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过去几十年关于气候变化的研究景观图书统计分析:机器学习应用的证据
Samuel-Soma M Ajibade1, Abdelhamid Zaidi2, Festus Victor Bekun3,4
1Department of Computer Engineering, Istanbul Ticaret University, Istanbul, Turkey.
Heliyon
|October 2, 2023
概括
机器学习 (ML) 对于理解和应对气候变化 (CC) 至关重要. 研究表明,社会经济和环境影响显著,预计会有越来越多的出版物和引用.
科学领域:
- 跨学科的研究跨越科学,技术,工程,艺术,人文和社会科学.
- 专注于计算工具,特别是机器学习 (ML),用于气候变化 (CC) 研究.
背景情况:
- 气候变化对人类健康,安全和环境构成重大威胁.
- 包括机器学习 (ML) 在内的计算工具越来越多地用于研究,减轻和适应CC.
研究的目的:
- 综合分析气候变化机器学习 (MLCC) 的研究和出版景观.
- 确定MLCC研究中的关键作者,机构,国家和合作模式.
主要方法:
- 对Scopus的出版物进行文献计量分析.
- 关键词同时出现的分析,以确定研究热点.
主要成果:
- 沙姆苏丁·沙希德 (Shamsuddin Shahid) 和马来西亚理工大学 ( Universiti Teknologi Malaysia) 被认为是高生产率的大学.
- 中国科学院是最具生产力的机构,美国和中国是领先的国家.
- 在远程传感等高影响力期刊上的合作是关键的生产力因素.
- 确定了四个主要研究主题:机器学习技术,风险行业,遥感和可持续发展.
结论:
- MLCC的研究表明,有相当大的社会经济,环境和学术影响.
- 该领域预计将在发现,出版物和引用方面持续增长.
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