Registration Number
0224U001993,
(0122U001701)
, R & D reports
Title
Development of methods and algorithms for combined learning of deep neuro-neo-fuzzy systems under short training set conditions
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Розробка архітектур, методів та алгоритмів комбінованого навчання нових глибинних стекових каскадних нейро-нео-фаззі систем за умов короткої навчальної вибірки
Head
Bodianskyi Yevhenii V., д.т.н.
Registration Date
03-02-2024
Organization
Kharkiv National University Of Radio Electronics
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Сonducting a research aimed at creating architectures, methods and algorithms for combined learning of new deep stacking cascade neuro-neo-fuzzy systems (DSCNNFS) to solve a wide range of data mining problems under short training set conditions using the latest research in this field (Deep Neural Networks, Deep Learning, Data Science, Evolving Systems, Stacking Systems, Cascaded Systems, Hybrid Systems of Computational Intelligence).
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The research was aimed at development of methods and algorithms for fast combined learning of a new class of computational intelligence systems – deep stacking cascade neuro-neo-fuzzy systems – under the conditions of a short training sets for a wide class of data processing tasks, first of all, pattern recognition (classification-clustering), forecasting, faults detection, control, diagnosis, decision-making, etc., arising in both civil and military applications, when the amount of source information is too small for training of traditional deep networks.
Product Description
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Boiko Olena O.
Popov Sergii V.
Dolotov Artem I.
Pliss Iryna P.
Kostyuk Serhii O.
Olha Chala
Vynokurova Olena A.
Bodyanskiy Yevgeniy V.
Filatov Valentyn O.
Alina Shafronenko
Brodetskiy Filip A.
Styopin Oleksandr S.
Pirus Anastasiya Ye.
Reveka Kateryna I.
Fedorenko Dariia O.
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2024-02-03
