Development and Analysis of a Logistic-Inspired Power Curve Model for Cyclist Performance Prediction-Reference-Cited by-同舟云学术

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Development and Analysis of a Logistic-Inspired Power Curve Model for Cyclist Performance Prediction

Published:2023-11-24 Issue: Volume:31 Page:319-322
ISSN:
Container-title:International Conference on Mathematics and Machine Learning
language:
Short-container-title:

Author:

Liu Mingchen¹^ORCID

Affiliation:

1. School of Software Engineering, Huazhong University of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3653724.3653780

Reference14 articles.

1. Coggan, A.R. 2019. Training and racing using a power meter: an introduction. VeloPress Publishing.

2. Sroka R. TRAINING CHARACTERISTICS AND POWER PROFILES OF USA CYCLING ROAD CYCLISTS [J]. 2021.

3. Sanders D, Myers T, Akubat I. Training-intensity distribution in road cyclists: objective versus subjective measures[J]. International journal of sports physiology and performance, 2017, 12(9): 1232-1237.

4. Martin J C, Milliken D L, Cobb J E, Validation of a mathematical model for road cycling power[J]. Journal of applied biomechanics, 1998, 14(3): 276-291.

5. David Johnstone. 2018. How does your cycling power output compare? https://www.cyclinganalytics.com/blog/2018/06/how-does-your-cycling-power-output-compare.

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