Enhancing Predictive Accuracy of Landslide Susceptibility via Machine Learning Optimization

Enhancing Predictive Accuracy of Landslide Susceptibility via Machine Learning Optimization

The present study examines the application of four machine learning models—Multi-Layer Perceptron, Naive Bayes, Credal Decision Trees, and Random Forests—to assess landslide susceptibility using Mei County, China, as a case study. Aerial photographs and field survey data were integrated into a GIS s...

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Bibliographic Details
Main Authors: Chuanwei Zhang, Dingshuai Liu, Paraskevas Tsangaratos, Ioanna Ilia, Sijin Ma, Wei Chen
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
landslide susceptibility mapping
machine learning optimization
GIS-based analysis
Random Forests
Mei County
China
Online Access:https://www.mdpi.com/2076-3417/15/11/6325
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