Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction

Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction

Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP) machine learning methods for the prediction and mappin...

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Bibliographic Details
Main Authors: Binh Thai Pham, Abolfazl Jaafari, Mohammadtaghi Avand, Nadhir Al-Ansari, Tran Dinh Du, Hoang Phan Hai Yen, Tran Van Phong, Duy Huu Nguyen, Hiep Van Le, Davood Mafi-Gholami, Indra Prakash, Hoang Thi Thuy, Tran Thi Tuyen
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Symmetry
Subjects:
Bayes network
decision tree
multivariate logistic regression
Naïve Bayes
spatial modeling
Online Access:https://www.mdpi.com/2073-8994/12/6/1022

Internet

https://www.mdpi.com/2073-8994/12/6/1022

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