Enhancing Real-Time Prediction of Effluent Water Quality of Wastewater Treatment Plant Based on Improved Feedforward Neural Network Coupled with Optimization Algorithm

Enhancing Real-Time Prediction of Effluent Water Quality of Wastewater Treatment Plant Based on Improved Feedforward Neural Network Coupled with Optimization Algorithm

To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality, a machine learning (ML) model was developed by combining an improved feedforward neural network (IFFNN) with an optimization algorithm. Data used as input variables of the IFFNN included hourly influent wate...

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Bibliographic Details
Main Authors: Chen, Y. (Author), Lian, Q. (Author), Peng, J. (Author), Sheng, M. (Author), Wang, Y. (Author), Xie, Y. (Author), Yin, H. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Activated sludge process
artificial intelligence
chemical oxygen demand
Chemical oxygen demand
Chemical-oxygen demands
China
Effluent treatment
Effluent waters
Effluents
Forecasting
genetic algorithm
Genetic algorithms
Input variables
Jiangsu
machine learning
model development
Model development
optimization
Optimization algorithms
Process monitoring
Real-time prediction
recurrent neural network
Recurrent neural networks
Sewage pumping plants
Total nitrogen
Toxicity
Waste water treatment plants
Wastewater treatment
wastewater treatment plant
Wastewater treatment plant effluent
water quality
Water quality
Water quality parameters
Water treatment plants
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