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Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering
In order to solve the problem, the psychological identification of athletes in professional competition pressure is difficult. This paper first analyzes the sources of athletes' psychological pressure based on the hierarchical clustering method, and then divides the weights of the sources of ps...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410923/ https://www.ncbi.nlm.nih.gov/pubmed/36035831 http://dx.doi.org/10.1155/2022/6555797 |
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author | Huang, Jun |
author_facet | Huang, Jun |
author_sort | Huang, Jun |
collection | PubMed |
description | In order to solve the problem, the psychological identification of athletes in professional competition pressure is difficult. This paper first analyzes the sources of athletes' psychological pressure based on the hierarchical clustering method, and then divides the weights of the sources of psychological pressure, quantificationally scores them and constructs an identification model of athletes' psychological pressure. Then, the clustering process is optimized based on the K-Means algorithm, and its effectiveness is verified. Finally, the psychological stress of 10 players in a football club was analyzed. The results show that the model effectively and reasonably reflects the influence of pressure sources on the athletes' competitive state during the competition, which provides a basis for the decision-making of relief about athletes' stress. |
format | Online Article Text |
id | pubmed-9410923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94109232022-08-26 Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering Huang, Jun Comput Intell Neurosci Research Article In order to solve the problem, the psychological identification of athletes in professional competition pressure is difficult. This paper first analyzes the sources of athletes' psychological pressure based on the hierarchical clustering method, and then divides the weights of the sources of psychological pressure, quantificationally scores them and constructs an identification model of athletes' psychological pressure. Then, the clustering process is optimized based on the K-Means algorithm, and its effectiveness is verified. Finally, the psychological stress of 10 players in a football club was analyzed. The results show that the model effectively and reasonably reflects the influence of pressure sources on the athletes' competitive state during the competition, which provides a basis for the decision-making of relief about athletes' stress. Hindawi 2022-08-18 /pmc/articles/PMC9410923/ /pubmed/36035831 http://dx.doi.org/10.1155/2022/6555797 Text en Copyright © 2022 Jun Huang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Huang, Jun Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title | Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title_full | Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title_fullStr | Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title_full_unstemmed | Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title_short | Identification of Sports Athletes Psychological Stress Based on K-Means Optimized Hierarchical Clustering |
title_sort | identification of sports athletes psychological stress based on k-means optimized hierarchical clustering |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410923/ https://www.ncbi.nlm.nih.gov/pubmed/36035831 http://dx.doi.org/10.1155/2022/6555797 |
work_keys_str_mv | AT huangjun identificationofsportsathletespsychologicalstressbasedonkmeansoptimizedhierarchicalclustering |