Preprints
https://doi.org/10.5194/nhess-2023-153
https://doi.org/10.5194/nhess-2023-153
05 Oct 2023
 | 05 Oct 2023
Status: this preprint is currently under review for the journal NHESS.

Regional landslide susceptibility assessment based on Inter.iamb-Tabu algorithm

Chao Yin, Xixuan Zhang, Xuebing Ma, Xinliang Liu, and Shufeng Li

Abstract. Due to the great differences in geological environment characteristics and landslide disaster mechanism in different regions, the logical structure of each mathematical model is also different. It can only be determined through comparative research. Four improved algorithms based on Bayesian networkwere verified, and the error index was introduced to determine the algorithm with the best modeling effect. The landslide susceptibility probability of 774570 grids in Boshan District was calculated, and the landslide susceptibility distribution map of Boshan District was plotted. Based on the spatial superposition and grid calculator function of GIS, the landslide susceptibility assessment results of each model were compared.

Chao Yin et al.

Status: open (until 28 Dec 2023)

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  • RC1: 'Comment on nhess-2023-153', Anonymous Referee #1, 10 Nov 2023 reply

Chao Yin et al.

Chao Yin et al.

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Short summary
In this paper, Boshan district, China was taken as the study area. Four improved algorithms based on Bayesian networkwere verified, and the error index was introduced to determine the algorithm with the best modeling effect. The results show that the landslide susceptibility modeling based on Inter.iamb-Tabu is the best in Boshan district.
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