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INICIO | 24 de mayo de 2024
  

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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Equipo DML-E
Instituto de Ciencias Matemáticas (ICMAT - CSIC)
rmm()icmat.es