43 citations · 122 across the 16 of their papers we have counts for
4 papers · 2 filters
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires
Joel Janek Dabrowski, Daniel Edward Pagendam, James Hilton +5
We apply the Physics Informed Neural Network (PINN) to the problem of wildfire fire-front modelling. We use the PINN to solve the level-set equation, which is a partial differentia…
A Spatio-Temporal Neural Network Forecasting Approach for Emulation of Firefront Models
Andrew Bolt, Carolyn Huston, Petra Kuhnert +3
Computational simulations of wildfire spread typically employ empirical rate-of-spread calculations under various conditions (such as terrain, fuel type, weather). Small perturbati…
Deep Learning for Prawn Farming: Forecasting and Anomaly Detection
Joel Janek Dabrowski, Ashfaqur Rahman, Andrew Hellicar +2
We present a decision support system for managing water quality in prawn ponds. The system uses various sources of data and deep learning models in a novel way to provide 24-hour f…
An Emulation Framework for Fire Front Spread
Andrew Bolt, Joel Janek Dabrowski, Carolyn Huston +1
Forecasting bushfire spread is an important element in fire prevention and response efforts. Empirical observations of bushfire spread can be used to estimate fire response under c…