摘要
背景:诸多学者都认同不同的体质指标对体质综合评价作用不同,却一直没有有效方法建立体质综合评价模型。目的:采用人工神经网络技术建立体质综合评价模型。方法:以上海市某高校教职工为研究对象,以人工神经网络技术,建立的不同年龄、不同性别的二级指标、三级指标体质综合评价模型。结果与结论:实验所建立的二级指标、三级指标体质综合评价模型的拟合度分别>93%和>94%,权重计算结果可信。在此模型中,反映身体素质的指标所占的权重系数总体最高,其次为反映身体形态的指标,而反映身体功能的指标较低。说明实验采用人工神经网络技术成功建立体质综合评价模型。
BACKGROUND：Many scholars agree that different fitness indexes play different roles in the comprehensive evaluation of the fitness. But there is no effective way to build a comprehensive fitness evaluation model. OBJECTIVE：To establish the comprehensive fitness evaluation model based on artificial neural network. METHODS：The university faculties in Shanghai were selected as objects and the artificial neural network technology was used to establish the comprehensive fitness evaluation models of second-rank index and third-rank index in different ages ad genders. RESULTS AND CONCLUSION：The fitting degrees of the second-rank index and third-rank index comprehensive fitness evaluation models established in this experiment were 93% and 94%. The weight calculation results are reliable. In this model, the indicators reflecting body diathesis accounted for the highest proportion of weight coefficients, followed by the indicators reflecting the body shape, and the indicators reflecting the physical function accounted for the lowest proportion of weight coefficients. The findings confirmed that the comprehensive fitness evaluation model was successfully established by using the artificial neural network technology.
出处
《中国组织工程研究》
CAS
CSCD
2012年第37期6956-6960,共5页
Chinese Journal of Tissue Engineering Research
基金
上海市科学技术委员会2010"创新行动计划"专项项目资助
课题编号:10490503500
江西省教育厅2011年"高校人文社科"一般项目(TY1116)~~
