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Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in the last 5 meters from the total approach distance of 30 meters, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The height of the fist is over the full length of the pole's stick) and these are considered independent variables, while the dependent variable was the prediction of achievement (Final height achieved by the jumper) as an output. The neural network architecture was represented by three layers, the first layer is the input layer with the five variables, and one layer is hidden and contains one node, while the last layer is the output layer that represents the outcome of the sport achievement prediction of male weight jumping. The momentum term and learning rate were chosen by 0.95 and 0.4 respectively, and the transfer function in the hidden layer was the sigmoid function and in the last layer was the sigmoid function, the historical data used in this model represent the Olympic achievements of a number of world champions, the results of this study were that the artificial neural network has the ability to prediction of sport achievement for determine the height of the jump of the pole player with a degree of accuracy of 90.10%, correlation coefficient and 95.60%.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Mon Jun 20 2022
Journal Name
International Journal Of Early Childhood Special Education
The Impact of the Visual Teaching Strategy by using Infographic in mathematics achievement for intrmediate grade students
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The research aims to identify the impact of the visual teaching strategy by using infographics mathematics achievement for intermediate grade students. The experimental research method was adopted, as the experimental design of two independent and equal groups with a post test was used, whereas the experiment was applied on a sample consisting of (52) male students from first- intermediate grade students in (Al-Haq Al-Mubin intermediate school for Boys) of the General Directorate in Anbar Governorate - Department Education in Fallujah for the academic year (2021-2022), and the research sample was distributed equally on the two research groups, and Division (B) was chosen randomly to be the experimental group, while Division (A) was the cont

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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed
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Publication Date
Sat Feb 28 2015
Journal Name
Al-khwarizmi Engineering Journal
Stabilizing Gap of Pole Electric Arc Furnace Using Smart Hydraulic System
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Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

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Publication Date
Mon Feb 02 2015
Journal Name
Al-khwarizmi Engineering Journal
Stabilizing Gap of Pole Electric Arc Furnace Using Smart Hydraulic System
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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Predicting Municipal Sewage Effluent Quality Index Using Mathematical Models In The Al-Rustamiya Sewage Treatment Plant
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Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and t

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Publication Date
Wed Apr 28 2021
Journal Name
Misan Journal For Physical Education Sciences
The Effectiveness of Using Generative Learning Model in Learning Kinetic Series on Rings and Horizontal Bar In Artistic Gymnastics for men
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The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

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