Atomfair Brainwave Hub: SciBase II / Artificial Intelligence and Machine Learning / AI-driven climate and disaster modeling

AI-driven climate and disaster modeling

Showing 121-132 of 295 articles

Spanning tectonic plate movements to predict seismic hazards in urban megacities

Predicting climate impacts during magnetic pole reversal using coupled geophysical models

Through magnetic pole reversal simulations to predict geomagnetic field collapse effects

For impact winter resilience using stratospheric aerosol reflectance modeling

Across continental drift velocities via quantum annealing methods

Optimizing swarm robotics algorithms for disaster response during grand solar minimum events

Using swarm robotics for autonomous disaster relief construction projects

Morphological computation in soft robotics for adaptive disaster response systems

Employing neglected mathematical tools for modeling chaotic ecosystems

With phase-change material synapses in neuromorphic disaster prediction networks

Volcanic winter preparedness through atmospheric sulfur injection modeling

Employing neuromorphic computing architectures for real-time wildfire prediction and management