Optimized filling of a given cuboid with spherical powders for additive manufacturing

Z Duriagina, I Lemishka, I Litvinchev… - Journal of the …, 2021‏ - Springer
In additive manufacturing (also known as 3D printing), a layer-by-layer buildup process is
used for manufacturing parts. Modern laser 3D printers can work with various materials …

[PDF][PDF] Piecewise-linear Approach for Medical Insurance Costs Prediction using SGTM Neural-Like Structure.

R Tkachenko, I Izonin, N Kryvinska, V Chopyak… - IDDM, 2018‏ - ceur-ws.org
The article proposes a new insurance medical cost prediction method. It is based on the
piecewise-linear approach using the SGTM neural-like structure. Piecewise-linear approach …

Recovery of incomplete IoT sensed data using high-performance extended-input neural-like structure

I Izonin, R Tkachenko, N Kryvinska, K Zub… - Procedia Computer …, 2019‏ - Elsevier
The task of the recovery of incomplete IoT sensed data is considered. A high-performance
extended-input neural network, which is constructed using a non-iterative neural-like …

On the computational complexity of learning bithreshold neural units and networks

V Kotsovsky, F Geche, A Batyuk - … Decision Making: Proceedings of the XV …, 2020‏ - Springer
We study the questions concerning the properties and capabilities of computational
bithreshold real-weighted neural-like units. We give and justify the two sufficient conditions …

Hybridization of the SGTM neural-like structure through inputs polynomial extension

P Vitynskyi, R Tkachenko, I Izonin… - 2018 IEEE Second …, 2018‏ - ieeexplore.ieee.org
In this paper, a new approach for increasing the approximation accuracy with the use of
computational intelligence tools is described. It is based on the compatible use of the neural …

New approaches in the learning of complex-valued neural networks

V Kotsovsky, A Batyuk… - 2020 IEEE Third …, 2020‏ - ieeexplore.ieee.org
We consider neural networks with complex weights and continuous activation functions. The
complex generalization of the backpropagation learning algorithm is studied in the paper …

On-line relaxation versus off-line spectral algorithm in the learning of polynomial neural units

V Kotsovsky, A Batyuk - International Conference on Data Stream Mining …, 2020‏ - Springer
The problem of the learning of polynomial threshold units over a fixed set of polynomials is
treated in the paper. We consider two approaches in the supervised learning: off-line …

Realization of RSA cryptographic algorithm based on vector-module method of modular exponention

IZ Yakymenko, MM Kasianchuk… - … on Advanced Trends …, 2018‏ - ieeexplore.ieee.org
The improvement of the implementation of the RSA cryptographic algorithm for
encrypting/decoding information flows based on the use of the vector-modular method of …

Bithreshold neural network classifier

V Kotsovsky, F Geche, A Batyuk - 2020 IEEE 15th international …, 2020‏ - ieeexplore.ieee.org
The fully connected 2-layer feedforward network architecture with the hidden layer
consisting of bithreshold neurons is considered in the paper. We design the neural network …

Neural controller for smart house security subsystem

V Teslyuk, P Denysyuk, N Kryvinska… - Procedia Computer …, 2019‏ - Elsevier
Abstract The Smart House security subsystem is presented in the paper. The subsystem is
based on neural controller that uses an artificial neural network of a multilayer perceptron …