Evolutionary product unit based neural networks for regression
This paper presents a new method for regression based on the evolution of a type of feed-forward neural networks whose bAsís function units are products of the inputs raised to real number power. These nodes are usually called product units. The main advantage of product units is their capacity for...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2006 |
| País: | España |
| Institución: | Universidad Loyola Andalucía |
| Repositorio: | Brújula |
| OAI Identifier: | oai:repositorio.uloyola.es:20.500.12412/1015 |
| Acceso en línea: | http://hdl.handle.net/20.500.12412/1015 |
| Access Level: | acceso abierto |
| Palabra clave: | product units regression evolutionary computation |
| Sumario: | This paper presents a new method for regression based on the evolution of a type of feed-forward neural networks whose bAsís function units are products of the inputs raised to real number power. These nodes are usually called product units. The main advantage of product units is their capacity for implementing higher order functions. |
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