MATEC Web Conf.
Volume 155, 2018VIII International Scientific and Practical Conference “Information and Measuring Equipment and Technologies“ (IME&T 2017)
|Number of page(s)||7|
|Published online||28 February 2018|
High-Performance Adaptive Neurofuzzy Classifier with a Parametric Tuning
National Research Tomsk State University, 634050, Tomsk, Russia
a Corresponding author: firstname.lastname@example.org
The article is devoted to research and development of adaptive algorithms for neuro-fuzzy inference when solving multicriteria problems connected with analysis of expert (foresight) data to identify technological breakthroughs and strategic perspectives of scientific, technological and innovative development. The article describes the optimized structuralfunctional scheme of the high-performance adaptive neuro-fuzzy classifier with a logical output, which has such specific features as a block of decision tree-based fuzzy rules and a hybrid algorithm for neural network adaptation of parameters based on the error back-propagation to the root of the decision tree.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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