Artificial intelligence-based solutions for climate change: a review
Climate change is a major threat already causing system damage to urban and natural
systems, and inducing global economic losses of over $500 billion. These issues may be …
systems, and inducing global economic losses of over $500 billion. These issues may be …
A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …
with early applications including neural networks and expert systems. Since then, the field …
Forecasting global weather with graph neural networks
R Keisler - arXiv preprint arXiv:2202.07575, 2022 - arxiv.org
We present a data-driven approach for forecasting global weather using graph neural
networks. The system learns to step forward the current 3D atmospheric state by six hours …
networks. The system learns to step forward the current 3D atmospheric state by six hours …
[PDF][PDF] Integrating physics-based modeling with machine learning: A survey
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …
require novel methodologies that are able to integrate traditional physics-based modeling …
Deep learning and process understanding for data-driven Earth system science
Abstract Machine learning approaches are increasingly used to extract patterns and insights
from the ever-increasing stream of geospatial data, but current approaches may not be …
from the ever-increasing stream of geospatial data, but current approaches may not be …
Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
WeatherBench: a benchmark data set for data‐driven weather forecasting
Data‐driven approaches, most prominently deep learning, have become powerful tools for
prediction in many domains. A natural question to ask is whether data‐driven methods could …
prediction in many domains. A natural question to ask is whether data‐driven methods could …
Deploying artificial intelligence for climate change adaptation
Artificial Intelligence (AI) is believed to have a significant potential use in tackling climate
change. This paper explores the connections between AI and climate change research as a …
change. This paper explores the connections between AI and climate change research as a …
A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects
I Palomares, E Martínez-Cámara, R Montes… - Applied …, 2021 - Springer
Abstract The17 Sustainable Development Goals (SDGs) established by the United Nations
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
Integrating scientific knowledge with machine learning for engineering and environmental systems
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …
require novel methodologies that are able to integrate traditional physics-based modeling …