Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Dmytro Peleshko"'
Autor:
Alexander Vlasenko, Nataliia Vlasenko, Olena Vynokurova, Yevgeniy Bodyanskiy, Dmytro Peleshko
Publikováno v:
Data, Vol 4, Iss 3, p 126 (2019)
Neuro-fuzzy models have a proven record of successful application in finance. Forecasting future values is a crucial element of successful decision making in trading. In this paper, a novel ensemble neuro-fuzzy model is proposed to overcome limitatio
Externí odkaz:
https://doaj.org/article/4f7a7aa194374b2ab2f8258b8976fa4d
Publikováno v:
Data, Vol 3, Iss 4, p 62 (2018)
Time series forecasting can be a complicated problem when the underlying process shows high degree of complex nonlinear behavior. In some domains, such as financial data, processing related time-series jointly can have significant benefits. This pape
Externí odkaz:
https://doaj.org/article/070c8db4eceb42c29042e1011aa092f7
Autor:
Olena Vynokurova, Dmytro Peleshko
Publikováno v:
2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP).
The Hybrid Multidimensional Deep Convolutional Neural Network (HMDCNN) topology for the multimodal recognition of the speech, the face, the lips, and human gestures behavior is proposed. In this case a hybridization is understood to be compatible use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3923b947eafc62fb04c1e09b98e8792a
https://doi.org/10.1109/dsmp47368.2020.9204215
https://doi.org/10.1109/dsmp47368.2020.9204215
Publikováno v:
2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP).
Time series in finance are distinguished by their highly complex nonlinear dynamics, which makes them hard to analyze and predict. This paper proposes a novel model based on combination of the empirical mode decomposition and multidimensional Gaussia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3dac4886e7afd245c457062a84ba005
https://doi.org/10.1109/dsmp47368.2020.9204179
https://doi.org/10.1109/dsmp47368.2020.9204179
Autor:
Dmytro Peleshko, Vladislav Serzhantov, Oleksandr Bondarenko, Vadim Ilyasov, Olena Vynokurova, Marta Peleshko
Publikováno v:
2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP).
In parallel with technological development the problem of fraud detection is becoming more and more important. Increasing number of electronic transactions in various business environments, on the one hand, and software and technology development, on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f03ca678dca2b379f5746f2f79ad8c3
https://doi.org/10.1109/dsmp47368.2020.9204244
https://doi.org/10.1109/dsmp47368.2020.9204244
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030542146
ISDMCI
ISDMCI
The basis of any business is customer databases, which provide information on customer relations with the company. For example, in the field of banking services, the database stores information about the client, account number, data on financial tran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af0841bcdf71ed9f3a46ca24095f450f
https://doi.org/10.1007/978-3-030-54215-3_34
https://doi.org/10.1007/978-3-030-54215-3_34
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030616557
DSMP
DSMP
The Hybrid Deep Convolutional Neural Network with Multimodal Fusion (HDCNNMF) topology for the multimodal recognition of the speech, the face, the lips, and human gestures behavior is proposed. Conducted researches relate to improving the understandi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8af970a64438ac22e1361364ec060e9
https://doi.org/10.1007/978-3-030-61656-4_4
https://doi.org/10.1007/978-3-030-61656-4_4
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030616557
DSMP
DSMP
Time series arise in different fields of the economy and forecasting of them is important part of decision making. However, their intrinsic complexity and nonlinear behavior makes prediction in that field a challenging task. Hybrid artificial intelli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3253a1de4ca5bf424764b44e4bc6d1f3
https://doi.org/10.1007/978-3-030-61656-4_9
https://doi.org/10.1007/978-3-030-61656-4_9
Publikováno v:
Neurocomputing. 230:409-416
In the paper the multivariate adaptive hybrid neuro-fuzzy system is proposed that allows to process nonstationary information disturbed by noises in sequential mode and also has smaller number of tuned parameters comparatively with known neuro-fuzzy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::062bd715ce661e5cce05627c7bcd3cdd
https://doi.org/10.1016/j.neucom.2016.12.042
https://doi.org/10.1016/j.neucom.2016.12.042
Publikováno v:
International Journal of Intelligent Systems and Applications. 9:42-48
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2efdb819eae30ae7c13bfb38195d8bce
https://doi.org/10.5815/ijisa.2017.02.06
https://doi.org/10.5815/ijisa.2017.02.06