万维提示：
1、该刊只有国际刊号！
2、投稿方式：在线投稿。
3、官网网址：
https://www.sciencedirect.com/journal/energy-and-ai
4、投稿系统：
https://www2.cloud.editorialmanager.com/eai/default2.aspx
5、主办单位相关网址：
http://www.lib.tju.edu.cn/show.jsp?classid=202102072014372093&informationid=202102072015334737
6、出刊日期：季刊，一年出版4期。
2024年3月6日星期三
Energy and AI（能源与人工智能）简介
期刊简介：
国际学术期刊Energy and AI（《能源与人工智能》）由天津大学内燃机燃烧学国家重点实验室联合国际知名学术出版社爱思唯尔创办，致力于提供一个快速权威的学术交流和发表平台，传播和促进人工智能在能源领域应用的最新进展。该刊由我校校长金东寒院士担任主编，由英国皇家工程院院士RafaellaOcone教授、天津大学焦魁教授和英国拉夫堡大学JinXuan教授担任副主编。
该期刊侧重于人工智能的创新应用，尤其是涉及能够解决能源系统、能源材料、能源化学、能源利用与转换、能源与社会等领域的关键挑战，以及能源研究中的其它重要紧迫问题的研究工作。该期刊还接收通过特定的人工智能技术与方法推进能源、脱碳和可持续发展的研究论文，包括数据驱动方法、优化算法和人工智能伦理等。
Energy and AI 的目标是成为能源和人工智能交叉领域前沿研究的权威期刊，只关注能源或人工智能单一方面的论文不适合发表在该期刊上。该期刊主要刊登研究(Research)、短讯(Short communication)、展望(Perspective)、综述(Review) 等类型的文章。欢迎广大学者踊跃投稿。
作者指南Guide for Authors
【官网信息】
Aims and scope
Energy and AI provides a fast and authoritative open access platform to disseminate the latest research progress in the cross-disciplinary area of energy and artificial intelligence (AI). The journal focuses on innovative applications of AI that address the critical challenges in energy systems, energy materials, energy chemistry, energy utilization & conversion, and energy & society, as well as other important pressing issues in energy research. The journal also considers papers on the development of bespoke AI technologies and methodologies for advancing energy, decarbonization and sustainable development, such as data-driven approaches, optimization algorithms and AI ethics.
Energy and AI aims to become a leading journal for cutting-edge research at the interface between energy and AI. Papers purely focusing on a single aspect of energy or AI are not suitable for the journal.
The journal considers full length, short communications, perspective and review articles, and publishes 4 volumes per year.
Focal points of the journal include, but are not limited to:
Automation of science discovery related to energy materials and chemistry
Digital twining or big data analytics of complex energy processes/systems
Data-driven design of energy materials, devices and systems
Internet-of-things and cyber-physical energy systems
AI for human factors in energy related activities
Virtual reality applied to energy and environment
Autonomous systems for energy efficiency maximalization
Hardware for data collections in energy systems
Data Science for energy applications
Hybrid data-driven and physical modelling for energy related problems
Intelligent control of energy systems
AI, energy and society
AI safety, reliability and ethics within energy applications
AI for life-cycle assessment or energy and decarbonization roadmaps
Energy robotics
……
更多详情：
https://www.elsevier.com/journals/energy-and-ai/2666-5468/guide-for-authors
