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Author:

Jiang, Xin (Jiang, Xin.) | Xinhua, E. (Xinhua, E..) | Zhao, Wenyi (Zhao, Wenyi.)

Indexed by:

EI Scopus

Abstract:

In view of the shortcomings in the current research on the accuracy of landslide disaster early warning and the relationship between multiple landslides, this paper combines the collaborative filtering method and the logical regression training method to improve on the previous research on early warning only for a single landslide. The results show that the combination of the collaborative filtering method can use the similarity between landslides to predict, and the model training results have been significantly improved. The prediction of landslide disasters has a higher recall rate, which is of great significance to the prevention and control of landslide disasters. © 2023 IEEE.

Keyword:

Disaster prevention Collaborative filtering Landslides Machine learning Disasters Logistic regression

Author Community:

  • [ 1 ] [Jiang, Xin]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 2 ] [Xinhua, E.]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 3 ] [Zhao, Wenyi]Monitoring Institute, The China Geological Environment, Beijing, China

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Year: 2023

Page: 27-31

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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