Automated Generation of Training Programs for Swimmers Generating Weekly Training Plans in the Style of a Professional Swimming Coach Using Genetic Algorithms and Random Trees
Typ
Examensarbete för masterexamen
Program
Publicerad
2021
Författare
Eriksson, Rikard
Nicander, Johan
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Optimal training planning is a combination of art and science, and a task that
requires expert knowledge. This is a time-consuming task that is often exclusively
available to top tier athletes. Many athletes outside the elite do not have access
or cannot afford to hire a professional coach to help them create their training
plans. In this study, we investigate if it is possible to use the historical training
logs of elite swimmers to construct detailed weekly training plans similar to how
a specific professional coach would have planned. We present a software system
based on machine learning and genetic algorithms for generation of detailed weekly
training plans based on desired volume, intensity, training frequency, and athlete
characteristics. The system schedules training sessions from a library extracted
from training plans written by a professional swimming coach. Results show that
the proposed system is able to generate highly accurate training plans in terms of
training load, types of sessions, and structure, compared to the human coach.
Beskrivning
Ämne/nyckelord
SWIMMING , TRAINING PLANNING , TRAINING PLAN GENERATION , MACHINE LEARNING , EXERCISE INTELLIGENCE