%A Sandro Rautenberg
%A Luciano Frontino de Medeiros
%A Wagner Igarashi
%A Fernando Ostuni Gauthier
%A Rog?rio Cid Bastos
%A Jos? Leomar Todesco
%J Learning and Nonlinear Models - Revista da Sociedade Brasileira de Redes Neurais (SBRN)
%T Iterative Application of the aiNET Algorithm in the Construction of a Radial Basis Function Neural Network
%X 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.
%N 1
%P 24-31
%V 4
%D 2008
%I ?Sociedade Brasileira de Redes Neurais
%L cogprints6046

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