On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing

On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing

Nowadays computational intelligence methods are widely spread in different tasks solving in Data Mining under uncertainty, nonlinearity, and disturbed by different type of stochastic, chaotic noises conditions. In the paper the hybrid neuro-neo-fuzzy system of computational intelligence is proposed....

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Main Authors: Yevgeniy Bodyanskiy, Olena Vynokurova, Iryna Pliss, Galina Setlak
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2015-12-01
Series:Sensors & Transducers
Subjects:
Computational intelligence
Data stream mining
Neuro-neo-fuzzy systems
Neo-fuzzy-neuron
Adaptive learning algorithm
Information processing in on-line mode.
Online Access:http://www.sensorsportal.com/HTML/DIGEST/december_2015/Vol_195/P_2778.pdf
id doaj-e255e7f0c75d456a910a6df7aff8e608
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spelling doaj-e255e7f0c75d456a910a6df7aff8e6082020-11-24T23:28:43ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792015-12-01195126268On-line Hybrid System of Computational Intelligence for Data Streams Adaptive ProcessingYevgeniy Bodyanskiy0Olena Vynokurova1Iryna Pliss2Galina Setlak3 Kharkiv National University of Radio Electronics, Leniva av., 14, Kharkiv, 61166, Ukraine Kharkiv National University of Radio Electronics, Leniva av., 14, Kharkiv, 61166, Ukraine Kharkiv National University of Radio Electronics, Leniva av., 14, Kharkiv, 61166, UkraineRzeszow University of Technology, Al. Powstancow Warszawy, 12, Rzeszow, 35-959, PolandNowadays computational intelligence methods are widely spread in different tasks solving in Data Mining under uncertainty, nonlinearity, and disturbed by different type of stochastic, chaotic noises conditions. In the paper the hybrid neuro-neo-fuzzy system of computational intelligence is proposed. This system is distinguished by the computational simplicity, the learning process high speed and the improved approximation properties. The hybrid neuro-neo-fuzzy system can be used for solving of Data Stream Mining tasks, which are connected with real time processing of non-stationary nonlinear stochastic and chaotic signals that are sequentially fed into system in on-line mode. http://www.sensorsportal.com/HTML/DIGEST/december_2015/Vol_195/P_2778.pdfComputational intelligenceData stream miningNeuro-neo-fuzzy systemsNeo-fuzzy-neuronAdaptive learning algorithmInformation processing in on-line mode.
collection DOAJ
language English
format Article
sources DOAJ
author Yevgeniy Bodyanskiy
Olena Vynokurova
Iryna Pliss
Galina Setlak
spellingShingle Yevgeniy Bodyanskiy
Olena Vynokurova
Iryna Pliss
Galina Setlak
On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
Sensors & Transducers
Computational intelligence
Data stream mining
Neuro-neo-fuzzy systems
Neo-fuzzy-neuron
Adaptive learning algorithm
Information processing in on-line mode.
author_facet Yevgeniy Bodyanskiy
Olena Vynokurova
Iryna Pliss
Galina Setlak
author_sort Yevgeniy Bodyanskiy
title On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
title_short On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
title_full On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
title_fullStr On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
title_full_unstemmed On-line Hybrid System of Computational Intelligence for Data Streams Adaptive Processing
title_sort on-line hybrid system of computational intelligence for data streams adaptive processing
publisher IFSA Publishing, S.L.
series Sensors & Transducers
issn 2306-8515
1726-5479
publishDate 2015-12-01
description Nowadays computational intelligence methods are widely spread in different tasks solving in Data Mining under uncertainty, nonlinearity, and disturbed by different type of stochastic, chaotic noises conditions. In the paper the hybrid neuro-neo-fuzzy system of computational intelligence is proposed. This system is distinguished by the computational simplicity, the learning process high speed and the improved approximation properties. The hybrid neuro-neo-fuzzy system can be used for solving of Data Stream Mining tasks, which are connected with real time processing of non-stationary nonlinear stochastic and chaotic signals that are sequentially fed into system in on-line mode.
topic Computational intelligence
Data stream mining
Neuro-neo-fuzzy systems
Neo-fuzzy-neuron
Adaptive learning algorithm
Information processing in on-line mode.
url http://www.sensorsportal.com/HTML/DIGEST/december_2015/Vol_195/P_2778.pdf
work_keys_str_mv AT yevgeniybodyanskiy onlinehybridsystemofcomputationalintelligencefordatastreamsadaptiveprocessing
AT olenavynokurova onlinehybridsystemofcomputationalintelligencefordatastreamsadaptiveprocessing
AT irynapliss onlinehybridsystemofcomputationalintelligencefordatastreamsadaptiveprocessing
AT galinasetlak onlinehybridsystemofcomputationalintelligencefordatastreamsadaptiveprocessing
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