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Sports competition stressors modelling based on K-means algorithm

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成果类型:
期刊论文
作者:
Hong, Banghui;Yao, Xin
作者机构:
[Hong, Banghui] School of Physical Education, Central China Normal University, China
[Hong, Banghui; Yao, Xin] School of Physical Education, Guizhou Normal University, China
语种:
英文
关键词:
Clustering;Information mining;K-means;Sports competition;Stressors modelling
期刊:
Boletín Técnico
ISSN:
0376-723X
年:
2017
卷:
55
期:
16
页码:
318-325
基金类别:
This research is supported by the General project of special fund for ethnic minorities in Guizhou province in 2013 and project of Guizhou science and Technology Fund. (JK [2012] 52)
机构署名:
本校为第一机构
院系归属:
体育学院
摘要:
In this research, we present the sports competition stressors modelling based on K-means algorithm. In many clustering algorithms, the k-means is one of the most widely used algorithms. Based on the algorithm of the Hadoop platform, K-means is not improved, and its K value is randomly selected, thus increasing the blindness. Therefore this is the skillful model to conduct research. The sports competition is the sports culture important constituent, also is the sports culture dissemination important for that may also retransmit at an informationization time important competition to world each q...

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