2017/07/03 by Iztok Fister, Fister, Iztok, Andres Iglesias +6
Computer Science · #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #cs.NE
paper · pdf · doi:10.48550/arxiv.1707.00718
ISCBI 2017
arxiv created 2017/07/03 · arxiv updated 2017/07/05
Modeling preference time in triathlons means predicting the intermediate times of particular sports disciplines by a given overall finish time in a specific triathlon course for the athlete with the known personal best result. This is a hard task for athletes and sport trainers due to a lot of different factors that need to be taken into account, e.g., athlete's abilities, health, mental preparations and even their current sports form. So far, this process was calculated manually without any specific software tools or using the artificial intelligence. This paper presents the new solution for modeling preference time in middle distance triathlons based on particle swarm optimization algorithm and archive of existing sports results. Initial results are presented, which suggest the usefulness of proposed approach, while remarks for future improvements and use are also emphasized.