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Evaluation of daily solar radiation flux using soft computing approaches based on different meteorological information: peninsula vs continent

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Abstract

This study compares single and hybrid soft computing models for estimating daily solar radiation flux for two scenarios. Scenario I developed single soft computing models, including multilayer perceptron (MLP), support vector machines (SVM), adaptive neuro-fuzzy inference system (ANFIS), and multivariate adaptive regression splines (MARS), for estimating daily solar radiation flux at two stations from the USA and South Korea. The MLP model was used to evaluate the effect of factors controlling daily solar radiation flux. Using different combinations of controlling factors as input, the MLP and SVM models, based on evaluation measures, were found to be superior to the ANFIS and MARS models at Big Bend station, USA. In addition, the MLP, SVM, and MARS models performed better than did the ANFIS model at Incheon station, South Korea. Scenario II combined the discrete wavelet transform (DWT) and single soft computing models (e.g., MLP and SVM) for improved performance using 4-input combination. The wavelet-based MLP (WMLP) and SVM (WSVM) models were superior to other single soft computing models (MLP, SVM, ANFIS, and MARS) at two stations. Taylor diagrams, violin plots and point density plots were also utilized to examine the similarity between the observed and estimated solar radiation flux values. Results showed that scenarios I and II can be alternatives for estimating daily solar radiation flux based on different meteorological information, such as peninsular and continental conditions.

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Acknowledgments

The authors would like to reveal our extreme appreciation and gratitude to the Illinois State Water Survey (ISWS), USA, and Korea Meteorological Administration (KMA), South Korea. This is for providing the meteorological information. In addition, the authors also sincerely thank the editors and reviewers for their admirable revision and scientific suggestions.

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Authors and Affiliations

  1. Department of Railroad Construction and Safety Engineering, Dongyang University, Yeongju, 36040, Republic of Korea

    Sungwon Kim

  2. Department of Constructional and Environmental Engineering, Kyungpook National University, Sangju, 37224, Republic of Korea

    Youngmin Seo

  3. Department of Civil Engineering, Graduate University of Advanced Technology-Kerman, P.O. Box 76315-116, Kerman, Iran

    Mohammad Rezaie-Balf

  4. Faculty of Natural Sciences and Engineering, Ilia State University, Tbilisi, Georgia

    Ozgur Kisi

  5. Department of Water Engineering, University of Tabriz, Tabriz, Iran

    Mohammad Ali Ghorbani

  6. Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A & M University, College Station, TX, 77843-2117, USA

    Vijay P. Singh

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Kim, S., Seo, Y., Rezaie-Balf, M. et al. Evaluation of daily solar radiation flux using soft computing approaches based on different meteorological information: peninsula vs continent. Theor Appl Climatol 137, 693–712 (2019). https://doi.org/10.1007/s00704-018-2627-x

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  • DOI: https://doi.org/10.1007/s00704-018-2627-x