Genetic algorithm optimized back propagation artificial neural network for a study on a wastewater treatment facility cost model

In this study, the genetic algorithm optimized back propagation artificial neural network (GA-BP-ANN) method is used to predict the cost of a wastewater treatment plant. With biological oxygen demand, design volume, catchment area and treatment degree as input data, the total cost and construction c...

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Bibliographic Details
Published in:Desalination and water treatment 2023-01, Vol.282, p.96-106
Main Authors: Yang, Gaiqiang, Xu, Yunfei, Huo, Lijuan, Guo, Dongpeng, Wang, Junwei, Xia, Shuang, Liu, Yahong, Liu, Qi
Format: Article
Language:English
Subjects:
Cost model
Genetic algorithm
Genetic algorithm optimized back propagation artificial neural network
Neural network
Wastewater treatment plant
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Summary:In this study, the genetic algorithm optimized back propagation artificial neural network (GA-BP-ANN) method is used to predict the cost of a wastewater treatment plant. With biological oxygen demand, design volume, catchment area and treatment degree as input data, the total cost and construction cost as output parameters, the cost of a wastewater treatment plant is simulated. Compared with the linear algorithm commonly used before, this method has the following advantages: (1) GA-BP-ANN is suitable for small sample analysis and can effectively improve the stability of data. (2) Remove the influence of subjectivity and provide better help for decision makers. The effectiveness and feasibility of this method are proved theoretically and verified by simulation. The results can provide guidance for the design and operation of sewage treatment plants.
ISSN:1944-3986
DOI:10.5004/dwt.2023.29183