Optimized deep learning models for effluent prediction in wastewater treatment processes-Reference-Cited by-同舟云学术

Optimized deep learning models for effluent prediction in wastewater treatment processes

Published:2024 Issue:5 Volume:10 Page:1208-1218
ISSN:2053-1400
Container-title:Environmental Science: Water Research & Technology
language:en
Short-container-title:Environ. Sci.: Water Res. Technol.

Author:

Yang Canyun¹,Guo Zhuoyue¹,Geng Yun¹,Zhang Fengshan²,Wei Wenguang²,Liu Hongbin¹³²^ORCID

Affiliation:

1. Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China

2. Laboratory for Comprehensive Utilization of Paper Waste of Shandong Province, Shandong Huatai Paper Co. Ltd., Dongying 257335, China

3. Guangxi Key Laboratory of Clean Pulp & Papermaking and Pollution Control, College of Light Industry and Food Engineering, Guangxi University, Nanning 530004, China

Abstract

Aiming at prediction of water quality in wastewater treatment systems, an optimized deep learning model with high prediction performance is proposed.

Funder

Guangxi Key Laboratory of Clean Pulp and Papermaking and Pollution Control

Natural Science Foundation of Shandong Province

Natural Science Foundation of Jiangsu Province

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/EW/D3EW00875D

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