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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IFSA Publishing, S.L.
2015-12-01
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Online Access: | http://www.sensorsportal.com/HTML/DIGEST/december_2015/Vol_195/P_2778.pdf |
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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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1725548296785625088 |