Перегляд за Автор "Zaychenko, Yu."
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Документ Відкритий доступ Fuzzy portfolio optimization problem under uncertainty сonditions with application of computational intelligence methods(КПІ ім. Ігоря Сікорського, 2020) Zaychenko, H.; Zaychenko, Yu.Документ Відкритий доступ Investigation of computational intelligence methods in forecasting at financial markets(КПІ ім. Ігоря Сікорського, 2023) Zaychenko, Yu.; Zaichenko, He.; Kuzmenko, O.Abstract. The work considers intelligent methods for solving the problem of shortand middle-term forecasting in the financial sphere. LSTM DL networks, GMDH, and hybrid GMDH-neo-fuzzy networks were studied. Neo-fuzzy neurons were chosen as nodes of the hybrid network, which allows to reduce computational costs. The optimal network parameters were found. The synthesis of the optimal structure of hybrid networks was performed. Experimental studies of LSTM, GMDH, and hybrid GMDH-neo-fuzzy networks with optimal parameters for short- and middleterm forecasting have been conducted. The accuracy of the obtained experimental predictions is compared. The forecasting intervals for which the application of the researched artificial intelligence methods is the most expedient have been determined.Документ Відкритий доступ Investigation of сomputational intelligence methods in forecasting problems at stock exchanges(КПІ ім. Ігоря Сікорського, 2021) Zaychenko, Yu.; Hamidov, G.; Gasanov, A.Документ Відкритий доступ Medical images of breast tumors diagnostics with application of hybrid CNN–FNN network(КПІ ім. Ігоря Сікорського, 2018) Zaychenko, Yu.; Hamidov, G.; Varga, I.The problem of classification of breast tumors on medical images is considered. For its solution the new class of convolutional neural networks-hybrid CNN–FNN network is developed in which convolutional neural network VGG-16 is used as the feature extractor while fuzzy neural network NEFClass is used as the classifier. Training algorithms of FNN were implemented. The experimental investigations of the suggested hybrid network on the standard data set were carried out and comparison with known results was performed. The problem of data dimensionality reduction is considered and application of PCM method is investigated.Документ Відкритий доступ Multilayer gmdh-neuro-fuzzy network based on extended neo-fuzzy neurons and its application in online facial expression recognition(КПІ ім. Ігоря Сікорського, 2020) Bodyanskiy, Ye.; Zaychenko, Yu.; Hamidov, G.; Kulishova, N.Документ Відкритий доступ Using convolutional neural networks for breast cancer diagnosing(КПІ ім. Ігоря Сікорського, 2019) Naderan, M.; Zaychenko, Yu.; Napoli, A.Документ Відкритий доступ Исследование двойственной задачи оптимизации инвестиционного портфеля в нечетких условиях(Політехніка, 2011) Зайченко, Ю. П.; Ови Нафас Агаи Аг Гамиш; Зайченко, Юрій Петрович; Ові Нафас Агаі Аг Гаміш; Zaychenko, Yu.; Ovi Nafas Agai Ag Gamish