人工智能在能源和气候变化建模中的进展与展望

IF 13 Q1 ENERGY & FUELS
Mobolaji Shobanke, Mehul Bhatt, Ekundayo Shittu
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引用次数: 0

摘要

本文探讨了人工智能和机器学习的应用,以破译气候变化事件的战略反应,并为能源系统的管理提供信息。鉴于全球对可持续和高效能源解决方案的日益依赖以及人工智能和机器学习的兴起,评估能源和气候变化建模的现有常规以确定进一步应用的领域已成为当务之急。对当代文献进行系统回顾的过程强调了人工智能和机器学习驱动的能源和气候变化建模系统中优化和预测分析的重大进展。本文通过研究人工智能和机器学习在能源建模和气候变化评估中的应用,为能源创新的前沿研究做出了贡献。本文弥合了研究、开发和实施之间的差距,对人工智能和机器学习在分析未来能源转型和减缓和适应气候变化方面的更广泛应用提供了重要见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancements and future outlook of Artificial Intelligence in energy and climate change modeling
This paper explores the employment of artificial intelligence and machine learning to decipher strategic responses to incidences of climate change and to inform the management of energy systems. Given the increasing global dependence on sustainable and efficient energy solutions and the rise of artificial intelligence and machine learning, it has become imperative to evaluate existing routines in energy and climate change modeling to identify areas for further application. The process of conducting a systematic review of the contemporary literature highlights significant advances in optimization and predictive analytics within energy and climate change modeling systems driven by artificial intelligence and machine learning. This paper contributes to cutting-edge research on energy innovation, i.e., through the examination of the applications of artificial intelligence and machine learning in energy modeling and climate change assessments. The article bridges the gaps between research, development, and implementation with significant insights into the broader applications of artificial intelligence and machine learning in the analysis of future energy transitions and climate change mitigation and adaptation.
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来源期刊
Advances in Applied Energy
Advances in Applied Energy Energy-General Energy
CiteScore
23.90
自引率
0.00%
发文量
36
审稿时长
21 days
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