Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties
2013
Yevgeniy Bodyanskiy,
Iryna Pliss,
Olena Vynokurova
In the paper, a new flexible modification of neofuzzy
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.
Keywords
Flexible activation-membership function, flexible neo-fuzzy neuron, forecasting, identification learning algorithm
Bodyanskiy, Y., Pliss, I., Vynokurova, O. Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties. Information Technology and Management Science. Vol.16, 2013, pp.47-52. ISSN 2255-9086. e-ISSN 2255-9094.
Publication language
English (en)