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No file available [This article belongs to Volume - 54, Issue - 1]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-06-2022-223
Title : Regional Landslide Susceptibility Prediction Based on Negative Sample Selected by Coupling Information Value Method
ZHOU Xiaoting, , HUANG Faming, , WU Weicheng, , ZHOU Chuangbing, , ZENG Shiyi, , PAN Lihan,

Abstract : For the landslide susceptibility prediction (LSP) based on machine learning (ML) models, the reasonable selection of negative samples has an important influence on the LSP performance. Generally, the main selection methods include randomly selecting from the whole study area or from the specific attribute areas such as low slopes. The negative samples selected by the above methods are often inaccurate or biased, resulting in low accuracy and low reliability of LSP. To solve this problem, the cou

Keywords : LSP, ML, Regional Landslide Susceptibility Prediction Based, Negative Sample Selected, Coupling Information Value Method For