Research Article | OPEN ACCESS
A Neural Network Model for the Correlation between Sprinters' Pre-competition Anxiety and Competition Performance
1, 2Jiwei Yao, 3Yongliang Yang, 3Xiang Xie, 2Wenxin Xu and 1Xiushi Ding
1Physical Education Institute, Hunan University of Science and Technology, Xiangtan 411201, China
2Institute of Physical Education and Sport Science, Fujian Normal University, Fuzhou 350007, China
3Physical Education Institute, Guangxi Normal University, Guilin 541004, China
Research Journal of Applied Sciences, Engineering and Technology 2013 1:75-81
Received: October 22, 2012 | Accepted: November 23, 2012 | Published: June 05, 2013
Abstract
Sprint is an important sporting event in track and field competition, in which, athletes’ pre-competition anxiety will greatly affect them in bringing into play their competence, which will then influence their final performance in the competition. For this reason, to study the correlation between sprinters’ pre-competition anxiety and their competition performance is of great significance in predicting athletes’ performance under difference anxiety state. After having analyzed domestic and foreign research achievements related with sport anxiety and sport performance, the study further applied CSAI-2 (1994) questionnaire to investigate athletes’ anxiety in sprint competition of a university sports meeting in Changsha. Moreover, based on neural network model, the study also constructed related models concerning athletes’ pre-competition anxiety and their competition performance. In addition, related curves concerning athletes’ pre-competition anxiety and specific performance are also formulated.
Keywords:
Correlation, neural network model, pre-competition anxiety, specific anxiety, sprinter,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is 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, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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