Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Bodyanskiy, Yevgeniy"'
A task of clustering data given in the ordinal scale under conditions of overlapping clusters has been considered. It's proposed to use an approach based on memberhsip and likelihood functions sharing. A number of performed experiments proved effecti
Externí odkaz:
http://arxiv.org/abs/1702.01200
Publikováno v:
I.J. Intelligent Systems and Applications, 2017, Vol. 9, No. 1, pp. 67-74
A fuzzy clustering algorithm for multidimensional data is proposed in this article. The data is described by vectors whose components are linguistic variables defined in an ordinal scale. The obtained results confirm the efficiency of the proposed ap
Externí odkaz:
http://arxiv.org/abs/1701.03571
Autor:
Izonin, Ivan, Tkachenko, Roman, Yendyk, Pavlo, Pliss, Iryna, Bodyanskiy, Yevgeniy, Gregus, Michal
Publikováno v:
Computation; Oct2024, Vol. 12 Issue 10, p203, 15p
Autor:
Bodyanskiy, Yevgeniy, Vynokurova, Olena, Savvo, Volodymyr, Tverdokhlib, Tatiana, Mulesa, Pavlo
Publikováno v:
International Journal of Intelligent Systems and Applications, 2016, Vol. 8, No. 8, pp.1-9
The hybrid clustering-classification neural network is proposed. This network allows increasing a quality of information processing under the condition of overlapping classes due to the rational choice of a learning rate parameter and introducing a s
Externí odkaz:
http://arxiv.org/abs/1610.07857
Publikováno v:
I.J. Information Technology and Computer Science, 2014, 08, 11-17
A new architecture and learning algorithms for the multidimensional hybrid cascade neural network with neuron pool optimization in each cascade are proposed in this paper. The proposed system differs from the well-known cascade systems in its capabil
Externí odkaz:
http://arxiv.org/abs/1610.06485
Publikováno v:
I.J. Intelligent Systems and Applications, 2015, 02, 21-26
A modification of the neo-fuzzy neuron is proposed (an extended neo-fuzzy neuron (ENFN)) that is characterized by improved approximating properties. An adaptive learning algorithm is proposed that has both tracking and smoothing properties. An ENFN d
Externí odkaz:
http://arxiv.org/abs/1610.06483
Publikováno v:
I.J. Modern Education and Computer Science, 2016, 5, 12-18
A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. A final result is
Externí odkaz:
http://arxiv.org/abs/1610.06490
Publikováno v:
I.J. Information Technology and Computer Science, 2016, 10, 1-10
An evolving weighted neuro-neo-fuzzy-ANARX model and its learning procedures are introduced in the article. This system is basically used for time series forecasting. This system may be considered as a pool of elements that process data in a parallel
Externí odkaz:
http://arxiv.org/abs/1610.06486
Publikováno v:
I.J. Intelligent Systems and Applications, 2016, 9, 1-7
Neo-fuzzy elements are used as nodes for an evolving cascade system. The proposed system can tune both its parameters and architecture in an online mode. It can be used for solving a wide range of Data Mining tasks (namely time series forecasting). T
Externí odkaz:
http://arxiv.org/abs/1610.06484
Publikováno v:
I.J. Modern Education and Computer Science, 2015, 2, 1-7
An architecture of a new neuro-fuzzy system is proposed. The basic idea of this approach is to tune both synaptic weights and membership functions with the help of the supervised learning and self-learning paradigms. The approach to solving the probl
Externí odkaz:
http://arxiv.org/abs/1610.06488