بررسی عدم‌قطعیت مدل‌های شبکۀ عصبی مصنوعی و عصبی فازی در پیش بینی رواناب حوضۀ رودخانۀ بشار

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[2].          Hassanzadeh Y, Abbaszadeh H. Investigating Discharge Coefficient of Slide Gate-Sill Combination Using Expert Soft Computing Models, Journal of Hydraulic Structures,2023, 63–80.

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[5].          Nadiri AA, Yousefzadeh S. A Comparison of the Performance of Artificial Neural Network, Fuzzy Logic and Adaptive Neuro-Fuzzy Inference Systems Models in the Estimation of Aquifer Hydraulic Conductivity. A Case Study: Maraghe-Bonab Aquifer, Hydrogeomorphology, 2017, 21–40.

[6].          Razzaghzadeh Z, Nourani V, Behfar N. The conjunction of feature extraction method with AI-based ensemble statistical downscaling models, Amirkabir Journal of Civil Engineering, 2020.

[7].          Hassanzadeh Y, Moazamnia M, Sadeghfam S, Nadiri, A A. Hydraulic conductivity and uncertainty analysis of between-models and input data by using Bayesian model averaging of artificial intelligence model, Amirkabir Journal of Civil Engineering, 2020, 2171–2190.

[8].          Zeinalie M, golabi, M R, Niksokhan M H, Sharifi, M R. Modeling Daily River Flow Using Simulator Meta-Models (Case study: Gamasiab River), Journal of Environmental Science and Technology, 2020, 121–133.

[9].          Seifi, A, Ehteram, M, Singh, V P, Mosavi A. Modeling and uncertainty analysis of groundwater level using six evolutionary optimization algorithms hybridized with ANFIS, SVM, and ANN, Sustainability, 2020, 4023.

[10].        Riahi-Madvar H, Seifi A. Uncertainty analysis in bed load transport prediction of gravel bed rivers by ANN and ANFIS, Arabian Journal of Geosciences, 2018, 1–20.

[11].        Daneshfaraz R, Norouzi R, Ebadzadeh P, Di Francesco S, Abraham J P. Experimental study of geometric shape and size of sill effects on the hydraulic performance of sluice gates, Water, 2023, 314.

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