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人工智能和埃迪共变性:一个审查
Arianna Lucarini1, Mauro Lo Cascio2, Serena Marras2
1Department of Agricultural Sciences, University of Sassari, Viale Italia 39A, 07100 Sassari, Italy; University School for Advanced Studies IUSS Pavia, Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, Italy.
The Science of the total environment
|August 10, 2024
概括
人工智能 (AI) 越来越多地与埃迪共变率 (EC) 方法一起用于监测地球.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 数据科学数据科学数据科学
背景情况:
- 埃迪协差 (EC) 方法测量了地球表面和大气之间的碳,水和能量流.
- 欧洲共同体数据流复杂且丰富,因此非常适合用于人工智能 (AI) 应用.
- 人工智能和欧盟的整合对于实现2030年议程的可持续发展目标 (SDGs) 中概述的气候变化减缓和适应目标至关重要.
研究的目的:
- 在过去的二十年中,对使用EC方法的AI技术进行范围审查.
- 识别流量监测AI-EC研究中的趋势,常见的AI模型和挑战.
- 提出人工智能和欧洲共同体在气候变化研究中的合作的未来方向.
主要方法:
- 采用范围审查方法来收集和分析EC流量监测中AI技术的研究.
- 71个不同的AI算法被识别和分类.
- 审查的重点是过去20年人工智能技术的新性和应用.
主要成果:
- 研究量显著增加,特别是在过去五年.
- 人工智能技术存在缺乏统一性,这是由于不同的环境条件,生态系统和变量.
- 流行的机器学习 (ML) 模型包括随机森林 (RF),支持矢量机 (SVM),人工神经网络 (ANN),支持矢量回归 (SVR) 和K-最近邻居 (KNN).
结论:
- 未来的进步需要计算机科学家和生态学家之间的国际合作.
- 建议研究现代深度学习 (DL) 技术,如变压器和生成人工智能.
- 为了在气候变化流量监测中最佳地利用AI-EC,需要采取战略方法.
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