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An application of weighted triangular norms to complexity reduction of neuro-fuzzy systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2008) 5097 LNAI 207-216
DOI: 10.1007/978-3-540-69731-2_21
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Abstract

In the paper we develop a new method for designing and reduction of neuro-fuzzy systems. The method is based on the concept of the weighted triangular norms. In subsequent stages we reduce number of inputs, number of rules and number of antecedents. Simulation results are given. © 2008 Springer-Verlag Berlin Heidelberg.

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Cpalka, K., & Rutkowski, L. (2008). An application of weighted triangular norms to complexity reduction of neuro-fuzzy systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5097 LNAI, pp. 207–216). https://doi.org/10.1007/978-3-540-69731-2_21

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