Generating Training Plans Based on Existing Sports Activities

Creating training plans is the more important task for real trainers, in which specific training sessions are prescribed to trainees according to intensity, duration, type, and repetition, for a specific training period. After realization of the plan, it is expected that the athlete in training would acquire the proper performance level needed for achieving the top results in competitions. Typically, this planning requires controlling the athlete’s results obtained during the realization and making decisions by analyzing these. Especially, the performance analysis is recently becoming too difficult for the trainers due to enormous amount of data generated by mobile devices during the training.

[1]  Iztok Fister,et al.  Adaptation and Hybridization in Nature-Inspired Algorithms , 2015 .

[2]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[3]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[4]  A. E. Eiben,et al.  Introduction to Evolutionary Computing , 2003, Natural Computing Series.

[5]  Iztok Fister,et al.  A hybrid bat algorithm , 2013, ArXiv.

[6]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[7]  Maurice K. Wong,et al.  Algorithm AS136: A k-means clustering algorithm. , 1979 .

[8]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[9]  J. A. Hartigan,et al.  A k-means clustering algorithm , 1979 .

[10]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[11]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[12]  Janez Demsar,et al.  Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..

[13]  L. de Franco Tobar,et al.  Motivational factors of senior athletes to participate in the Ironman , 2013 .

[14]  M. Friedman A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings , 1940 .

[15]  Iztok Fister,et al.  Planning the sports training sessions with the bat algorithm , 2015, Neurocomputing.