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Modeling Multistep Ahead Dissolved Oxygen Concentration Using Improved Support Vector Machines by a Hybrid Metaheuristic Algorithm

Author

Listed:
  • Rana Muhammad Adnan

    (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
    School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Hong-Liang Dai

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Reham R. Mostafa

    (Information Systems Department, Faculty of Computers and Information Sciences, Mansoura University, Mansoura 35516, Egypt)

  • Kulwinder Singh Parmar

    (Department of Mathematics, IKG Punjab Technical University, Jalandhar 144005, India)

  • Salim Heddam

    (Faculty of Science, Agronomy Department, Hydraulics Division University, 20 Août 1955, Route El Hadaik, BP 26, Skikda 21024, Algeria)

  • Ozgur Kisi

    (Department of Civil Engineering, University of Applied Sciences, 23562 Lübeck, Germany
    Department of Civil Engineering, Ilia State University, 0162 Tbilisi, Georgia)

Abstract

Dissolved oxygen (DO) concentration is an important water-quality parameter, and its estimation is very important for aquatic ecosystems, drinking water resources, and agro-industrial activities. In the presented study, a new support vector machine (SVM) method, which is improved by hybrid firefly algorithm–particle swarm optimization (FFAPSO), is proposed for the accurate estimation of the DO. Daily pH, temperature (T), electrical conductivity (EC), river discharge (Q) and DO data from Fountain Creek near Fountain, the United States, were used for the model development. Various combinations of pH, T, EC, and Q were used as inputs to the models to estimate the DO. The outcomes of the proposed SVM–FFAPSO model were compared with the SVM–PSO, SVM–FFA, and standalone SVM with respect to the root mean square errors (RMSE), the mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), and determination coefficient (R 2 ), and graphical methods, such as scatterplots, and Taylor and violin charts. The SVM–FFAPSO showed a superior performance to the other methods in the estimation of the DO. The best model of each method was also assessed in multistep-ahead (from 1- to 7-day ahead) DO, and the superiority of the proposed method was observed from the comparison. The general outcomes recommend the use of SVM–FFAPSO in DO modeling, and this method can be useful for decision-makers in urban water planning and management.

Suggested Citation

  • Rana Muhammad Adnan & Hong-Liang Dai & Reham R. Mostafa & Kulwinder Singh Parmar & Salim Heddam & Ozgur Kisi, 2022. "Modeling Multistep Ahead Dissolved Oxygen Concentration Using Improved Support Vector Machines by a Hybrid Metaheuristic Algorithm," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3470-:d:772317
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    References listed on IDEAS

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