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

AI-driven climate and disaster modeling

Showing 277-288 of 295 articles

Aligning climate adaptation strategies with 2035 SDG targets for coastal cities

Decoding last glacial maximum conditions through scientific folklore methods and paleoclimate data

Optimizing wildfire containment strategies using AI-driven prediction models and real-time drone surveillance

Simulating magma chamber dynamics to predict volcanic eruption precursors

Updating Cold War research on atmospheric nuclear testing effects using modern climate models

Bridging swarm robotics and ant colony foraging algorithms for disaster response

Optimizing exascale system integration for climate modeling at petabyte scales

Predicting solar flare impacts on Earth's power grids during the 2025-2035 solar maximum

Using AI-driven wildfire prediction models to optimize evacuation routes in urban-adjacent forests

For 2040 urban planning: Modeling microclimate resilience using advanced computational fluid dynamics

Using military-to-civilian tech transfer for next-generation wildfire prediction systems

Across magma chamber dynamics to predict volcanic eruptions with machine learning