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Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter (hw/dH), ratio of pressure of process to atmosphere pressure (P/Pa), Weber number (lTe).
Statistical analysis showed that the proposed models have an average absolute relative error (AARE) of 9.3% and
standard deviation (SD) of 9.7%for first model, AARE of 9.35% and SD of 10.5%for second model and AARE of 9.8%
and SD of 7.5% for the third model.

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of the Effect of Using Stone Column in Clayey Soil on the Behavior of Circular Footing by ANN Model
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Shallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories &amp; Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using the Artificial Gas Lift to Increase the Productivity of Noor Oil Field / Mishrif Formation
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Noor Oil Field is one of Iraqi oil fields located in Missan province / Amarah city. This field is not subjected to licensing rounds, but depends on the national effort of  Missan Oil Company. The first two wells in the field were drilled in seventies and were  not opened to production until 2009. The aim of this study is to study the possibility of using the method of gas lift to increase the productivity of this field . PROSPER software was used to design the continuous  gas lift by using maximum production rate in the design.

   The design was made after comparing  the measured pressure with the calculated pressure, this comparison  show  that the method of Beggs-Brill and Petroleum Exper

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Publication Date
Thu Nov 16 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Importance of Using Metaverse Technology in Education from the Point of View of University Teachers
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The study aims to demonstrate the significance of metaverse technology across various disciplines, academic degrees, scientific fields, and academic titles. It also aims to assess the level of knowledge and understanding of university teachers (research sample) regarding metaverse technology. Hence, the descriptive research methodology was based on the method of statistical survey in the sample. It involved a set of organized scientific steps to deduce data from the reality of the statistical sample and its nature in order to achieve the objectives of the study. In this study, a questionnaire was used as a tool to collect data from a random sample of approximately 121 teachers and instructors from the University of Baghdad. This app

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Publication Date
Mon Oct 29 2018
Journal Name
International Journal Of Women's Health And Reproduction Sciences
Prediction of Placenta Accreta Using Hyperglycosylated Human Chorionic Gonadotropin
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Objectives: Hyperglycosylated human chorionic gonadotropin (hCG) is a variant of hCG. In addition, it has a different oligosaccharide structure compared to the regular hCG and promotes the invasion and differentiation of peripheral cytotrophoblast. This study aimed to measure hyperglycosylated hCG as a predictor in the diagnosis of placenta accreta. Materials and Methods: In general, 90 pregnant women were involved in this case-control study among which, 30 ladies (control group) were pregnant within the gestational age of ≥36 weeks with at least one previous caesarean section and a normal sited placenta in transabdominal ultrasound (TAU). The other 60 pregnant women (case

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Publication Date
Tue Sep 03 2019
Journal Name
Eastern-european Journal Of Enterprise Technologies
Prediction of spot welding parameters using fuzzy logic controlling
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Publication Date
Fri Apr 01 2022
Journal Name
Civil Engineering Journal
Prediction of Urban Spatial Changes Pattern Using Markov Chain
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Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to ana

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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