[HTML][HTML] Deep graphical regression for jointly moderate and extreme Australian wildfires
Recent wildfires in Australia have led to considerable economic loss and property
destruction, and there is increasing concern that climate change may exacerbate their …
destruction, and there is increasing concern that climate change may exacerbate their …
Multimodal fusion-based spatiotemporal incremental learning for ocean environment perception under sparse observation
L Lei, J Huang, Y Zhou - Information Fusion, 2024 - Elsevier
Accurate ocean environment perception is crucial for weather and climate prediction.
Environmental limitations and deployment costs constrain satellite and buoy real-time …
Environmental limitations and deployment costs constrain satellite and buoy real-time …
On the locality of local neural operator in learning fluid dynamics
X Ye, H Li, J Huang, G Qin - Computer Methods in Applied Mechanics and …, 2024 - Elsevier
This paper launches a thorough discussion on the locality of local neural operator (LNO),
which is the core that enables LNO great flexibility on varied computational domains in …
which is the core that enables LNO great flexibility on varied computational domains in …
Using echo state networks to inform physical models for fire front propagation
Wildfires can be devastating, causing significant damage to property, ecosystem disruption,
and loss of life. Forecasting the evolution of wildfire boundaries is essential to real-time …
and loss of life. Forecasting the evolution of wildfire boundaries is essential to real-time …
Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease
To mitigate the negative effects of emerging wildlife diseases in biodiversity and public
health it is critical to accurately forecast pathogen dissemination while incorporating relevant …
health it is critical to accurately forecast pathogen dissemination while incorporating relevant …
Physics-informed neural networks for parameter learning of wildfire spreading
Wildland fires pose a terrifying natural hazard, underscoring the urgent need to develop data-
driven and physics-informed digital twins for wildfire prevention, monitoring, intervention …
driven and physics-informed digital twins for wildfire prevention, monitoring, intervention …
Data-driven modeling of wildfire spread with stochastic cellular automata and latent spatio-temporal dynamics
N Grieshop, CK Wikle - Spatial Statistics, 2024 - Elsevier
We propose a Bayesian stochastic cellular automata modeling approach to model the
spread of wildfires with uncertainty quantification. The model considers a dynamic …
spread of wildfires with uncertainty quantification. The model considers a dynamic …
PINN-Ray: A Physics-Informed Neural Network to Model Soft Robotic Fin Ray Fingers
Modelling complex deformation for soft robotics provides a guideline to understand their
behaviour, leading to safe interaction with the environment. However, building a surrogate …
behaviour, leading to safe interaction with the environment. However, building a surrogate …
[HTML][HTML] LSA-PINN: A new method based on Physics-Informed Neural Network with lightweight self-attention for solving modified Bloch equation
J Liu, W Wang, H **a, Y Yuan, X Lei, H Pei - Results in Physics, 2024 - Elsevier
Abstract The Spin-Exchange Relaxation-Free (SERF) atomic magnetometers play an
increasingly significant roles in cardiac and brain magnetometry fields, etc. For the SERF …
increasingly significant roles in cardiac and brain magnetometry fields, etc. For the SERF …
Stochastic Approaches Systems to Predictive and Modeling Chilean Wildfires
Whether due to natural causes or human carelessness, forest fires have the power to cause
devastating damage, alter the habitat of animals and endemic species, generate insecurity …
devastating damage, alter the habitat of animals and endemic species, generate insecurity …