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Complementary data-intelligence model for river flow simulation

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Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Numerical Simulation of Magnetohydrodynamic Influences on Casson Model for Blood Flow through an Overlapping Stenosed Artery

Magnetohydrodynamic (MHD) effects of unsteady blood flow on Casson fluid through an artery with overlapping stenosis were investigated. The nonlinear governing equations accompanied by the appropriate boundary conditions were discretized and solved based on a finite difference technique, using the pressure correction method with MAC algorithm. Moreover, blood flow characteristics, such as the velocity profile, pressure drop, wall shear stress, and patterns of streamlines, are presented graphically and inspected thoroughly for understanding the blood flow phenomena in the stenosed artery.

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Large Eddy Simulation in Duct Flow

In this paper, the problem of developing turbulent flow in rectangular duct is investigated by obtaining numerical results of the velocity profiles in duct by using large eddy simulation model in two dimensions with different Reynolds numbers, filter equations and mesh sizes. Reynolds numbers range from (11,000) to (110,000) for velocities (1 m/sec) to (50 m/sec) with (56×56), (76×76) and (96×96) mesh sizes with different filter equations. The numerical results of the large eddy simulation model are compared with k-ε model and analytic velocity distribution and validated with experimental data of other researcher. The large eddy simulation model has a good agreement with experimental data for high Reynolds number with the first, seco

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Publication Date
Sun Mar 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
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Publication Date
Sat Feb 27 2021
Journal Name
Journal Of Engineering
Physical Simulation for the Flow in Straight and Rectangular Loop Manifolds

The flow in a manifolds considered as an advanced problem in hydraulic engineering applications. The objectives of this study are to determine; the uniformity qn/q1 (ratio of the discharge at last outlet, qn to the discharge at first outlet, q1) and total head losses of the flow along straight and rectangular loop manifolds with different flow conditions. The straight pipes were with 18 m and 19 m long and with of 25.4 mm (1.0 in) in diameter each. While, the rectangular close loop configuration was with length of 19 m and with diameter of 25.4 mm (1.0 in) also. Constant head in the supply tank was used and the head is 2.10 m. It is found that outlets spacing and manifold configuration are the main factors aff

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Hydromorphodynamics Simulation for Selected Stretch of Euphrates River within Al-Anbar Governorate

In this study, the hydromorphodynamic simulation of a stretch of the Euphrates River was conducted. The stretch of the Euphrates River extended from Haditha dam to the city of Heet in Al-Anbar Governorate and it is estimated to be 124.4 km. Samples were taken from 3 sites along the banks of the river stretch using sampling equipment. The samples were taken to the laboratory for grain size analysis where the median size (D50) and sediment load were determined. The hydromorphodynamic simulation was conducted using the NACY 2DH solver of the iRIC model.  The model was calibration using the Manning roughness,    sediment load, and median particle size and the validation process showed that the error between th

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