Intelligence Planning for Aerobic Training Using a Genetic Algorithm

Kumyaito, Nattapon; Tamee, Kreangsak

doi:10.1007/978-3-319-70016-8_17

Cited by 1 publication

(2 citation statements)

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“…The process of sports training generation is tailored to generate the optimum training plans for athletes to reach the highest levels of performance. Sports training must be done carefully to avoid the pitfalls of inadequate training plans such as over-training, plateau effects, and monotony, which impact the performance of athletes negatively [15]. Some approaches generate generalized sports training plans for athletes [15]- [18] where target power-meter, heart rate, and duration are proposed for individualized sports training sessions.…”

Section: A Sport Training Generationmentioning

confidence: 99%

“…Sports training must be done carefully to avoid the pitfalls of inadequate training plans such as over-training, plateau effects, and monotony, which impact the performance of athletes negatively [15]. Some approaches generate generalized sports training plans for athletes [15]- [18] where target power-meter, heart rate, and duration are proposed for individualized sports training sessions. How and where the trainee will execute his goals are left to his own will; some approaches do not generate actual sports training, but aid in the training process (e.g.…”

Section: A Sport Training Generationmentioning

confidence: 99%

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A Modified Evolutionary Algorithm for Generating the Cycling Training Routes

Rajšp

Fister

2022

IEEE Access

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We present a novel method for generating cycling training routes from geographical property graphs based on an Evolutionary Algorithm. The algorithm operators of crossover and mutation are adjusted for use in the Property Graph domain. Data fusion of geographical data from the OpenStreetMap, EU-DEM digital surface model, and existing training records is performed as a basis of the intersections-paths' property graph. The proposed approach allows route generation based on their starting and ending points in the property graph and their distance and ascent. A property graph of all intersections and cycling roads is shown and generated for the regions of Podravje and Pomurje. The property graph used in the proposed algorithm's feasibility demonstration is shown. This is done by presenting four different cases of routes that were generated with our algorithm. The algorithm allows for generating classic cycling routes of A to B nature, routes with more than two fixed points, as well as cyclical training routes. The research is concluded by offering further directions on route generation research.

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Section: A Sport Training Generationmentioning

confidence: 99%