New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units
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| Format: | Artículo científico |
| Language: | es |
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Asociación Española para la Inteligencia Artificial
2014
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| _version_ | 1876459165274079232 |
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| author | Antonio J. Tallón-Ballesteros |
| author_facet | Antonio J. Tallón-Ballesteros |
| contents | New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units Antonio J. Tallón-Ballesteros Ingeniería product unit classification sigmoidal unit feature selection evolutionary algorithm This paper sums up the main contributions of the PhD Dissertation with an homonymous name to the current article. Specifically, three contributions to train feed-forward neural network models based on evolutionary computation for a classification task are described. The new methodologies have been evaluated in three-layered neural models, including one input, one hidden and one output layer. Particularly, two kind of neurons such as product and sigmoidal units have been considered in an independent fashion for the hidden layer. Experiments have been carried out in a good number of problems, including three complex real-world problems, and the overall assessment of the new algorithms is very outstanding. Statistical tests shed light on that significant improvements were achieved. The applicability of the proposals is wide in the sense that can be extended to any kind of hidden neuron, either to other kind of problems like regression or even optimization with special emphasis in the two first approaches. 2014 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92537916006 es http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.54 Vol.17 |
| format | Artículo científico |
| id | redalyc_92537916006 |
| institution | Redalyc |
| language | es |
| publishDate | 2014 |
| publisher | Asociación Española para la Inteligencia Artificial |
| spellingShingle | New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units Antonio J. Tallón-Ballesteros Ingeniería product unit classification sigmoidal unit feature selection evolutionary algorithm New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units Antonio J. Tallón-Ballesteros Ingeniería product unit classification sigmoidal unit feature selection evolutionary algorithm This paper sums up the main contributions of the PhD Dissertation with an homonymous name to the current article. Specifically, three contributions to train feed-forward neural network models based on evolutionary computation for a classification task are described. The new methodologies have been evaluated in three-layered neural models, including one input, one hidden and one output layer. Particularly, two kind of neurons such as product and sigmoidal units have been considered in an independent fashion for the hidden layer. Experiments have been carried out in a good number of problems, including three complex real-world problems, and the overall assessment of the new algorithms is very outstanding. Statistical tests shed light on that significant improvements were achieved. The applicability of the proposals is wide in the sense that can be extended to any kind of hidden neuron, either to other kind of problems like regression or even optimization with special emphasis in the two first approaches. 2014 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92537916006 es http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.54 Vol.17 |
| title | New training approaches for classification based on evolutionary neural networks. Application to product and sigmoidal units |
| topic | Ingeniería product unit classification sigmoidal unit feature selection evolutionary algorithm |
| url | https://www.redalyc.org/articulo.oa?id=92537916006 |