Izvorni znanstveni članak
https://doi.org/10.24138/jcomss-2024-0107
A Hierarchical Fuzzy Inference System for Evaluating Cyclist Training Performance
Miguel A. Wister
orcid.org/0000-0003-0250-7780
; DACYTI, UJAT
*
Fabricio Landero-Cristobal
; Academic Division of Information Sciences and Technologies (DACYTI), Juarez Autonomous University of Tabasco (UJAT), Cunduacan, Mexico
Pablo Payro-Campos
; DACYTI, UJAT
Pedro Ivan Arias-Vazquez
; Multidisciplinary Academic Division of Comalcalco, UJAT, Comalcalco, Mexico
* Dopisni autor.
Sažetak
This paper proposes a method to obtain the quality of a cyclist’s training session based on training zone, heart rate, and power. Our proposal is called FuCycling (Fuzzy and CYcling). We propose a hierarchical fuzzy inference system that is applied in two phases. The first phase evaluates three input variables: training zone, heart rate, and power; the output variable is performance. In the second phase, the output variable performance will be an input variable, adding a training zone and perceived exertion rating. The output in the second phase is the final output, called session quality. Using this proposed method, a sports coach can review the quality of the cyclist’s session for further feedback on the training plan objectives. We also developed a web application to enable a sports coach to evaluate the dataset and visualize the quality rating of the session in a dashboard, training statistics, the time elapsed in the training zones, and a route map to show the training evaluation.
Ključne riječi
Fuzzy Inference System; Heart Rate; Power; Cycling; Fuzzy rule-based System
Hrčak ID:
330882
URI
Datum izdavanja:
31.3.2025.
Posjeta: 551 *