Abstract
In the paper relational neuro-fuzzy systems are described with additional fuzzy relation connecting input and output linguistic fuzzy terms. Thanks to this the fuzzy rules have more complicated structure and can be better suited the task. Fuzzy clustering and relational equations are used to obtain the initial set of fuzzy rules and systems are then learned by the backpropagation algorithm.Simulations shows excellent performance of the modified neuro-fuzzy systems. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Scherer, R. (2008). Regression modeling with fuzzy relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5097 LNAI, pp. 317–323). https://doi.org/10.1007/978-3-540-69731-2_31
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