Parametric and nonparametric regression models in study of the length of hydraulic jump after a multi-segment sharp-crested V-notch weir

Saadatnejadgharahassanlou, Hamid; Zeynali, Rasoul Ilkhanipour; Vaheddoost, Babak; Gharehbaghi, Amin

doi:10.2166/ws.2019.198

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…Keeping in mind that at least one best-fit evaluation criterion (e.g., R 2 ), together with an error determination indicator (e.g., RMSE), is usually required to identify the best model. The fusion of such performance indicators into a single weighted grade [50,51] would be helpful in the determination of the best model.…”

Section: Discussionmentioning

confidence: 99%

Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye

et al. 2023

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The impact of climate change has led to significant changes in hydroclimatic patterns and continuous stress on water resources through frequent wet and dry spells. Hence, understanding and effectively addressing the escalating impact of climate change on hydroclimatic patterns, especially in the context of meteorological drought, necessitates precise modeling of these phenomena. This study focuses on assessing the accuracy of drought modeling using the well-established Standard Precipitation Index (SPI) in the Aegean region of Türkiye. The study utilizes monthly precipitation data from six stations in Cesme, Kusadasi, Manisa, Seferihisar, Selcuk and Izmir at Kucuk Menderes Basin covering the period from 1973 to 2020. The dataset is divided into three sets, training (60%), validation (20%), and testing (20%) sets. The study aims to determine the SPI-3, SPI-6 and SPI-12 using a multi-station prediction technique. Three boosting regression models (BRMs), namely Extreme Gradient Boosting (XgBoost), Adaptive Boosting (AdaBoost), and Gradient Boosting (GradBoost), were employed and optimized with the help of the Weighted Mean of Vectors (INFO) technique. Model performances were then evaluated with the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient of Determination (R2) and the Willmott Index (WI). Results demonstrated a distinct superiority of the XgBoost model over AdaBoost and GradBoost in terms of accuracy. During the test phase, the XgBoost model achieved RMSEs of 0.496, 0.429 and 0.389 for SPI-3, SPI-6 and SPI-12, respectively. The WIs were 0.899, 0.901 and 0.825 for SPI-3, SPI-6 and SPI-12, respectively. These are considerably lower than the corresponding values obtained by the other models. Yet, the comparative statistical analysis further underscores the effectiveness of XgBoost in modeling extended periods of drought in the Aegean region of Türkiye.

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Section: Discussionmentioning

confidence: 99%

Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye

et al. 2023

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“…Fortunately, one of the effective and powerful ways to investigate in this field is numerical method. With dramatic developments that have occurred during recent decades in the field of computer science and mathematics, novel numerical techniques have been developed (Gharehbaghi et al 2017, Saadatnejadgharahassanlou et al 2020. The finite volume method (FVM) is one of the most widely used numerical techniques in engineering and science.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of groundwater flow based on explicit and fully implicit schemes of finite volume method

DALKILIÇ¹,

Gharehbaghi

2021

JER is an international, peer-reviewed journal that publishes f

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This paper documents a novel numerical model for calculating the behavior of unsteady, one-dimensional groundwater flow by using the finite volume method. The developed model determined water table fluctuations for different scenarios as follows: Drainage and recession from an unconfined aquifer, and water table fluctuations above an inclined leaky layer due to ditch recharge with a constant and variable upper boundary condition. The Boussinesq equation, which is the governing equation in this domain, is linearized and solved numerically in both of the explicit and fully implicit conditions. Meanwhile, the upwind scheme is employed to discretize the governing equation. The computed outcomes of both the explicit and implicit approaches agreed well with the results of analytical solution and laboratory experiments. The main reason is that in the first half of simulation process explicit scheme obtains slightly better results and in the second half of the simulation process fully implicit scheme predicts more reliable outcomes that are hidden in the neighbor node points. As a final point, the numerical outcomes confirm that the developed model is capable of calculating satisfactory outcomes in engineering and science applications.

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Using a hybrid artificial intelligence approach to estimate length of the hydraulic jump caused by novel kind of Sharp-Crested V-notch weirs

Ghasemlounia

2021

European Journal of Environmental and Civil Engineering

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Parametric and nonparametric regression models in study of the length of hydraulic jump after a multi-segment sharp-crested V-notch weir

Cited by 6 publications

References 23 publications

Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye

Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye

Numerical modeling of groundwater flow based on explicit and fully implicit schemes of finite volume method

Using a hybrid artificial intelligence approach to estimate length of the hydraulic jump caused by novel kind of Sharp-Crested V-notch weirs

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