An air quality prediction model based on improved Vanilla LSTM with multichannel input and multiroute output

作者：

Highlights：

• An air quality prediction model IVLSTM-MCMR is proposed based on deep learning.

• The number of parameters in IVLSTM-MCMR is reduced to accelerate the convergence.

• The improved linear similarity dynamic time warping is introduced in IVLSTM-MCMR.

• The integration of multi-channel data input and multi-route output is designed.

摘要

•An air quality prediction model IVLSTM-MCMR is proposed based on deep learning.•The number of parameters in IVLSTM-MCMR is reduced to accelerate the convergence.•The improved linear similarity dynamic time warping is introduced in IVLSTM-MCMR.•The integration of multi-channel data input and multi-route output is designed.

论文关键词：Long short-term memory (LSTM),Air quality prediction,Deep learning,Dynamic time warping

论文评审过程：Received 24 October 2021, Revised 20 July 2022, Accepted 3 August 2022, Available online 27 August 2022, Version of Record 31 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118422