Zobrazeno 1 - 10
of 139
pro vyhledávání: '"Velichko, Andrei"'
Autor:
Velichko, Andrei S.
Publikováno v:
Известия Саратовского университета. Новая серия. Серия Математика. Механика. Информатика, Vol 23, Iss 3, Pp 411-417 (2023)
The paper deals with a problem of decision-making support for production location problem. The paper describes the mathematical model of production location. Minimization of total cost of delivery of raw materials to the place of production is used a
Externí odkaz:
https://doaj.org/article/384c5768038845a78da06de6a3e4b8d2
Autor:
Borisenkov, Mikhail, Velichko, Andrei, Belyaev, Maksim, Korzun, Dmitry, Tserne, Tatyana, Bakutova, Larisa, Gubin, Denis
This study investigates machine learning algorithms to identify objective features for diagnosing food addiction (FA) and assessing confirmed symptoms (SC). Data were collected from 81 participants (mean age: 21.5 years, range: 18-61 years, women: 77
Externí odkaz:
http://arxiv.org/abs/2409.00310
In this study a new method for analyzing synchronization in oscillator systems is proposed using the example of modeling the dynamics of a circuit of two resistively coupled pulse oscillators. The dynamic characteristic of synchronization is fuzzy en
Externí odkaz:
http://arxiv.org/abs/2406.12906
The study presents the concept of a computationally efficient machine learning (ML) model for diagnosing and monitoring Parkinson's disease (PD) in an Internet of Things (IoT) environment using rest-state EEG signals (rs-EEG). We computed different t
Externí odkaz:
http://arxiv.org/abs/2309.07134
This study proposes an enhancement to the existing method for detecting Solar Active Regions (ARs). Our technique tracks ARs using images from the Atmospheric Imaging Assembly (AIA) of NASA's Solar Dynamics Observatory (SDO). It involves a 2D circula
Externí odkaz:
http://arxiv.org/abs/2306.08270
Publikováno v:
Sensors 2023, 23, 7137
The study presents a bio-inspired chaos sensor model based on the perceptron neural network for the estimation of entropy of spike train in neurodynamic systems. After training, the sensor on perceptron, having 50 neurons in the hidden layer and 1 ne
Externí odkaz:
http://arxiv.org/abs/2306.01991
Publikováno v:
Algorithms 2023, 16, 255
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. However, for the effective separation of time series, new entropy estimatio
Externí odkaz:
http://arxiv.org/abs/2303.17995
Publikováno v:
Appl. Sci. 2022, 12, 12180
Early evaluation of patients who require special care and who have high death-expectancy in COVID-19, and the effective determination of relevant biomarkers on large sample-groups are important to reduce mortality. This study aimed to reveal the rout
Externí odkaz:
http://arxiv.org/abs/2210.12342
Publikováno v:
Remote Sens. 2022, 14, 5983
Approximation of entropies of various types using machine learning (ML) regression methods are shown for the first time. The ML models presented in this study define the complexity of the short time series by approximating dissimilar entropy techniqu
Externí odkaz:
http://arxiv.org/abs/2210.06901
Publikováno v:
Sensors 2022, 22, 7886
Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the p
Externí odkaz:
http://arxiv.org/abs/2209.03522