Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties

Yevgeniy Bodyanskiy, Iryna Pliss, Olena Vynokurova


In the paper, a new flexible modification of neo- fuzzy neuron, neuro-fuzzy network based on these neurons and adaptive learning algorithms for the tuning of their all parameters are proposed. The algorithms are of interest because they ensure the on-line tuning of not only the synaptic weights and membership function parameters but also forms of these functions that provide improving approximation properties and allow avoiding the occurrence of “gaps” in the space of inputs.


Flexible activation-membership function; flexible neo-fuzzy neuron; forecasting; identification learning algorithm

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