An interpretable machine learning model for predicting forest fire danger based on Bayesian optimization
As global warming increases forest fire frequency, early prevention and effective management become crucial. This requires models that are both accurate and easily understood. However, traditional machine learning models, which typically use preset parameters, are often inaccurate and hard to interp...
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| Principais autores: | , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Maximum Academic Press
2024-01-01
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| Serier: | Emergency Management Science and Technology |
| Fag: | |
| Online adgang: | https://www.maxapress.com/article/doi/10.48130/emst-0024-0026 |
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