摘要
主要运用历史研究方法和文献资料法,对20世纪中后期竞技能力增长的理论模型及其演进特征进行揭示和剖析,厘清其理论的科学基础与演进特点。结果表明:1)竞技能力增长模型大抵进路为:以1950年代Selye应激理论提出的GAS模型衍生而来的运动训练"超量补偿循环"模型、"高级适应循环"模型、"超量补偿循环和代偿适应"模型等生理学理论模型,到基于生理学、物理学和数学、计算机科学提出的CP模型、IR模型、PerPot模型等计算模型;2)生理学是运动训练的重要基础;3)数学模型通过假设与验证,实现对复杂生物系统的有效表达,并可根据个体参数不同实现模型个性化;4)融合计算机信息技术的"PerPot模型"则通过现有数据,即刻优化训练计划和预防过度训练,借助其强大的运算功能,达到运动训练数据与目标成绩之间的高度拟合。研究认为,同其他科学与社会的发展规律一致,如吉姆·格雷在"科学的第4个范式"中所言,数据密集型科学理论或同样是运动训练理论与方法的下一个科学范式,并有待基于此范式,构建下一个竞技能力增长理论模型。
Objective: Later period of the 20th century, through two world wars, and usher in the era of "big science" of society, science and history background, this paper reveals and analyzes the theoretical models and its evolution characteristics of the athletic performance enhancement from that time on, and then clarifies the scientific basis and theory evolution characteristics. Method ; mainly using methds of historical research and literature. Result : 1) the generally evo- lution approach of theoretical models of the athletic performance enhancement is as follows : the physiological model of "cycle of suercompensation", "cycle of super adaptation"," cycle of su- percompensation and compensatory adaptation" that based on the Selye's GAS (general adapta- tion syndrome) model in the 1950 s ; to the computational models of CP ( critical power), IR (impulse-response), PerPot(The Performance Potential Metamodel)that based on physiology, physics and mathematics, computer science; g )Physiology is an important basis of athletic training; 3)Mathematical model by assuming and verification, to achieve effective expression of the complex biological system, and according to different individual parameters personalized im- plementation models;4)the PerPot that integration of computer information technology can use the existing data to optimize training plans and prevent excessive training immediately, with its strong operation function to achieve a good fit between athletic training data and target results. Conclusion.. With other law of development of science and society, and the same to Jim Gray in "the fourth paradigm of science", data-intensive scientific theory or is also a scientific paradigm of athletic training theory and method, and needs to be based on this paradigm, build the next theoretical model of the athletic performance enhancement.
出处
《体育科学》
CSSCI
北大核心
2016年第2期14-24,40,共12页
China Sport Science
基金
江苏省博士后基金项目(1402039C)
南京航空航天大学基本业务青年科技创新基金项目(NR2015019)
关键词
运动训练
竞技能力增长
生理学
数学
计算科学
数据密集型
athletic trainning
athletic performance enhancement
physiology
math
corn putational science
data-intensive