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- W4384694844 endingPage "8275" @default.
- W4384694844 startingPage "8275" @default.
- W4384694844 abstract "Due to the harm forest fires cause to the environment and the economy as they occur more frequently around the world, early fire prediction and detection are necessary. To anticipate and discover forest fires, several technologies and techniques were put forth. To forecast the likelihood of forest fires and evaluate the risk of forest fire-induced damage, artificial intelligence techniques are a crucial enabling technology. In current times, there has been a lot of interest in machine learning techniques. The machine learning methods that are used to identify and forecast forest fires are reviewed in this article. Selecting the best forecasting model is a constant gamble because each ML algorithm has advantages and disadvantages. Our main goal is to discover the research gaps and recent studies that use machine learning techniques to study forest fires. By choosing the best ML techniques based on particular forest characteristics, the current research results boost prediction power." @default.
- W4384694844 created "2023-07-20" @default.
- W4384694844 creator A5015767080 @default.
- W4384694844 creator A5031595723 @default.
- W4384694844 creator A5033673749 @default.
- W4384694844 creator A5082257373 @default.
- W4384694844 date "2023-07-17" @default.
- W4384694844 modified "2023-10-01" @default.
- W4384694844 title "A Brief Review of Machine Learning Algorithms in Forest Fires Science" @default.
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