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