An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques

Mohammed Asim Ghazi

doi:doi:10.11648/j.ajai.20220602.11

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An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques

Mohammed Asim Ghazi

Published in American Journal of Artificial Intelligence (Volume 6, Issue 2)

Received: 3 September 2022 Accepted: 20 September 2022 Published: 29 November 2022

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Abstract

Artificial intelligence has changed the way we consume and analyze sports. The role of artificial intelligence in improving decision-making and prediction in sports is expanding, due to the specific changes in the performance of athletes, a performance prediction model based on a machine learning algorithm has been proposed. The current research state of athlete performance modelling and prediction is analyze and the current athlete performance prediction model is found. The shortcomings of the model are analyze. The reason for the low prediction accuracy of the model was analyze. Then chaos theory is used to process the historical data of the athletes, within the range of data used in this study is the average data from the total reaction time ((RT, movement time (MT), response time) through the skill performance of the skill of URA MAWASHI GERI and about By using the electronic device to measure the reaction speed and approved by the Ministry of Higher Education and the Patent Office No. (217050754), and it was collected and used through a sample of (210) karate players who are registered on the database of the Egyptian Karate Federation, classified (age, height, Weight, training age). ata collected for time series analysis were categorized by year and time (RT, MT, reaction time), and organized using Microsoft Excel Office 365 and IBM And SPSS 20.0 was used, and the results came to determine the correct training status of the player's condition and how to legalize the player's training loads and work the training programs for the player throughout the training season and over the training periods during the training season or a For the training course, how to plan and implement the training content and evaluate the training periods, the conclusions came by standing on the skill level and forming predictions by making scientific predictions based on time-stamped historical data. It includes building predictive models through time series and artificial intelligence techniques.

Published in	American Journal of Artificial Intelligence (Volume 6, Issue 2)
DOI	10.11648/j.ajai.20220602.11
Page(s)	31-35
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Reaction Time (RT), Motion Time (MT), Time Series, Artificial Intelligence

References

[1]	Hanan Ali Hassanein. (2021). Using the systems method between kinetic energy, body mass and response speed in evaluating the skill performance of some karate skills. Journal of the sports system.
[2]	Samiha Ali Salem Al-Saqri. (2020). Artificial intelligence techniques as an input to assess skill performance in systems analysis and some karate skills. Journal of Sports Arts, Faculty of Physical Education, Assiut University, 580-604.
[3]	Sareeh Abdel Karim. (2013). Biomechanics applications in sports training and motor performance. I 1, Dijla Publishing House, Iraq.
[4]	Muhammad Asim Ghazi. (2022). Time series and prediction of sports performance, first edition, p. (55). Jordan: Dar Al-Ibtikar for Publishing and Distribution.
[5]	Muhammad Asim Ghazi. (2019). Engineering planning training loads and training periods in physical education sciences. Jordan: Dar Al-Jian for publishing and distribution.
[6]	Talha Hossam El Din. (2003). Biomechanics, Theoretical and Applied Foundations, 1st Edition, Cairo. 1st floor, Cairo.
[7]	Nahid Ali Muhammad. (2008). Kinetic rhythm between theory and practice. Zagazig: Journal of the Faculty of Physical Education for Girls.
[8]	Krause, L. (2019). Exploring the influence of practice design on the development of tennis players. Victoria University, Footscray, VIC, Australia., (Doctoral dissertation).
[9]	McCabe, A. a. (2008). Artificial intelligence in sports prediction. in Fifth International Conference on Information Technology: New Generations. (IEEE: Las Vegas, NV, 1194–1197. doi: 10.1109/ITNG.2008.203.
[10]	Santos, A. C.-O. (2020). An AI Application to learn Martial. Computer Science School, UNED. Madrid, Spain, 1-3.
[11]	Suwarganda, E. K. (2015). ANALYSIS OF PERFORMANCE OF THE KARATE PUNCH. Malaysia: Center for Biomechanics, National Sport Institute.

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APA Style

Mohammed Asim Ghazi. (2022). An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. American Journal of Artificial Intelligence, 6(2), 31-35. https://doi.org/10.11648/j.ajai.20220602.11

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ACS Style

Mohammed Asim Ghazi. An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. Am. J. Artif. Intell. 2022, 6(2), 31-35. doi: 10.11648/j.ajai.20220602.11

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AMA Style

Mohammed Asim Ghazi. An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. Am J Artif Intell. 2022;6(2):31-35. doi: 10.11648/j.ajai.20220602.11

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@article{10.11648/j.ajai.20220602.11,
  author = {Mohammed Asim Ghazi},
  title = {An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques},
  journal = {American Journal of Artificial Intelligence},
  volume = {6},
  number = {2},
  pages = {31-35},
  doi = {10.11648/j.ajai.20220602.11},
  url = {https://doi.org/10.11648/j.ajai.20220602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajai.20220602.11},
  abstract = {Artificial intelligence has changed the way we consume and analyze sports. The role of artificial intelligence in improving decision-making and prediction in sports is expanding, due to the specific changes in the performance of athletes, a performance prediction model based on a machine learning algorithm has been proposed. The current research state of athlete performance modelling and prediction is analyze and the current athlete performance prediction model is found. The shortcomings of the model are analyze. The reason for the low prediction accuracy of the model was analyze. Then chaos theory is used to process the historical data of the athletes, within the range of data used in this study is the average data from the total reaction time ((RT, movement time (MT), response time) through the skill performance of the skill of URA MAWASHI GERI and about By using the electronic device to measure the reaction speed and approved by the Ministry of Higher Education and the Patent Office No. (217050754), and it was collected and used through a sample of (210) karate players who are registered on the database of the Egyptian Karate Federation, classified (age, height, Weight, training age). ata collected for time series analysis were categorized by year and time (RT, MT, reaction time), and organized using Microsoft Excel Office 365 and IBM And SPSS 20.0 was used, and the results came to determine the correct training status of the player's condition and how to legalize the player's training loads and work the training programs for the player throughout the training season and over the training periods during the training season or a For the training course, how to plan and implement the training content and evaluate the training periods, the conclusions came by standing on the skill level and forming predictions by making scientific predictions based on time-stamped historical data. It includes building predictive models through time series and artificial intelligence techniques.},
 year = {2022}
}

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TY  - JOUR
T1  - An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques
AU  - Mohammed Asim Ghazi
Y1  - 2022/11/29
PY  - 2022
N1  - https://doi.org/10.11648/j.ajai.20220602.11
DO  - 10.11648/j.ajai.20220602.11
T2  - American Journal of Artificial Intelligence
JF  - American Journal of Artificial Intelligence
JO  - American Journal of Artificial Intelligence
SP  - 31
EP  - 35
PB  - Science Publishing Group
SN  - 2639-9733
UR  - https://doi.org/10.11648/j.ajai.20220602.11
AB  - Artificial intelligence has changed the way we consume and analyze sports. The role of artificial intelligence in improving decision-making and prediction in sports is expanding, due to the specific changes in the performance of athletes, a performance prediction model based on a machine learning algorithm has been proposed. The current research state of athlete performance modelling and prediction is analyze and the current athlete performance prediction model is found. The shortcomings of the model are analyze. The reason for the low prediction accuracy of the model was analyze. Then chaos theory is used to process the historical data of the athletes, within the range of data used in this study is the average data from the total reaction time ((RT, movement time (MT), response time) through the skill performance of the skill of URA MAWASHI GERI and about By using the electronic device to measure the reaction speed and approved by the Ministry of Higher Education and the Patent Office No. (217050754), and it was collected and used through a sample of (210) karate players who are registered on the database of the Egyptian Karate Federation, classified (age, height, Weight, training age). ata collected for time series analysis were categorized by year and time (RT, MT, reaction time), and organized using Microsoft Excel Office 365 and IBM And SPSS 20.0 was used, and the results came to determine the correct training status of the player's condition and how to legalize the player's training loads and work the training programs for the player throughout the training season and over the training periods during the training season or a For the training course, how to plan and implement the training content and evaluate the training periods, the conclusions came by standing on the skill level and forming predictions by making scientific predictions based on time-stamped historical data. It includes building predictive models through time series and artificial intelligence techniques.
VL  - 6
IS  - 2
ER  -

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Author Information

Mohammed Asim Ghazi

Faculty Physical Education, Alexandria University, Alexandria, Egypt

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APA Style

Mohammed Asim Ghazi. (2022). An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. American Journal of Artificial Intelligence, 6(2), 31-35. https://doi.org/10.11648/j.ajai.20220602.11

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ACS Style

Mohammed Asim Ghazi. An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. Am. J. Artif. Intell. 2022, 6(2), 31-35. doi: 10.11648/j.ajai.20220602.11

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AMA Style

Mohammed Asim Ghazi. An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques. Am J Artif Intell. 2022;6(2):31-35. doi: 10.11648/j.ajai.20220602.11

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@article{10.11648/j.ajai.20220602.11,
  author = {Mohammed Asim Ghazi},
  title = {An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques},
  journal = {American Journal of Artificial Intelligence},
  volume = {6},
  number = {2},
  pages = {31-35},
  doi = {10.11648/j.ajai.20220602.11},
  url = {https://doi.org/10.11648/j.ajai.20220602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajai.20220602.11},
  abstract = {Artificial intelligence has changed the way we consume and analyze sports. The role of artificial intelligence in improving decision-making and prediction in sports is expanding, due to the specific changes in the performance of athletes, a performance prediction model based on a machine learning algorithm has been proposed. The current research state of athlete performance modelling and prediction is analyze and the current athlete performance prediction model is found. The shortcomings of the model are analyze. The reason for the low prediction accuracy of the model was analyze. Then chaos theory is used to process the historical data of the athletes, within the range of data used in this study is the average data from the total reaction time ((RT, movement time (MT), response time) through the skill performance of the skill of URA MAWASHI GERI and about By using the electronic device to measure the reaction speed and approved by the Ministry of Higher Education and the Patent Office No. (217050754), and it was collected and used through a sample of (210) karate players who are registered on the database of the Egyptian Karate Federation, classified (age, height, Weight, training age). ata collected for time series analysis were categorized by year and time (RT, MT, reaction time), and organized using Microsoft Excel Office 365 and IBM And SPSS 20.0 was used, and the results came to determine the correct training status of the player's condition and how to legalize the player's training loads and work the training programs for the player throughout the training season and over the training periods during the training season or a For the training course, how to plan and implement the training content and evaluate the training periods, the conclusions came by standing on the skill level and forming predictions by making scientific predictions based on time-stamped historical data. It includes building predictive models through time series and artificial intelligence techniques.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - An Analytical Method for Evaluating the Performance of the URA MAWASHI GERI Skill Using Time Series and Artificial Intelligence Techniques
AU  - Mohammed Asim Ghazi
Y1  - 2022/11/29
PY  - 2022
N1  - https://doi.org/10.11648/j.ajai.20220602.11
DO  - 10.11648/j.ajai.20220602.11
T2  - American Journal of Artificial Intelligence
JF  - American Journal of Artificial Intelligence
JO  - American Journal of Artificial Intelligence
SP  - 31
EP  - 35
PB  - Science Publishing Group
SN  - 2639-9733
UR  - https://doi.org/10.11648/j.ajai.20220602.11
AB  - Artificial intelligence has changed the way we consume and analyze sports. The role of artificial intelligence in improving decision-making and prediction in sports is expanding, due to the specific changes in the performance of athletes, a performance prediction model based on a machine learning algorithm has been proposed. The current research state of athlete performance modelling and prediction is analyze and the current athlete performance prediction model is found. The shortcomings of the model are analyze. The reason for the low prediction accuracy of the model was analyze. Then chaos theory is used to process the historical data of the athletes, within the range of data used in this study is the average data from the total reaction time ((RT, movement time (MT), response time) through the skill performance of the skill of URA MAWASHI GERI and about By using the electronic device to measure the reaction speed and approved by the Ministry of Higher Education and the Patent Office No. (217050754), and it was collected and used through a sample of (210) karate players who are registered on the database of the Egyptian Karate Federation, classified (age, height, Weight, training age). ata collected for time series analysis were categorized by year and time (RT, MT, reaction time), and organized using Microsoft Excel Office 365 and IBM And SPSS 20.0 was used, and the results came to determine the correct training status of the player's condition and how to legalize the player's training loads and work the training programs for the player throughout the training season and over the training periods during the training season or a For the training course, how to plan and implement the training content and evaluate the training periods, the conclusions came by standing on the skill level and forming predictions by making scientific predictions based on time-stamped historical data. It includes building predictive models through time series and artificial intelligence techniques.
VL  - 6
IS  - 2
ER  -

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