ainet算法在径向基函数神经网络构造中的迭代应用

Sandro Rautenberg, Luciano Frontino de Medeiros, Wagner Igarashi, F. Gauthier, R. Bastos, J. Todesco
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引用次数: 3

摘要

本文介绍了利用人工免疫系统算法(aiNET)迭代构建径向基函数神经网络的一些步骤。这些程序在以下方面证明是有效的:(1)由免疫启发式启发的质心的自由确定;ii)经过多次迭代后获得适当的最小平方误差。将实验结果与实证结果进行比较,以证实(或否定)某些假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ITERATIVE APPLICATION OF THE AINET ALGORITHM IN THE CONSTRUCTION OF A RADIAL BASIS FUNCTION NEURAL NETWORK
This paper presents some of the procedures adopted in the construction of a Radial Basis Function Neural Network by iteratively applying the aiNET, an Artificial Immune Systems Algorithm. These procedures have shown to be effective in terms of i) the free determination of centroids inspired by an immune heuristics; and ii) the achievement of appropriate minimal square errors after a number of iterations. Experimental and empirical results are compared aiming at confirming (or not) some hypotheses.
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