Predicting Countermovement Jump Heights By Time Domain, Frequency Domain, and Machine Learning Algorithms
Document Type
Conference Proceeding
Publication Date
2-5-2018
School
Computing Sciences and Computer Engineering
Abstract
© 2017 IEEE. In this paper, we introduce an experiment evaluating performance of football players in countermovement jumps (CMJs). Three methods including time domain, frequency domain, and machine learning algorithms are proposed for performance evaluation. Correlation coefficients and p-values are given for time domain and frequency domain methods, and prediction errors are given for different machine learning algorithms.
Publication Title
Proceedings - 2017 10th International Symposium on Computational Intelligence and Design, ISCID 2017
First Page
167
Last Page
170
Recommended Citation
Zhou, Z.,
Shakya, S.,
Sha, Z.
(2018). Predicting Countermovement Jump Heights By Time Domain, Frequency Domain, and Machine Learning Algorithms. Proceedings - 2017 10th International Symposium on Computational Intelligence and Design, ISCID 2017, 167-170.
Available at: https://aquila.usm.edu/fac_pubs/17921