Williams, Janett and Li, Yan (2008) A case study using neural networks algorithms: horse racing predictions in Jamaica. In: ICAI 2008: International Conference on Artificial Intelligence , 14-17 Jul 2008, Las Vegas, NV. United States.
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Abstract
Neural networks (NNs) have been applied to predict many complex problems, such as horse racing prediction. This study investigates the performances of four supervised neural network algorithms in horse racing. We employed the Backpropagation (BP), Quasi_Newton (QN), LevenbergMarquardt (LM) and Conjugate Gradient Descent (CGD) learning algorithms to real horse racing data collected from Caymans Race Track, Jamaica. The training and testing data comes from 143 actual races collected from 1 January to 16 June 2007. The experimental results demonstrate that all algorithms can provide acceptable predictions with an accuracy of 74%. The BP algorithm slightly performs better than the other three algorithms but needs a longer training time and more parameter selections.
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| Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | No evidence of copyright restrictions. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013) |
| Date Deposited: | 06 Aug 2008 05:57 |
| Last Modified: | 02 Jul 2013 23:05 |
| Uncontrolled Keywords: | neural network; back propagation algorithm; machine learning; race tracks; supervised neural networks; robot learning |
| Fields of Research (2008): | 01 Mathematical Sciences > 0101 Pure Mathematics > 010111 Real and Complex Functions (incl. Several Variables) 08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation |
| Socio-Economic Objectives (2008): | E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences |
| URI: | http://eprints.usq.edu.au/id/eprint/4300 |
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