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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
Mon Apr 04 2016
Journal Name
Iraqi Journal Of Physics
Thickness and gamma-ray effect on physical properties of CdO thin films grown by pulsed laser deposition
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Polycrystalline Cadmium Oxide (CdO) thin films were prepared using pulsed laser deposition onto glass substrates at room temperature with different thicknesses of (300, 350 and 400)nm, these films were irradiated with cesium-137(Cs-137) radiation. The thickness and irradiation effects on structural and optical properties were studied. It is observed by XRD results that films are polycrystalline before and after irradiation, with cubic structure and show preferential growth along (111) and (200) directions. The crystallite sizes increases with increasing of thickness, and decreases with gamma radiation, which are found to be within the range (23.84-4.52) nm and (41.44-4.974)nm before and after irradiation for thickness 350nm and 4

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Thickness and gamma-ray effect on physical properties of CdO thin films grown by pulsed laser deposition
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Polycrystalline Cadmium Oxide (CdO) thin films were prepared
using pulsed laser deposition onto glass substrates at room
temperature with different thicknesses of (300, 350 and 400)nm,
these films were irradiated with cesium-137(Cs-137) radiation. The
thickness and irradiation effects on structural and optical properties
were studied. It is observed by XRD results that films are
polycrystalline before and after irradiation, with cubic structure and
show preferential growth along (111) and (200) directions. The
crystallite sizes increases with increasing of thickness, and decreases
with gamma radiation, which are found to be within the range
(23.84-4.52) nm and (41.44-4.974)nm before and after irradiation for

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Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Dynamic Response of Slender Reinforced Concrete Columns Strengthened by Using CFRP and Circularization Subjected to Seismic Excitation
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Publication Date
Wed Oct 07 2026
Journal Name
Journal Of Physical Education
The Effect of Constructive Learning Model on Cognitive Achievement and Learning dribbling Skill in Soccer for Secondary School Students
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The research aimed at identifying the effect of using constructive learning model on academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. The researcher used the experimental method on (30) secondary school students; 10 selected for pilot study, 20 were divided into two groups. The experimental group followed constructive learning model while the controlling group followed the traditional method. The experimental program lasted for eight weeks with two teaching sessions per week for each group. The data was collected and treated using SPSS to conclude the positive effect of using constructive learning model on developing academic achievement and learning soccer dribbling Skill in 2nd grade seconda

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Publication Date
Wed Oct 07 2026
Journal Name
University Of Anbar Sport And Physical Education Sciences
The Effect of special exercises to develop the speed of lateral movement and accurate low blows straight front and rear squash players
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Publication Date
Wed Oct 07 2026
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 4, 2022, Págs. 165-167
Social-kinetic Cohesion and its Relationship to Goal Direction with its two Dimensions (Performance and Result) for Advanced Handball Players in Iraq
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Autorías: Muhammad Hamza Shihab, Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2022. Artículo de Revista en Dialnet.

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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Wed Jan 15 2003
Journal Name
كلية الترا ث الجامعة
Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

Publication Date
Wed Oct 07 2026
Journal Name
Journal Of The College Of Basic Education
Addiction to the Internet and its relation to the mental alertness of students of the Faculty of Physical Education and Sports Science for Girls
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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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