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Particle swarm optimization-based radial basis function network for estimation of reference evapotranspiration

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Abstract

Accurate estimation of the reference evapotranspiration (ET0) is important for the water resource planning and scheduling of irrigation systems. For this purpose, the radial basis function network with particle swarm optimization (RBFN-PSO) and radial basis function network with back propagation (RBFN-BP) were used in this investigation. The FAO-56 Penman–Monteith equation was used as reference equation to estimate ET0 for Serbia during the period of 1980–2010. The obtained simulation results confirmed the proposed models and were analyzed using the root mean-square error (RMSE), the mean absolute error (MAE), and the coefficient of determination (R 2). The analysis showed that the RBFN-PSO had better statistical characteristics than RBFN-BP and can be helpful for the ET0 estimation.

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Acknowledgments

The study is supported by the Ministry of Education, Science and Technological Development, Republic of Serbia (Grant No. TR37003). We would like to acknowledge to colleges Mazdak Zamani and Monaf Amiromojedi from Advanced Informatics School (AIS), Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia, for their contribution in data simulation and analyzing. Mazdak Zamani did data simulation, calculation, and result analyzing. Monaf Amiromojedi did analyzing of the measured data and grammar proofreading.

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Authors and Affiliations

  1. Department for Mechatronics and Control, Faculty of Mechanical Engineering, University of Nis, Aleksandra Medvedeva 14, 18000, Nis, Serbia

    Dalibor Petković

  2. Faculty of Civil Engineering and Architecture, University of Nis, Aleksandra Medvedeva 14, 18000, Nis, Serbia

    Milan Gocic & Slavisa Trajkovic

  3. Computer Science Department, College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

    Sultan Noman Qasem

  4. Department of Computer Science, Faculty of Applied Sciences, Taiz University, Taiz, Yemen

    Sultan Noman Qasem

  5. Department of Computer System and Information Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Shahaboddin Shamshirband

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  1. Dalibor Petković
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  2. Milan Gocic
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  3. Shahaboddin Shamshirband
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  4. Sultan Noman Qasem
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  5. Slavisa Trajkovic
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Correspondence to Dalibor Petković.

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Petković, D., Gocic, M., Shamshirband, S. et al. Particle swarm optimization-based radial basis function network for estimation of reference evapotranspiration. Theor Appl Climatol 125, 555–563 (2016). https://doi.org/10.1007/s00704-015-1522-y

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