基于复杂网络模型的运动损伤程度评估模型Sports injury degree evaluation model based on complex network model
介博
摘要(Abstract):
现有的运动损伤程度评估模型不能有效地描述运动强度与损伤程度之间的关系。为了解决此问题,通过对致伤因子的研究、对损伤基函数的选取,达到了评估运动损伤程度的目的。通过研究RBF神经复杂网络、设计复杂网络下运动损伤隐含层,建立RBF运动损伤评估模型。模拟应用环境设计仿真实验,结果表明,应用RBF运动损伤评估模型,解决运动损伤与运动强度之间关联度问题,避免运动强度过大造成运动损伤;在一定环境下,能有效描述运动强度与损伤程度之间的关系。
关键词(KeyWords): 复杂网络模型;运动损伤;程度评估;RBF;致伤因子;外部因素
基金项目(Foundation): 湖北省基金项目(B2015032)~~
作者(Author): 介博
DOI: 10.16652/j.issn.1004-373x.2018.06.040
参考文献(References):
- [1]蒋乐,刘俊勇,魏震波,等.基于Bayesian网络与复杂网络理论的特/超高压输电线路状态评估模型[J].高电压技术,2015,41(4):1278-1284.JIANG Le,LIU Junyong,WEI Zhenbo,et al.A condition assessment model of EHV/UHV transmission line based on Bayesian network and complex network theory[J].High voltage engineering,2015,41(4):1278-1284.
- [2]张树奎,肖英杰,尤晓静.基于复杂网络的交叉航道内船舶汇聚度模型[J].重庆交通大学学报(自然科学版),2017,36(2):95-100.ZHANG Shukui,XIAO Yingjie,YOU Xiaojing.Model of ships aggregation at fairway crossing based on complex network[J].Journal of Chongqing Jiaotong University(Natural sciences),2017,36(2):95-100.
- [3]徐敬友,陈冲,罗纯坚,等.基于改进复杂网络模型的电网关键环节辨识[J].电力系统自动化,2016,40(10):53-61.XU Jingyou,CHEN Chong,LUO Chunjian,et al.Identification of power grid key parts based on improved complex network model[J].Automation of electric power systems,2016,40(10):53-61.
- [4]韩忠明,陈炎,李梦琪,等.一种有效的基于三角结构的复杂网络节点影响力度量模型[J].物理学报,2016,65(16):285-296.HAN Zhongming,CHEN Yan,LI Mengqi,et al.An efficient node influence metric based on triangle in complex networks[J].Acta physica sinica,2016,65(16):285-296.
- [5]熊云艳,肖文俊,毛宜军,等.基于度序列的复杂网络模型及其路由策略分析[J].华南理工大学学报(自然科学版),2015,43(11):30-34.XIONG Yunyan,XIAO Wenjun,MAO Yijun,et al.A degree sequence-based complex network model and its routing strategy analysis[J].Journal of South China University of Technology(natural science edition),2015,43(11):30-34.
- [6]马文韬,吉斌,敖兴勇.近30年国外排球运动研究热点的文献计量学分析[J].山东体育科技,2016,38(1):33-39.MA Wentao,JI Bin,AO Xingyong.Bibliometric analysis of volleyball research highlights abroad in the last 30 years[J].Shandong sports science&technology,2016,38(1):33-39.
- [7]韩永良,李咏梅,罗琦,等.视神经脊髓炎患者默认网络及额顶网络功能连接的研究[J].磁共振成像,2017,8(2):105-109.HAN Yongliang,LI Yongmei,LUO Qi,et al.Study of functional connectivity of default mode network and frontoparietal network in neuromyelitis optica[J].Chinese journal of magnetic resonance imaging,2017,8(2):105-109.
- [8]沈诚,吴殷,张兰兰,等.不同本体感觉输入对复杂运动动作表象的影响:f MRI研究[J].天津体育学院学报,2016,31(3):227-232.SHEN Cheng,WU Yin,ZHANG Lanlan,et al.The effect of different proprioception inputs on motor imagery of complex movement:an f MRI study[J].Journal of Tianjin University of Sport,2016,31(3):227-232.
- [9]何有世,李金海,马云蕾,等.基于复杂网络构建面向主题的在线评论挖掘模型[J].软科学,2015(10):115-119.HE Youshi,LI Jinhai,MA Yunlei,et al.Construction of mining model of subject-oriented online reviews based on complex network[J].Soft science,2015(10):115-119.
- [10]王靖飞.基于复杂网络的风电消纳能力评估模型改进[J].中国电力,2017,50(1):136-139.WANG Jingfei.Wind power accommodation capacity evaluation model based on complex network[J].Electric power,2017,50(1):136-139.