<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Athlete training optimization is an important part of sports management, and the scientific management program is of practical significance for athletes to improve their sports level. This paper collects sports training data for cluster analysis, establishes the optimization function of the distance from the data point to the center of the class, solves it, and determines the consistency matrix to judge the data category. Establish the column generation optimization model, get the linear programming model based on the matrix change column generation, in the process of transforming the model to solve the recursive matrix recursive relationship formula and solve the objective function. According to the solution of the optimization function to adjust the athletes’ sports training program. After the test, it was found that the pre-and post-test scores of the three tests of the experimental class were improved by 1.03 seconds, 1.05 meters, and 1.33 meters, respectively, and were significantly ahead of the scores of the control group. According to the satisfaction analysis, 76.67% of students were satisfied with the training effect. It indicates that the new training mode improved by the algorithm has good application effects.</p>
</abstract>

Athlete training optimization is an important part of sports management, and the scientific management program is of practical significance for athletes to improve their sports level. This paper collects sports training data for cluster analysis, establishes the optimization function of the distance from the data point to the center of the class, solves it, and determines the consistency matrix to judge the data category. Establish the column generation optimization model, get the linear programming model based on the matrix change column generation, in the process of transforming the model to solve the recursive matrix recursive relationship formula and solve the objective function. According to the solution of the optimization function to adjust the athletes’ sports training program. After the test, it was found that the pre-and post-test scores of the three tests of the experimental class were improved by 1.03 seconds, 1.05 meters, and 1.33 meters, respectively, and were significantly ahead of the scores of the control group. According to the satisfaction analysis, 76.67% of students were satisfied with the training effect. It indicates that the new training mode improved by the algorithm has good application effects.

Research on Sports Training Mode of College Athletes Based on Column Generation Algorithm of Recursive Matrix

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Athlete training optimization is an important part of sports management, and the scientific management program is of practical significance for athletes to...

Research on Sports Training Mode of College Athletes Based on Column Generation Algorithm of Recursive Matrix

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 22 mar 2024

Przyjęty: 16 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2178

Słowa kluczowe
Column generation algorithm, Recursive matrix, Cluster analysis, Sports training mode

© 2024 Xiangmin Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Sports Training Mode of College Athletes Based on Column Generation Algorithm of Recursive Matrix

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 22 mar 2024

Przyjęty: 16 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2178

Słowa kluczoweColumn generation algorithm, Recursive matrix, Cluster analysis, Sports training mode

© 2024 Xiangmin Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Column generation algorithm, Recursive matrix, Cluster analysis, Sports training mode