.png){kind=icon}
返回
Using Mathematical Modeling in Training Planning
.png){kind=icon}
PRE
AI
DOI：10.1123/ijspp.1.4.400.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This report aims to discuss the strengths and weaknesses of the application of systems modeling to analyze the effects of training on performance. The simplifications inherent to the modeling approach are outlined to question the relevance of the models to predict athletes' responses to training. These simplifications include the selection of the variables assigned to the system's input and output, the specification of model structure, the collection of data to estimate the model parameters, and the use of identified models and parameters to predict responses. Despite the gain in insight to understand the effects of an intensification or reduction of training, the existing models would not be accurate enough to make predictions for a particular athlete in order to monitor his or her training.
Keyword:
system identification
prediction
training schedule
performance
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.3
论文数:
3.1K
被引数:
9.7K
机构
引用论文
Low-temperature interlaminar shear strength of reactor irradiated glass-fibre-reinforced laminates.png)
Cryogenics
CryogenicsIF0
PREAI
分享收藏
Human Midbrain Sensitivity to Cognitive Feedback and Uncertainty During Classification Learning
PREAI
分享收藏
查看更多内容