PAPER making! FROM THE PUBLISHERS OF PAPER TECHNOLOGY INTERNATIONAL ® FROM THE PUBLISHERS OF PAPER TEC Volume 11, Number 3, 2025
Effluent Quality Prediction of Papermaking Wastewater Treatment Processes Using Stacking Ensemble Learning HONGBIN LIU 1,2 , CHEN XIN 1 , HAO ZHANG 1 , FENGSHAN ZHANG 2 & MINGZHI HUANG 3 Advanced process modeling methods have been used for prediction and monitoring of key quality indices in wastewater treatment processes. However, single conventional models usually have limited precision accuracy when predicting the effluent indices in papermaking wastewater treatment processes. To achieve a better prediction accuracy and robustness, we propose a stacking ensemble learning (SEL) method which utilizes the advantages of the internal base-learning models. The method combines base-learning algorithms including partial least squares, support vector regression, and artificial neural networks with a meta-learning algorithm, which is a multiple-response linear regression in this work. To evaluate the model performance in practical applications, both real wastewater data and simulation wastewater data are used for modeling. The predicted effluent indices include effluent suspended solid (SS eff ), effluent chemical oxygen demand (COD eff ), effluent ammonia concentration (SNH eff ), and effluent nitrate concentration (SNO eff ). Compared with base-learning algorithms and other ensemble learning methods, the results demonstrate that SEL significantly improves the prediction accuracy and reduces the prediction errors, which provides a new way to achieve real-time monitoring of wastewater treatment processes. Contact information: 1. 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 Company Ltd., Dongying 257335, China. 3. SCNU Environmental Research Institute, Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China. IEEE Access, Vol.8, 2020, 180844-180854.
Digital Object Identifier 10.1109/ACCESS.2020.3028683 Creative Commons Attribution 4.0 International License
The Paper Industry Technical Association (PITA) is an independent organisation which operates for the general benefit of its members – both individual and corporate – dedicated to promoting and improving the technical and scientific knowledge of those working in the UK pulp and paper industry. Formed in 1960, it serves the Industry, both manufacturers and suppliers, by providing a forum for members to meet and network; it organises visits, conferences and training seminars that cover all aspects of papermaking science. It also publishes the prestigious journal Paper Technology International ® and the PITA Annual Review , both sent free to members, and a range of other technical publications which include conference proceedings and the acclaimed Essential Guide to Aqueous Coating .
Article 6 – Wastewater Treatment
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