Learning from imprecise examples with GA-P algorithms.

Título inglés	Learning from imprecise examples with GA-P algorithms.
Título español	Aprendizaje a partir de ejemplos imprecisos con algoritmos GA-P.
Autor/es	Sánchez, Luciano ; Couso, Inés
Organización	Dep. Informát. Univ. Oviedo, Oviedo, España;Dep. Estad. Inv. Oper. Univ. Oviedo, Oviedo, España
Revista	1134-5632
Publicación	1998, 5 (2-3): 305-319, 13 Ref.
Tipo de documento	articulo
Idioma	Inglés
Resumen inglés	GA-P algorithms combine genetic programming and genetic algorithms to solve symbolic regression problems. In this work, we will learn a model by means of an interval GA-P procedure which can use precise or imprecise examples. This method provides us with an analytic expression that shows the dependence between input and output variables, using interval arithmetic. The method also provides us with interval estimations of the parameters on which this expression depends. The algorithm that we propose has been tested in a practical problem related to electrical engineering. We will obtain an expression of the length of the low voltage electrical line in some Spanish villages as a function of their area and their number of inhabitants. The obtained model is compared to statistical regression-based, neural network, fuzzy rule-based and genetic programming-based models.
Clasificación UNESCO	120304
Palabras clave español	Algoritmos de aprendizaje ; Algoritmos genéticos ; Lógica simbólica ; Lógica difusa ; Regresión
Código Z-Math	Zbl 0957.68100
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