Deep learning based soft sensor for microbial wastewater treatment efficiency prediction-Reference-Cited by-同舟云学术

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Deep learning based soft sensor for microbial wastewater treatment efficiency prediction

Published:2023-12 Issue: Volume:56 Page:104259
ISSN:2214-7144
Container-title:Journal of Water Process Engineering
language:en
Short-container-title:Journal of Water Process Engineering

Author:

Cao Jiafei,Xue Anke,Yang Yong,Cao Wei,Hu Xiaojing,Cao Guanglong,Gu Jiahao,Zhang Le,Geng Xiulin

Funder

Hangzhou Dianzi University

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Process Chemistry and Technology,Waste Management and Disposal,Safety, Risk, Reliability and Quality,Biotechnology

Reference35 articles.

1. Advances in control technologies for wastewater treatment processes: status, challenges, and perspectives;Iratni;IEEE/CAA Journal of Automatica Sinica,2019

2. Prediction of the five-day biochemical oxygen demand and chemical oxygen demand in natural streams using machine learning methods;Najafzadeh;Environ. Monit. Assess.,2019

3. Prediction of effluent concentration in a wastewater treatment plant using machine learning models;Guo;J. Environ. Sci.,2015

4. Estimating the chemical oxygen demand of petrochemical wastewater treatment plants using linear and nonlinear statistical models–a case study;Abouzari;Chemosphere,2021

5. Optimizing dissolved oxygen requirement and energy consumption in wastewater treatment plant aeration tanks using machine learning;Qambar;Journal of Water Process Engineering,2022

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1. Dynamic multi-objective optimization control for wastewater treatment process based on modal decomposition and hybrid neural network;Journal of Water Process Engineering;2024-05

2. Soft-sensor estimation via parameter fitting and dynamic optimization in an experimental batch butadiene homopolymerization reactor;Computers & Chemical Engineering;2024-04

3. Multi-Step Short-Term Wind Power Prediction Model Based on CEEMD and Improved Snake Optimization Algorithm;IEEE Access;2024

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