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Efficiency evaluation of reverse osmosis desalination plant using hybridized multilayer perceptron with particle swarm optimization

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Abstract

The scarcity of freshwater causes the necessity for water delineation of brackish water. Reverse osmosis (RO) is one of the popular strategies characterized with lower cost and simple processing procedure compared to the other desalination techniques. The current research is conducted to investigate the efficiency the RO process based on one-week advance prediction of total dissolved solids (TDS) and permeate flow rate for Sistan and Bluchistan provinces located in Iran region. The water parameters including pH, feed pressure temperature, and conductivity are used to construct the prediction matrix. A newly hybrid data-intelligence (DI) model called multilayer perceptron hybridized with particle swarm optimization (MLP-PSO) is developed for the investigation. The potential of the proposed MLP-PSO model is validated against two predominate DI models including support vector machine (SVM) and M5Tree (M5T) models. The results evidenced the potential of the proposed MLP-PSO model over the SVM and M5T models in predicting the TDS and permeate flow rate. In addition, the proposed model attained lower uncertainty for the simulated data. Overall, the feasibility of the hybridized MLP-PSO achieved remarkable predictability for the RO process.

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Authors and Affiliations

  1. Department of Water Engineering and Hydraulic Structure, Faculty of Civil Engineering, Semnan University, Semnan, Iran

    Mohammad Ehteram

  2. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Sinan Q. Salih

  3. Sustainable Developments in Civil Engineering Research Group, Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Zaher Mundher Yaseen

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  1. Mohammad Ehteram
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  2. Sinan Q. Salih
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  3. Zaher Mundher Yaseen
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Correspondence to Zaher Mundher Yaseen.

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Ehteram, M., Salih, S.Q. & Yaseen, Z.M. Efficiency evaluation of reverse osmosis desalination plant using hybridized multilayer perceptron with particle swarm optimization. Environ Sci Pollut Res 27, 15278–15291 (2020). https://doi.org/10.1007/s11356-020-08023-9

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