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....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IFSA Publishing, S.L.
2015-12-01
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| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | http://www.sensorsportal.com/HTML/DIGEST/december_2015/Vol_195/P_2778.pdf |
| Summary: | 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.
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| ISSN: | 2306-8515 1726-5479 |