Modeling and diagnosis of water quality parameters in wastewater treatment process based on improved particle swarm optimization and self-organizing neural network-Reference-Cited by-同舟云学术

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Modeling and diagnosis of water quality parameters in wastewater treatment process based on improved particle swarm optimization and self-organizing neural network

Published:2024-08 Issue:4 Volume:12 Page:113142
ISSN:2213-3437
Container-title:Journal of Environmental Chemical Engineering
language:en
Short-container-title:Journal of Environmental Chemical Engineering

Author:

Dai Hongliang,Liu Xingyu,Zhao Jinkun,Wang Zeyu,Liu Yanpeng,Zhu Guangcan,Li Bing,Abbasi Haq Nawaz,Wang Xingang

Funder

Postdoctoral Research Foundation of China

National Natural Science Foundation of China

Joint Project of Industry-University-Research of Jiangsu Province

China Postdoctoral Science Foundation

Postdoctoral Science Foundation of Jiangxi Province

Qinglan Project of Jiangsu Province of China

Publisher

Elsevier BV

Reference53 articles.

1. SBR-Extended Kalman Filter model-based fault diagnosis and signal reconstruction for the papermaking wastewater treatment process;Niu;J. Water Process Eng.,2023

2. Improved data-based fault detection strategy and application to distillation columns;Madakyaru;Process Saf. Environ. Prot.,2017

3. Voltage-correlation based multi-fault diagnosis of lithium-ion battery packs considering inconsistency;Lin;J. Clean. Prod.,2022

4. An advanced control system for nitrogen removal and energy consumption optimization in full-scale wastewater treatment plants;Ruano;J. Water Process Eng.,2024

5. An auto-deployed model-based fault detection and diagnosis approach for Air Handling Units using BIM and Modelica;Andriamamonjy;Autom. Constr.,2018

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