Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility

Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility

AbstractIn this study, the generalized linear model (GLM) and four ensemble methods (partial least squares (PLS), boosting, bagging, and Bayesian) were applied to predict forest fire hazard in the Chalus Rood watershed in the Mazandaran Province, Iran. Data from 108 historical forest fire events col...

Full description

Bibliographic Details
Main Authors: Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, Jungho Im, Hao-Thing Pai, Shahab S. Band, Amir Mosavi
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Generalized linear model
ensemble
natural hazards
Chalus Rood watershed
forest fire susceptibility
artificial intelligence
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2023.2206512

Similar Items

Similar Items