Hybrid neuro-neo-fuzzy system and its adaptive learning algorithm

Nowadays computational intelligence methods are widely spread in different tasks solving in Data Mining under uncertain, nonlinear, stochastic, chaotic and disturbed by different type of 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 connect with real time processing of nonstationary nonlinear stochastic and chaotic signals that are sequentially fed into system in on-line mode.