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Using artificial neural networks to assign soccer players by physical and motor abilities
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Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to identify the relationships between physical variables and playing positions. Results: The Pearson correlation analysis reveals statistically significant relationships between physical and motor abilities and the players’ actual playing positions (p < 0.05). In addition, the artificial neural network (MLP) model demonstrated the ability to assign players to different playing positions based on the relative weights of the variables. Speed, endurance, and explosive power were identified as the most influential factors in determining offensive positions, whereas flexibility and visual–motor coordination played a significant role in determining defensive positions and goalkeeping. The model achieved a classification accuracy exceeding 85%. Discussion: The artificial neural network model demonstrates a high capacity to exploit correlational relationships and transform them from conventional statistical associations into accurate predictive patterns. This enables the model to guide players toward the most suitable playing positions based on their physical and motor characteristics. Conclusions: The findings of the study confirm the feasibility of adopting artificial neural networks as an intelligent tool for sports performance analysis and for guiding youth players toward the playing positions most suited to their physical and motor abilities.

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Sun Nov 01 2020
Journal Name
The Iraqi Journal For Information And Documentation Studies
Improving students' cognitive abilities using modern technologies: an experimental study
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The importance of knowledge is represented in the use of various sources of information, the corresponding to the same level of importance is the use of modern means and technologies in the delivery and investment of these sources to the beneficiaries, among these means and technologies are the multimedia that deal with most of the human senses, but the most important of which is sight and hearing, if these are invested the means in the field of education will give many positive results, such as the speed of receiving information, its clarity, and its freedom from impurities and influences, as well as its stability in memory as it is based on nderstanding, not memorization. On this basis, the experience of supporting the education process

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Tue Jan 10 2012
Journal Name
Iraqi Journal Of Community Medicine
Evaluation of physical parameters in mitral valve stenosis by using Doppler Ultrasound
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Background: Mitral valve stenosis is a condition in which the hearts mitral valve is narrowed (stenosis), This narrowing blocks the valve from opening properly obstructing blood flow through the heart and the rest of the body and this causes changes in physical parameters (resistance and conductance). Aim of the study: To assess the changes in the physical parameters in mitral valve stenosis disease in different gender and age by using Doppler ultrasound. Methods : The examination of patients at the Division of Echo - at the Iraqi Center for Heart Disease in Medical City for surgery specialist - Baghdad - Iraq, during(February2009 till November2010). The current study included fifty eight cases containing (27 males and 31 females) ages rang

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Publication Date
Sat Jul 19 2025
Journal Name
Annals Of Applied Sport Science
A Comparative Study of the Average Motor Response Time for the Arms and Legs of Handball, Basketball, and Volleyball Players Aged 14-16 Years
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Background. The motor response is a fundamental ability that is evident during any physical or motor activity. However, the need for this ability varies from one sport to another and depends on the specific skills required in each sport. Objectives. This study aims to compare the average motor reaction times of the arm and leg among handball, basketball, and volleyball players aged 14 to 16 years. Methods. The sample included 30 players aged 14-16 years from the sports talent care center, evenly distributed on handball, basketball, and volleyball. Standardized tests were used to measure the speed of motor response, including the Batak Micro test for hands, which records the number of responses to light stimuli in 30 seconds, and the Saqer t

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Publication Date
Sun Jul 12 2026
Journal Name
Journal Of School Health
Enhancing Motor Competence in Rhythmic Gymnastics: Effects of the Overlapping Waves Strategy in School‐Based Physical Education
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ABSTRACT<sec> <title>Background

Rhythmic gymnastics offers a context for motor development. This study examined the association between the Overlapping Waves Strategy and traditional instruction in fundamental club skills.

Methods

A cluster‐allocated quasi‐experimental design (16 sessions) was implemented among 64 fifth‐grade female students. Participants received Overlapping Waves Strategy ( n

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