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使用多式联运数据和动态建模技术进行先进的空气质量预测

Umesh Kumar Lilhore1, Sarita Simaiya2, Rajesh Kumar Singh3

  • 1Department of Computer Science and Engineering, Galgotias University, Greater Noida, UP, India.

Scientific reports
|July 30, 2025
PubMed
概括

一个新的混合深度学习模型通过整合多种数据源和CNN,BiLSTM和神经ODEs等先进技术来改善空气质量预测,从而为更好的环境管理提供更准确的预测.

关键词:
空气质量 空气质量深度学习是一种深度学习.气象数据 气象数据多式联络是多式联络.污染物的分布 污染物的分布这是卫星图像.传感器数据 传感器数据

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