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

AI-driven climate and disaster modeling

Showing 61-72 of 295 articles

Mapping magma chamber dynamics using seismic tomography and geochemical proxies

Marrying ethology with swarm robotics to design adaptive disaster rescue systems

Predicting regional climate extremes aligned with El Niño oscillations using hybrid AI models

Using military-to-civilian tech transfer for next-generation disaster response robots

During grand solar minimum: predicting global climate anomalies with improved solar models

Predicting earthquake risks by analyzing continental drift velocities across microplate boundaries

Planning for the next glacial period through coupled climate-ice sheet modeling

Planning for next glacial period using paleomagnetic reversal data and climate models

Improving earthquake prediction via computational lithography optimizations in seismic sensor arrays

Anticipating 2080 population peaks through integrated demographic-climate modeling

Spanning tectonic plate movements to predict megathrust earthquake nucleation zones

Employing neuromorphic computing architectures for real-time earthquake prediction