Modeling an Adaptive Hybrid Soft Sensor with Co-training Learning toward Applications in Wastewater Treatment-Reference-Cited by-同舟云学术

Modeling an Adaptive Hybrid Soft Sensor with Co-training Learning toward Applications in Wastewater Treatment

Published:2023-10-09 Issue:41 Volume:62 Page:16841-16853
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Wu Jing¹,Tang Lili¹,Jin Shaoqin¹,Li Xuan²,Liu Huan²^ORCID,Li Dong³,Liu Yiqi⁴,Wang Qilin²^ORCID

Affiliation:

1. School of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, Guizhou China

2. Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia

3. The School of Automation, Central South University, Changsha 410 083, China

4. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong China

Funder

Department of Education of Guizhou Province

Basic and Applied Basic Research Foundation of Guangdong Province

Department of Education and Training

Natural Science Foundation of Hainan Province

National Natural Science Foundation of China

Science and Technology Planned Project of Guizhou Province

Guangdong Technology International Cooperation Project Application

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.3c03067

Reference38 articles.

1. Process Monitoring of Quality-Related Variables in Wastewater Treatment Using Kalman-Elman Neural Network-Based Soft-Sensor Modeling

2. A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes

3. Novel Process Monitoring Approach Enhanced by a Complex Independent Component Analysis Algorithm with Applications for Wastewater Treatment

4. PLS-based soft-sensor to predict ammonium concentration evolution in hollow fibre membrane contactors for nitrogen recovery

5. Semi-supervised adaptive PLS soft-sensor with PCA-based drift correction method for online valuation of NOx emission in industrial water-tube boiler