Integrating statistical and machine learning approaches to characterise and model the performance of a full-scale wastewater treatment plant

This publication has 62 references indexed in Scilit:

• Interpretable‐AI‐Based Model Structural Transfer Learning to Accelerate Bioprocess Model Construction
  Biotechnology and Bioengineering, 2025
• Unravelling the impact of light spectra on microalgal growth and biochemical composition using principal component analysis and artificial neural network models
  Algal Research, 2024
• Nutrients removal by high-rate activated sludge and its effects on the mainstream wastewater treatment
  Chemical Engineering Journal, 2023
• Improving wastewater treatment plant performance: an ANN-based predictive model for managing average daily overflow and resource allocation optimization using Tabu search
  Asian Journal of Civil Engineering, 2023
• Univariate imputation method for recovering missing data in wastewater treatment process
  Chinese Journal of Chemical Engineering, 2022
• Artificial neural networks for water quality soft-sensing in wastewater treatment: a review
  Artificial Intelligence Review, 2021
• Effect of aeration rate on performance and stability of algal-bacterial symbiosis system to treat domestic wastewater in sequencing batch reactors
  Bioresource Technology, 2016
• Seasonal variation of nutrient loads in treated wastewater effluents and receiving water bodies in Sedibeng and Soshanguve, South Africa
  Environmental Monitoring and Assessment, 2015
• An integrated dynamic model for simulating a full-scale municipal wastewater treatment plant under fluctuating conditions
  Chemical Engineering Journal, 2010
• Descriptive and multivariable analysis of the physico-chemical and biological parameters of Sfax wastewater treatment plant
  Desalination, 2009