Parameter Optimization and State Evaluation of Basketball Teaching Based on BPNN-Reference-Cited by-同舟云学术

Parameter Optimization and State Evaluation of Basketball Teaching Based on BPNN

Published:2022-07-31 Issue: Volume:2022 Page:1-10
ISSN:1875-905X
Container-title:Mobile Information Systems
language:en
Short-container-title:Mobile Information Systems

Author:

Wang Zhanqi¹²^ORCID

Affiliation:

1. College of Physical Education, Luoyang Institute of Science and Technology, Luoyang 471023, Henan, China

2. Henan Province Engineering Research Center of Industrial Intelligent Vision, Luoyang 471023, Henan, China

Abstract

BPNN is a multi-layer network with forward and backward error algorithms. It is currently the most widely used NN. Especially when it is applied to the basketball teaching scene, it can improve the research on the parameter optimization and state evaluation of the BP neural network in the teaching scene. This paper is mainly to study how to optimize the parameters of basketball teaching scene to improve the teaching effect and to evaluate the state. This paper improves the BPNN technology to study the basketball teaching scene and then proposes a genetic algorithm on the basis of the BPNN. It optimizes the parameters of basketball teaching scene through genetic algorithm and then analyzes the experimental data. The experimental results of this paper show that the BPNN is not as good as the BPNN based on the genetic algorithm in optimizing the parameters of the basketball teaching scene. The BPNN based on genetic algorithm has a successful recognition rate of more than 93% for basketball dribbling and shooting, which is 7-8% higher than that of the BPNN.

Funder

Science and Technology Department, Henan Province

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

Link

http://downloads.hindawi.com/journals/misy/2022/4327356.pdf

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