Tackling Climate Change with Machine Learning
Борьба с изменением климата с помощью машинного обучения
2022-02-07
SCID: 54.1/n79nt94v
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climate changedisaster managementgreenhouse gas emissionsmachine learningsmart grids
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Abstract (AI)
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.
Key Findings
1
Effective climate applications require collaboration between machine-learning experts and other fields.
2
High-impact opportunities exist for machine learning in areas such as smart grids, particularly where current capabilities have gaps.
3
Machine learning can contribute to climate-change mitigation by helping reduce greenhouse-gas emissions.
4
Machine learning can support societal adaptation to climate change, including applications in disaster management.
5
The paper identifies both promising research questions and business opportunities for the machine-learning community’s climate efforts.
Research Object
Applications of machine learning to climate change mitigation and adaptation problems
Research Subject
Applications of machine learning for reducing greenhouse gas emissions and helping society adapt to climate change
Publication Details
Publication Date
2022-02-07
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References available in scid.ai4
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Machine Learning in Agriculture: A Review2018