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Found 4 papers, 1 papers with code
A Neural Emulator for Uncertainty Estimation of Fire Propagation
When compared to a related neural model (emulator) which was employed to generate probability maps via ensembles of emulated fires, the proposed approach produces competitive Jaccard similarity scores while being approximately an order of magnitude faster.
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires
We show that popular optimisation cost functions used in the literature can result in PINNs that fail to maintain temporal continuity in modelled fire-fronts when there are extreme changes in exogenous forcing variables such as wind direction.
A Spatio-Temporal Neural Network Forecasting Approach for Emulation of Firefront Models
We propose a dedicated spatio-temporal neural network based framework for model emulation, able to capture the complex behaviour of fire spread models.
An Emulation Framework for Fire Front Spread
Empirical observations of bushfire spread can be used to estimate fire response under certain conditions.
