Issue 6, 2023
From the journal:

Environmental Science: Water Research & Technology

Correction: Exploring potential dual-stage attention based recurrent neural network machine learning application for dosage prediction in intelligent municipal management

Xusheng Fang,a   Jian Zang,*b   Zhengang Zhai,a   Li Zhang,a   Ziyu Shub  and  Yuqi Liangc  

* Corresponding authors

a China Electronics Technology Group Corporation 36th Research Institute, China

b National Center for International Research of Low-carbon and Green Buildings (Ministry of Science and Technology), School of Civil Engineering, Chongqing University, China
E-mail: Jian.zang@cqu.edu.cn

c Faculty of Digital Humanities, King's College of London, UK

Abstract

Correction for ‘Exploring potential dual-stage attention based recurrent neural network machine learning application for dosage prediction in intelligent municipal management’ by Xusheng Fang et al., Environ. Sci.: Water Res. Technol., 2023, 9, 890–899, https://doi.org/10.1039/D2EW00560C.

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Article information

DOI
https://doi.org/10.1039/D3EW90018E
Article type
Correction
Submitted
17 May 2023
Accepted
17 May 2023
First published
23 May 2023
This article is Open Access
Creative Commons BY license

Environ. Sci.: Water Res. Technol., 2023,9, 1750-1750

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Correction: Exploring potential dual-stage attention based recurrent neural network machine learning application for dosage prediction in intelligent municipal management

X. Fang, J. Zang, Z. Zhai, L. Zhang, Z. Shu and Y. Liang, Environ. Sci.: Water Res. Technol., 2023, 9, 1750 DOI: 10.1039/D3EW90018E

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