Diseño y entrenamiento en paralelo de redes neuronales, por medio de algoritmos geneticos desordenados y altamente recursivos


Authors

  • Delia Johana Munoz

Abstract

El siguiente trabajo ataca de manera inusual, dos típicos problemas de optimización, como lo son, el diseño (capas-neuronas) y entrenamiento (acople de pesos) de una red neuronal artificial. Para tal propósito se hace uso de un algoritmo genético adaptado, que en últimas y al menos en teoría, poseerá la capacidad de predecir de manera óptima el diseño y el resultado del entrenamiento de una RNA (Red Neuronal Artificial), para alguna tarea en particular que el programador desee que aprenda. También se considera la gama de dificultades y limitaciones que se generan en el sistema, animando y dando recursos al lector para el desarrollo de una posible evolución de la técnica.

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Published

2006-01-05

How to Cite

Munoz, D. J. (2006). Diseño y entrenamiento en paralelo de redes neuronales, por medio de algoritmos geneticos desordenados y altamente recursivos. Scientia Et Technica, 1(30). Retrieved from https://ojs2.utp.edu.co/index.php/revistaciencia/article/view/6559

Issue

Vol. 1 No. 30 (2006)

Section

Sistemas y Computación

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