Importance Sampling for Cost-Optimized Estimation of Burn Probability Maps in Wildfire Monte Carlo Simulations
Background: Wildfire modelers rely on Monte Carlo simulations of wildland fire to produce burn probability maps. These simulations are computationally expensive. Methods: We study the application of importance sampling to accelerate the estimation of burn probability maps, using L2 distance as the m...
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| Principais autores: | , |
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| 格式: | Artigo |
| 語言: | Inglês |
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MDPI AG
2024-12-01
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| 叢編: | Fire |
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| 在線閱讀: | https://www.mdpi.com/2571-6255/7/12/455 |
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