机器学习方法对印度热浪事件预测的比较分析
Ritesh Choudary V1, Anita Christaline Johnvictor2, Prem Sankar N3
1School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, India.
Scientific reports
|July 2, 2025
概括
准确的热浪预测对于减轻气候变化影响至关重要. 这项研究比较了机器学习模型来对印度奈的热浪事件进行分类,以改进预警系统.
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:
- 热浪是长时间出现极高温度的情况,对人类健康,动物福利和农业构成严重风险.
- 气候变化正在增加全球热浪的频率和强度,需要改进预测能力.
- 准确及时预测热浪对于制定有效的缓解和适应战略至关重要.
研究的目的:
- 对各种机器学习模型进行比较分析,以对热浪事件进行分类.
- 为了评估模型性能,使用来自印度泰米尔纳德邦奈的时间序列数据集.
- 为了应对诸如热浪预测中的阶级不平衡等挑战.
主要方法:
- 机器学习模型的比较分析,包括随机森林,CNN,LightGBM,LSTM,变压器,SVM,GNN,XGBoost和自动编码器.
- 利用来自印度奈的时间序列天气数据集.
- 研究了处理阶级不平衡的策略,以提高预测准确度.
主要成果:
- 用于热浪分类的多个机器学习模型的性能评估.
- 确定有效的策略来克服阶级不平衡问题.
- 展示了先进机器学习在准确预测热浪方面的潜力.
结论:
- 通过先进的机器学习技术,可以准确预测热浪.
- 可以制定有效的缓解计划,以保护人类,动物和植物免受热浪影响.
- 这项研究提供了对优化机器学习模型进行极端天气事件预测的见解.
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