Survey on Neuro-Fuzzy systems and their applications in technical diagnostics and measurement

Viharos, Zsolt János and Kis, Krisztián Balázs (2015) Survey on Neuro-Fuzzy systems and their applications in technical diagnostics and measurement. MEASUREMENT, 67. pp. 126-136. ISSN 0263-2241 10.1016/j.measurement.2015.02.001

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Abstract

Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a powerful computational model for classification and estimation, have been used in many application fields since their birth. These two techniques are somewhat supplementary to each other in a way that what one is lacking of the other can provide. This led to the creation of Neuro-Fuzzy systems which utilize fuzzy logic to construct a complex model by extending the capabilities of Artificial Neural Networks. Generally speaking all type of systems that integrate these two techniques can be called Neuro-Fuzzy systems. Key feature of these systems is that they use input-output patterns to adjust the fuzzy sets and rules inside the model. The paper reviews the principles of a Neuro-Fuzzy system and the key methods presented in this field, furthermore provides survey on their applications for technical diagnostics and measurement. © 2015 Elsevier Ltd.

Item Type: Article
Uncontrolled Keywords: fuzzy logic; Neurofuzzy system; Key feature; Input-output pattern; Inference Systems; Computational model; Complex model; Application fields; surveys; NEURAL NETWORKS; Measurements; fuzzy systems; Fuzzy sets; Fuzzy neural networks; Fuzzy inference; Computation theory; COMPLEX NETWORKS; TECHNICAL DIAGNOSTICS; neuro-fuzzy systems; Measurement
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Research Laboratory on Engineering & Management Intelligence
SWORD Depositor: MTMT Injector
Depositing User: MTMT Injector
Date Deposited: 25 Apr 2015 08:13
Last Modified: 21 Nov 2016 10:45
URI: https://eprints.sztaki.hu/id/eprint/8231

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