Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Olena Vynokurova"'
Publikováno v:
Annals of computer science and information systems, Vol 8, Pp 141-145 (2016)
Externí odkaz:
https://doaj.org/article/3ce4d1b34d4f4a6c8e5471c0ec840705
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
Publikováno v:
Information Technology and Management Science; Vol 21 (2018): Information Technology and Management Science; 24-28
Information Technology and Management Science
Information Technology and Management Science
In the paper 2D-neo-fuzzy neuron is presented. It is a generalization of the traditional NFN for data in matrix form. 2D-NFN is based on the matrix adaptive bilinear model with an additional fuzzification layer. It reduces the number of adjustable sy
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
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
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
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