Advanced data mining techniques for landslide susceptibility mapping

Advanced data mining techniques for landslide susceptibility mapping

This paper describes the development and validation of landslides susceptibility models for mountainous regions using advanced data mining techniques. The investigation was carried out to ascertain the effectiveness of Naïve Bayes Multinomial (NBM) and Random Trees (RT) in landslide susceptibility m...

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Bibliographic Details
Main Authors: Muhammad Bello Ibrahim, Zahiraniza Mustaffa, Abdul-Lateef Balogun, Indra Sati Hamonangan Harahap, Mudassir Ali Khan
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
landslides analysis
susceptibility mapping
soft computing
machine learning and gis
data mining
conditioning factors
frequency ratio
Online Access:http://dx.doi.org/10.1080/19475705.2021.1960433

Internet

http://dx.doi.org/10.1080/19475705.2021.1960433

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