Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

Spatial modelling of gully erosion at regional level is very relevant for local authorities to establish successful counter-measures and to change land-use planning. This work is exploring and researching the potential of a genetic algorithm-extreme gradient boosting (GE-XGBoost) hybrid computer edu...

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Bibliographic Details
Main Authors: Alireza Arabameri, Subodh Chandra Pal, Romulus Costache, Asish Saha, Fatemeh Rezaie, Amir Seyed Danesh, Biswajeet Pradhan, Saro Lee, Nhat-Duc Hoang
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
gully erosion
spatial modelling
ensemble learning
extreme gradient boosting machine
gis
genetic algorithm
Online Access:http://dx.doi.org/10.1080/19475705.2021.1880977

Internet

http://dx.doi.org/10.1080/19475705.2021.1880977

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