hu Jiana
Zhu Lingb
Mao Yiminb
a. Dept. of Information Engineering, College of Applied Science, b. School of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China

Abstract

In the clustering study of landslide prediction, the difficulties of determining the number of clusters which traditional clustering algorithm needs to set in advance and accurately measuring the important factor of landslide induced-rainfall leads to bad prediction effect. Therefore, this paper proposed a new clustering algorithm-uncertain PAHT algorithm. The algorithm introduced a kind of uncertain data model called M-D distance, which effectively measured the uncertain rainfall; and based on the hierarchical clustering thinking, through finding the best threshold p* to determine the k value. Contrast experiment in Yan'an Baota district as an example, the experimental results verify the effectiveness of uncertain M-D distance and PAHT algorithm and the feasibility of uncertain PAHT algorithm on the landslide hazard prediction.

Foundation Support

江西省教育厅科技项目(GJJ151528,GJJ151531)
国家自然科学基金资助项目(41562019,41530640)
江西省自然科学基金资助项目(20161BAB203093)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.11.0744
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: System Development & Application
Pages: 1459-1463
Serial Number: 1001-3695(2019)05-037-1459-05

Publish History

[2019-05-05] Printed Article

Cite This Article

胡健, 朱玲, 毛伊敏. 不确定PAHT聚类算法在滑坡危险性预测上的应用 [J]. 计算机应用研究, 2019, 36 (5): 1459-1463. (Hu Jian, Zhu Ling, Mao Yimin. Uncertain PAHT clustering algorithm in landslide hazard prediction application [J]. Application Research of Computers, 2019, 36 (5): 1459-1463. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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