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通过改进的混合深度学习,提高城市PM2.5度的短期预测

Yin Zhou1, Yaping Lyu2, Xiuli Dang1

  • 1College of Land and Environment, National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, Northeast Key Laboratory of Conservation and Improvement of Cultivated Land, Shenyang Agricultural University, Shenyang, 110866 P. R. China.

Journal of environmental health science & engineering
|August 28, 2025
PubMed
概括

这项研究引入了一种改进的深度学习模型,用于预测颗粒物 (PM2.5) 度. 这种新模型显著减少了预测错误,

关键词:
大气污染双向长期短期记忆神经网络卷积神经网络深度学习预测PM2.5度

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Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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