Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Lyudmyla Kirichenko"'
Publikováno v:
Mathematics, Vol 12, Iss 19, p 3079 (2024)
This study explores the application of neural networks for anomaly detection in time series data exhibiting fractal properties, with a particular focus on changes in the Hurst exponent. The objective is to investigate whether changes in fractal prope
Externí odkaz:
https://doaj.org/article/08ac78cad56c46049ed70271009ebaa0
Autor:
Lyudmyla Kirichenko, Roman Lavrynenko
Publikováno v:
Fractal and Fractional, Vol 7, Iss 7, p 517 (2023)
This paper explores the capabilities of machine learning for the probabilistic forecasting of fractional Brownian motion (fBm). The focus is on predicting the probability of the value of an fBm time series exceeding a certain threshold after a specif
Externí odkaz:
https://doaj.org/article/57fe8511b1c04c4ba03c9171c3b01d3e
Publikováno v:
Кібербезпека: освіта, наука, техніка, Vol 3, Iss 11, Pp 183-194 (2021)
Виявлення аномалій є важливим завданням у багатьох сферах людського життя. Для виявлення аномалій використовується множина статистичн
Externí odkaz:
https://doaj.org/article/319c8f6c05e145028e82465a3dd801ac
Publikováno v:
Кібербезпека: освіта, наука, техніка, Vol 3, Iss 7, Pp 17-30 (2020)
У даній роботі розглянута проблема балансування навантаження в системах виявлення вторгнень. Проведено аналіз існуючих проблем баланс
Externí odkaz:
https://doaj.org/article/f118e1db43dc43d29ead84174d21948b
Publikováno v:
Computation, Vol 10, Iss 11, p 199 (2022)
Shoplifting is a major problem for shop owners and many other parties, including the police. Video surveillance generates huge amounts of information that staff cannot process in real time. In this article, the problem of detecting shoplifting in vid
Externí odkaz:
https://doaj.org/article/f6e5f33c6ba3429fa375bcf364f464c9
Publikováno v:
International Journal of Electronics and Telecommunications, Vol vol. 64, Iss No 1 (2018)
Externí odkaz:
https://doaj.org/article/3d9d145f47dd4b5182b0edc7c971b50d
Publikováno v:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, Vol 8, Iss 1 (2018)
W pracy przedstawiono uogólnione podejście do analizy fraktalnej samopodobnych procesów losowych przedstawianych w krótkich szeregach czasowych. Zaproponowano kilka etapów analizy fraktalnej. Wstępna analiza szeregów czasowych obejmuje elimina
Externí odkaz:
https://doaj.org/article/3dc61c2d4f254b60b805abd48486a5ed
Publikováno v:
Data, Vol 4, Iss 1, p 5 (2018)
The article presents a novel method of fractal time series classification by meta-algorithms based on decision trees. The classification objects are fractal time series. For modeling, binomial stochastic cascade processes are chosen. Each class that
Externí odkaz:
https://doaj.org/article/f17dafa3126d416b8c4bb3655bd39f4c
Publikováno v:
2017 14th International Conference The Experience of Designing and Application of CAD Systems in Microelectronics (CADSM), Lviv, 2017, pp. 260-264
The paper proposes a solution an actual scientific problem related to load balancing and efficient utilization of resources of the distributed system. The proposed method is based on calculation of load CPU, memory, and bandwidth by flows of differen
Externí odkaz:
http://arxiv.org/abs/1904.05218
Autor:
Lavrynenko, Lyudmyla Kirichenko, Roman
Publikováno v:
Fractal and Fractional; Volume 7; Issue 7; Pages: 517
This paper explores the capabilities of machine learning for the probabilistic forecasting of fractional Brownian motion (fBm). The focus is on predicting the probability of the value of an fBm time series exceeding a certain threshold after a specif