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.
The Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t
... Show Moreتم التطرق في هذا البحث الى دور الذكاء الاصطناعي والتكنولوجيا الحديثة في العملية التدريبية بما يخدم أهدافه والاستفادة منه من خلال المخرجات الجيدة، حيث ان توظيف التكنولوجيا في تدريب رياضة المبارزة يسهل العملية التدريبية على المدرب واللاعب ويساهم في تقليل الجهد المبذول والوقت المستغرق ، وهدفت الدراسة الى التعرف على تأثير الجهاز المصنع في ضبط المسافة بين القدمين لدى عينة البحث ،استخدم المنهج التجريبي بت
... Show MoreIt research and descriptive sample of players Handball number (21) player (Club Husseiniya) The research aims to identify the relationship between certain components of blood and immunological speed the transition has been a test speed the transition in addition to the withdrawal of a blood sample after (5-10) minutes on the test to identify the nature of the correlation between speed and some transitional immune blood Mkonaght. The importance of research in identifying the relationship element speed in the game where one of the key elements in this game and some blood components immune where there is little of the studies, which focused on the nature of the relationship between exercise and immune blood, especially in a game of handball, e
... Show MoreThe purpose of this paper is to evaluate neuromuscular fatigue among elite basketball players in the Iraqi Basketball League using surface electromyography (sEMG) with the Ultium EMG device and the MR3.18 program, and using the Wavelet analysis application with the Continuous Wavelet Transform (CWT) method. The research sample included six advanced players from the Iraqi Elite League, aged (21.50 ±3.67) years, with a body mass of (80.50 ±11.71) kg, and a height of (189.00 ±7.75) cm. The research sample underwent a physical skill-exertion protocol that simulated the actual playing requirements of basketball, during which the electrical activity of the six selected muscles involved in performing the ski
... Show MoreIn order to get advanced results, we must stand at the pointsthat have been observed by the trainers that are of significance inthe sport of fencing and concern for capacity optical (traceoptical and precision visual animation), so we must learn some ofthese types of capacity, whichever is more influential in the gamefencing so that they add a new axis to the player to pick andchoose in order to achieve the desired goal and raise the level ofthe game.The study aimed to identify the relationship between the visualtracking and accuracy of visual animated face and the results ofcompetitions Sabre of the other.Used a much more descriptive approach to study relational on asample of players clubs Sabre and the way intentional, whoqualified to the
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreAbstract Lateral Epicondylitis (LE) which has been referred to as the Tennis Elbow as well is a lesion affecting common tendinous origins of wrist extensors due to chronic overuse injury that results in damaging common extensor tendons which join forearm extensor muscles to humerus. The aim of the present evidence-based clinical statement is reviewing scientific evidences for efficacy of a variety of the rehabilitation methods, chronic lateral epicondylitis management. It is focused upon treating chronic lateral epicondylitis and the latest developments in physiotherapy area for managing chronic lateral epicondylitis. Due to the fact that primary physical impairments in the LE are decreased is the strength of the grip, fundamentally due to
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