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基于对应分析模型原理的户外运动安全风险研究
引用本文:欧雅怡,刘〓亚,马逢伯.基于对应分析模型原理的户外运动安全风险研究[J].广州体育学院学报,2017,37(2):43-48.
作者姓名:欧雅怡  刘〓亚  马逢伯
作者单位:北京理工大学珠海学院,广东珠海,519088
摘    要:通过对我国2001年至2014年期间,258个户外运动安全事故案例的统计和分析,结合国内外相关研究,建立户外运动安全风险分析框架,将户外运动安全风险划分为4个维度,18个因素指标.根据对应分析模型原理,深入研究户外运动中季节、月份与时段风险的对应性关系,R(3.2.0)软件运行结果显示:户外运动中,凌晨和晚上的风险指数最高;春季、秋季的上午和下午时段,可能存在的伤亡风险几率较高;5月、9月、10月的上午和晚上,3月、6月、11月、12月的下午,1月和4月的凌晨时段,可能存在的伤亡风险几率更高.使用Minitab软件,根据累积贡献率80%以上为主要因素的帕累托原则得到8个主要风险因素和7个次要风险因素.

关 键 词:户外运动  安全风险  维度  因素指标  对应分析模型原理
修稿时间:2016/12/14 0:00:00

Research on Security Risk of Outdoor Sports Based on Correspondence Analysis Model
OU Ya-yi,LIU Y,MA feng-bo.Research on Security Risk of Outdoor Sports Based on Correspondence Analysis Model[J].Journal of Guangzhou Physical Education Institute,2017,37(2):43-48.
Authors:OU Ya-yi  LIU Y  MA feng-bo
Institution:(The zhuhai college of Beijing institute of technology,Zhuhai 519088,China)
Abstract:Though statistical analysis of 258 accident cases of outdoor sports in China during the period from 2001 to 2014, this paper aims at building an analysis framework for security risk of outdoor sports which can be divided into four dimensions and eighteen factors. According to the principle of correspondence analysis model intensive study will be made about the correspondent relation between outdoor sports and seasons, months and time. The operation of R (3.2.0) software shows: the risk index is highest in the early hours in the morning and in the evening; the potential casualty risk is comparatively high in the morning and afternoon in spring and autumn; the potential casualty risk is higher in the morning and evening in May, September and October, in the afternoon in March, June, November and December, and in the early hours in the morning in January and April. According to Minitab software and Pareto Principle, there are 8 major factors whose accumulative contributions ratios reach up to 80% and 7 minor factors of Security Risk of Outdoor Sports.
Keywords:outdoor sports  security risk  dimension  factor index  correspondence analysis model
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