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Cites:

Information Journal Paper

Title

Runoff Prediction Using Black and Gray Box Models

Pages

  177-192

Abstract

 In the past decade, machine learning is considered to be a promising approach for empirical RainfallRunoff modeling as a useful complement to hydrologic models, particularly in basins where data to support process-based models are limited. In this paper, we used black-box models (i. e. neuro-fuzzy and support vector machine) and gray-box models (i. e. TOPMODEL and HBV) for simulating the transformation of daily Rainfall-Runoff process in the Nodeh Khormaloo watershed located in Gorganrood River Basin and compare their performance in terms of predictive accuracy. For the black-box models, the three input vectors including discharge, temperature and Rainfall were selected in nine different scenarios based on the sequential time series data. Our result showed that the neuro-fuzzy model which consisted of three antecedent values of flow and one antecedent values of temperature outperformed other models when the root mean square error and coefficient of determination were used as quality indicators. In general, the black-box models outperformed the HBV and TOPMODEL simulations for the calibration and validation data sets. A detailed comparison of the overall performance indicated that the neuro-fuzzy and SVM models predicted Runoff in warm months were consistently lower than that in the cold months.

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  • Cite

    APA: Copy

    BAGHERPOUR, M., SEYEDIAN, S.M., FATHABADI, A., & MOHAMMADI, A.. (2019). Runoff Prediction Using Black and Gray Box Models. IRAN-WATER RESOURCES RESEARCH, 14(5 ), 177-192. SID. https://sid.ir/paper/100192/en

    Vancouver: Copy

    BAGHERPOUR M., SEYEDIAN S.M., FATHABADI A., MOHAMMADI A.. Runoff Prediction Using Black and Gray Box Models. IRAN-WATER RESOURCES RESEARCH[Internet]. 2019;14(5 ):177-192. Available from: https://sid.ir/paper/100192/en

    IEEE: Copy

    M. BAGHERPOUR, S.M. SEYEDIAN, A. FATHABADI, and A. MOHAMMADI, “Runoff Prediction Using Black and Gray Box Models,” IRAN-WATER RESOURCES RESEARCH, vol. 14, no. 5 , pp. 177–192, 2019, [Online]. Available: https://sid.ir/paper/100192/en

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