Recurrent Neural Network to Forecast Sprint Performance
The present paper demonstrates that the performance of an elite track and field sprinter can be predicted by means of the dynamic, nonlinear mathematical method of recurrent neural networks (RNNs). Dataset considers three years of National Collegiate Athletics Association (NCAA) Division I competiti...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-09-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2018.1505214 |