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A Novel Rough Neural Network and Its Training Algorithm

Sheng-He SUN, Xiao-Dan MEI, Zhao-Li ZHANG

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Summary :

A novel rough neural network (RNN) structure and its application are proposed in this paper. We principally introduce its architecture and training algorithms: the genetic training algorithm (GA) and the tabu search training algorithm (TSA). We first compare RNN with the conventional NN trained by the BP algorithm in two-dimensional data classification. Then we compare RNN with NN by the same training algorithm (TSA) in functional approximation. Experiment results show that the proposed RNN is more effective than NN, not only in computation time but also in performance.

Publication
IEICE TRANSACTIONS on Information Vol.E85-D No.2 pp.426-431
Publication Date
2002/02/01
Publicized
Online ISSN
DOI
Type of Manuscript
LETTER
Category
Biocybernetics, Neurocomputing

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