The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury predictions, predicting injuries and analysing related risks, and evaluating player performance using AI models are the three main topics highlighted in the study. This study highlights the use of AI algorithms in the sports field to predict injuries and predict team or player performance, especially in football.
We present the concept of maps Γ- periodi2 on Γ -near-ring S. Our main goal is to research and explore the presence and mapping traits such as h Γ –hom anti-Γ –hom, Γ –α-derivations of Γ -periodi2 on Γ- near-rings.
One of the principle concepts to understand any hydrocarbon field is the heterogeneity scale; This becomes particularly challenging in supergiant oil fields with medium to low lateral connectivity and carbonate reservoir rocks.
The main objectives of this study is to quantify the value of the heterogeneity for any well in question, and propagate it to the full reservoir. This is a quite useful specifically prior to conducting detailed water flooding or full field development studies and work, in order to be prepared for a proper design and exploitation requirements that fit with the level of heterogeneity of this formation.
As a reservoir is depleted due to production, pore pressure decreases leading to increased effective stress which causes a reduction in permeability, porosity, and possible pore collapse or compaction. Permeability is a key factor in tight reservoir development; therefore, understanding the loss of permeability in these reservoirs due to depletion is vital for effective reservoir management. The paper presents a case history on a tight carbonate reservoir in Iraq which demonstrates the behavior of rock permeability and porosity as a function of increasing effective stress simulating a depleting mode over given production time. The experimental results show unique models for the decline of permeability and porosity as function effective str
... Show MoreKE Sharquie, AA Noaimi, EA Al-Janabi…, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 13
This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.