DocumentCode :
2310412
Title :
Skill and tactic diagnosis for table tennis matches based on artificial neural network and genetic algorithm
Author :
Mao, Wenwu ; Yu, Lijuan ; Zhang, Hui ; Ling, Peiliang ; Wang, Haihang ; Wang, Jie
Volume :
4
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1847
Lastpage :
1851
Abstract :
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.
Keywords :
backpropagation; genetic algorithms; neural nets; sport; artificial neural network; backpropagation network; genetic algorithm; skill diagnosis; table tennis matches; tactic diagnosis; Artificial neural networks; Data acquisition; Educational institutions; Indexes; Joints; Sensitivity analysis; Training; artificial neural network; genetic algorithm; skill and tactic diagnosis; table-tennis match;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5584534
Filename :
5584534
Link To Document :
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