Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm
Due to the complexity, multiplicity and randomness of table tennis matches, the paper presents skill and tactic diagnostic model for table-tennis matches of elite athletes with artificial neural network and genetic algorithm. A back propagation network is used to build basic structure of the model and genetic algorithm is established to optimize the connection weights and threshold values of the neural network to improve the prediction precision and congestion performance. The application results show that it is an effective tool to provide decision support for table-tennis players.
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