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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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Fire |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-6255/7/12/455 |
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