Forest fire forecasting using ensemble learning approaches
Y Xie, M Peng - Neural Computing and Applications, 2019 - Springer
Frequent and intense forest fires have posed severe challenges to forest management in
many countries worldwide. Since human experts may overlook important signals, the …
many countries worldwide. Since human experts may overlook important signals, the …
Predicting forest fire using remote sensing data and machine learning
Over the last few decades, deforestation and climate change have caused increasing
number of forest fires. In Southeast Asia, Indonesia has been the most affected country by …
number of forest fires. In Southeast Asia, Indonesia has been the most affected country by …
[HTML][HTML] Prediction and data mining of burned areas of forest fires: Optimized data matching and mining algorithm provides valuable insight
DA Wood - Artificial Intelligence in Agriculture, 2021 - Elsevier
An optimized data-matching machine learning algorithm is developed to provide high-
prediction accuracy of total burned areas for specific wildfire incidents. It is applied to a well …
prediction accuracy of total burned areas for specific wildfire incidents. It is applied to a well …
Estimation of tree heights in an uneven-aged, mixed forest in northern Iran using artificial intelligence and empirical models
The diameters and heights of trees are two of the most important components in a forest
inventory. In some circumstances, the heights of trees need to be estimated due to the time …
inventory. In some circumstances, the heights of trees need to be estimated due to the time …
Machine learning for the estimation of diameter increment in mixed and uneven-aged forests
Estimating the diameter increment of forests is one of the most important relationships in
forest management and planning. The aim of this study was to provide insight into the …
forest management and planning. The aim of this study was to provide insight into the …
Prediction of forest fire using ensemble method
D Rosadi, W Andriyani - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
In this paper we consider the application of ensemble classification method, which is called
as the Adaptive Boosting (AdaBoost) method, to predict the occurrences of forest fire. To …
as the Adaptive Boosting (AdaBoost) method, to predict the occurrences of forest fire. To …
Modeling neutrosophic variables based on particle swarm optimization and information theory measures for forest fires
MG Gafar, M Elhoseny, M Gunasekaran - The Journal of Supercomputing, 2020 - Springer
Recently, neutrosophic systems modeling gained great attention in indeterminacy handling.
Generating suitable membership, indeterminacy and non-membership functions for …
Generating suitable membership, indeterminacy and non-membership functions for …
Generalized net model of forest zone monitoring by UAVs
The paper presents a generalized net (GN) model of the process of terrain observation with
the help of unmanned aerial vehicles (UAVs) for the prevention and rapid detection of …
the help of unmanned aerial vehicles (UAVs) for the prevention and rapid detection of …
Hotspot Classification for Forest Fire Prediction using C5. 0 Algorithm
Forest and land fires impact the destruction of ecosystems and destroy flora and fauna.
Forest fires haze can also disrupt the transportation sector, especially aviation …
Forest fires haze can also disrupt the transportation sector, especially aviation …
Spatiotemporal analysis of wildfire in the Tigris and Euphrates basin: A remote sensing based wildfire potential mapping
AH Velayati, AD Boloorani, M Kiavarz… - Remote Sensing …, 2024 - Elsevier
In recent years, there has been a significant increase in the occurrence of wildfires in
rangelands and forests worldwide. Such events are even more critical in arid and semi-arid …
rangelands and forests worldwide. Such events are even more critical in arid and semi-arid …