Adaptation of Sport Training Plans by Swarm Intelligence
Automatic planning of sport training sessions with Swarm Intelligence algorithms has been proposed recently in the scientific literature that influences the sports training process in practice dramatically. These algorithms are capable of generating sophisticated training plans based on an archive of the existing sports training sessions. In recent years, training plans have been generated for various sport disciplines, like road cycling, mountain biking, running. These plans have also been verified by professional sport trainers confirming that the proposed training plans correspond with the theory of sports training. Unfortunately, not enough devotion has been given to adapting the generated sports training plans due to the changing conditions that may occur frequently during their realization and causes a break in continuity of the sports training process. For instance, athletes involved in the training process can become ill or injured. These facts imply disruption of the systematic increase of the athlete’s capacity. In this paper, therefore, we propose a novel solution that is capable of adapting training plans due to the absence of an athlete from the training process.
KeywordsArtificial sport trainer Multisport Sport training Swarm intelligence Running
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