Wildfire susceptibility mapping using five boosting machine learning algorithms: the case study of the Mediterranean region of Turkey
Forest fires caused by different environmental and human factors are responsible for the
extensive destruction of natural and economic resources. Modern machine learning …
extensive destruction of natural and economic resources. Modern machine learning …
Hybrid ensemble based machine learning for smart building fire detection using multi modal sensor data
Fire disasters are one the most challenging accidents that can take place in any urban
buildings like houses, offices, hospitals, colleges and industries. These accidents which the …
buildings like houses, offices, hospitals, colleges and industries. These accidents which the …
Improving machine learning prediction of peatlands fire occurrence for unbalanced data using SMOTE approach
From our previous study, we have known that only a small number of literatures have
studied peatlands fire modeling in Indonesia. It is including our recent study on the …
studied peatlands fire modeling in Indonesia. It is including our recent study on the …
Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
S Cheng, H Chassagnon, M Kasoar… - … on Emerging Topics …, 2024 - ieeexplore.ieee.org
Global wildfire models play a crucial role in anticipating and responding to changing wildfire
regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire …
regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire …
Forest fire prediction for nasa satellite dataset using machine learning
Natural resources play an essential role in living, but natural hazards hinder the sustainable
development of humans and living things. An increase in global warming increases the …
development of humans and living things. An increase in global warming increases the …
Prediction of forest fire occurrence in peatlands using machine learning approaches
In this paper we consider the application of various machine learning approaches for
prediction of the forest fire occurrence in the peatlands area. Here we consider some …
prediction of the forest fire occurrence in the peatlands area. Here we consider some …
Prediction of Wildfires Based on the Spatio-Temporal Variability of Fire Danger Factors
AT Gizatullin, NA Alekseenko - Geography, Environment, Sustainability, 2022 - ges.rgo.ru
Most methods in the field of wildfire prevention are based on expert assessment of fire
danger factors. However, their weights are usually assumed constant for the entire …
danger factors. However, their weights are usually assumed constant for the entire …
Spatiotemporal dynamics and climate influence of forest fires in Fujian Province, China
Climate determines the spatiotemporal distribution pattern of forest fires by affecting
vegetation and the extent of drought. Thus, analyzing the dynamic change of the forest fire …
vegetation and the extent of drought. Thus, analyzing the dynamic change of the forest fire …
Prediction of forest fire using hybrid fuzzy-clustering-bagging method
Various classification methods have been considered to predict the occurrence of the forest
fire, including the recent ensemble methods, such as bootstrap aggregating (bagging) …
fire, including the recent ensemble methods, such as bootstrap aggregating (bagging) …
Forest fire detection in aerial vehicle videos using a deep ensemble neural network model
N Sarikaya Basturk - Aircraft engineering and aerospace technology, 2023 - emerald.com
Purpose The purpose of this paper is to present a deep ensemble neural network model for
the detection of forest fires in aerial vehicle videos. Design/methodology/approach …
the detection of forest fires in aerial vehicle videos. Design/methodology/approach …