Evaluation Method of Basketball Special Technology in College Sports Specialty Based on Genetic Algorithm

Author:

Chen Guining1ORCID

Affiliation:

1. School of Physical Education and Health, Yulin Normal University, Yulin 537000, Guangxi, China

Abstract

Assessment is an important link and method in the teaching process, it can be used in teaching activities, obtaining feedback information for improving teaching methods, and guiding students to better master the knowledge and skills they have learned. This research mainly discusses the assessment and evaluation method of basketball special technology for college sports major based on genetic algorithms. In this paper, a genetic algorithm is proposed, aiming at the shortcomings of the genetic algorithm that can easily generate local optimal solutions, the genetic algorithm is improved, and the superiority of the algorithm is verified by comparative experiments. Finally, the algorithm is applied to the basketball professional skills assessment data and evaluation data to verify the practicability of the algorithm and my valuable information in a large amount of data in the assessment process. Based on the existing assessment basis, expert interviews, and questionnaire survey results in the assessment and evaluation methods of sports professional basketball special techniques, the necessity and basic principles of the innovation of the assessment and evaluation methods of special techniques are expounded. Then, by building a new system of assessment methods for basketball specialization in sports training majors, we can better explore the teaching objectives, teaching time, teaching content, teaching methods, organizational forms, teaching assessment and other aspects of basketball for sports majors in colleges and universities. Due to the complex nonlinear relationship between the technical evaluation results of basketball experts and professors and their influencing factors, as well as the unique advantages of genetic algorithms, it is feasible to introduce genetic algorithms into the field of basketball technical evaluation. There was no significant difference in the evaluation scores between the basketball special technology assessment model based on a genetic algorithm and the basketball skill assessment experts P > 0.05 . The scientific and effective technical test indicators for young basketball players can also objectively test the quality and effect of teaching and training for different age groups. It is a favorable tool for talent selection and plays a guiding role in grassroots youth basketball training. The content and methods stipulated by the test indicators directly affect the training content and methods of grassroots youth basketball players. This research helps to improve students’ basketball skills and tactics and comprehensive practice ability.

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

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