基于机器学习的方法来预测由于气候变化的冰川融化和解决方案
Piyush Pant1, Anand Singh Rajawat1, S B Goyal2
1School of Computer Sciences and Engineering, Sandip University, Nashik, India.
概括
气候变化威胁着所有的生命. 这项研究使用机器学习和多变量线性回归来预测冰川冰融,确定化石燃料燃烧是主要的污染源.
科学领域:
- 环境科学 环境科学
- 气候变化研究 气候变化研究
- 数据科学数据科学数据科学
背景情况:
- 气候变化对全球生态系统和人类健康构成存在的威胁.
- 全球气温上升,极端天气事件和污染是人类活动的直接后果,如森林砍伐和化石燃料燃烧.
- 国际报告显示,自1880年代以来,全球气温上升超过1°C.
研究的目的:
- 使用机器学习开发冰川冰融的预测模型.
- 确定影响冰川融化的关键环境特征,并确定主要污染源.
- 提高社会对人类造成的环境破坏的认识,并促进集体行动.
主要方法:
- 使用机器学习算法,特别是多变量线性回归,来训练预测模型.
- 分析和操纵各种环境特征,以确定它们对冰川融化的影响.
- 专注于数据采集的挑战和模型开发的系统要求.
主要成果:
- 确定燃烧煤炭和化石燃料是导致气候变化的污染的主要来源.
- 开发了一种能够根据所选特征预测冰川冰融的模型.
- 突出了特定特征对冰损失速度的重大影响.
结论:
- 机器学习为了解和减轻气候变化影响提供了一种强大的技术方法.
- 有必要采取科学研究为基础的紧急集体行动,以应对环境破坏.
- 解决化石燃料造成的污染对于为后代保护地球至关重要.
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