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Experimental investigation with analyzing the training method complexity of neuro-fuzzy networks based on parallel random search

Experimental investigation with analyzing the training method complexity of neuro-fuzzy networks... The problem of training neuro-fuzzy networks is discussed. The computational complexity of the method for training neuro-fuzzy networks on the basis of parallel random search is analyzed. Theoretical estimations of the speedup and efficiency of the method are found. Software implementing of the method in C++ with using the MPI library and providing the construction of neuro-fuzzy networks in terms of the given observation sets is developed. Experiments for practical tasks are carried out. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Control and Computer Sciences Springer Journals

Experimental investigation with analyzing the training method complexity of neuro-fuzzy networks based on parallel random search

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Publisher
Springer Journals
Copyright
Copyright © 2015 by Allerton Press, Inc.
Subject
Computer Science; Control Structures and Microprogramming
ISSN
0146-4116
eISSN
1558-108X
DOI
10.3103/S0146411615010071
Publisher site
See Article on Publisher Site

Abstract

The problem of training neuro-fuzzy networks is discussed. The computational complexity of the method for training neuro-fuzzy networks on the basis of parallel random search is analyzed. Theoretical estimations of the speedup and efficiency of the method are found. Software implementing of the method in C++ with using the MPI library and providing the construction of neuro-fuzzy networks in terms of the given observation sets is developed. Experiments for practical tasks are carried out.

Journal

Automatic Control and Computer Sciences – Springer Journals

Published: Mar 13, 2015

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