Abstract
In this study, we explored hybrid fuzzy logic modelling techniques to predict the burned area of forest fires. Fast detection is crucial for successful firefighting, and a model with an accurate prediction ability is extremely useful for optimizing fire management. Fuzzy Inductive Reasoning (FIR) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are two powerful fuzzy techniques for modelling burned areas of forests in Portugal. The results obtained from them were compared with those of other artificial intelligence techniques applied to the same datasets found in the literature.
Highlights
In this paper we addressed the challenge of modelling forest fires by means of hybrid machine-learning techniques based on fuzzy logic to predict the areas forest fires will burn
The main goal of this research was to study the performance of hybrid fuzzy logic modelling techniques to predict the burned area of forest fires
The results obtained by Fuzzy Inductive Reasoning (FIR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models are presented
Summary
Academic Editors: Michele Salis, Grazia Pellizzaro, Bachisio Arca, Pierpaolo Duce, Donatella Spano, Costantino Sirca and Valentina Bacciu
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