Multiple linear regression based on coefficients identification using non-iterative SGTM neural-like structure

I Izonin, R Tkachenko, N Kryvinska… - … Work-Conference on …, 2019 - Springer
In the paper, a new method for solving the multiple linear regression task via a linear
polynomial as a constructive formula is proposed. It is based on the use of high-speed …

Using improved conditional generative adversarial networks to detect social bots on Twitter

B Wu, L Liu, Y Yang, K Zheng, X Wang - IEEE Access, 2020 - ieeexplore.ieee.org
The detection and removal of malicious social bots in social networks has become an area
of interest in industry and academia. The widely used bot detection method based on …

Stacking-based GRNN-SGTM ensemble model for prediction tasks

I Izonin, R Tkachenko, P Vitynskyi, K Zub… - … on decision aid …, 2020 - ieeexplore.ieee.org
An effective solution of the prediction tasks requires the high accuracy of the result with
minimal resource and time costs for the operation of the chosen algorithm. In cases when …

An integral software solution of the SGTM neural-like structures implementation for solving different Data Mining Tasks

R Tkachenko - Lecture Notes in Computational Intelligence and …, 2022 - Springer
The paper presents a developed software solution that implements a new learning model
and application of artificial neural networks, ie the Successive Geometric Transformations …

[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 …

Committee of the combined RBF-SGTM neural-like structures for prediction tasks

R Tkachenko, P Tkachenko, I Izonin, P Vitynskyi… - … Conference on Mobile …, 2019 - Springer
The paper describes the committee of non-iterative artificial intelligence tools for solving the
regression task. It is based on the use of high-speed neural-like structures with extended …

A multi-task convolutional neural network for lesion region segmentation and classification of non-small cell lung carcinoma

Z Wang, Y Xu, L Tian, Q Chi, F Zhao, R Xu, G Jin, Y Liu… - Diagnostics, 2022 - mdpi.com
Targeted therapy is an effective treatment for non-small cell lung cancer. Before treatment,
pathologists need to confirm tumor morphology and type, which is time-consuming and …

Committee of SGTM neural-like structures with RBF kernel for insurance cost prediction task

I Izonin, R Tkachenko, N Kryvinska… - 2019 IEEE 2nd …, 2019 - ieeexplore.ieee.org
A new method for constructing a committee based on the use of a set of SGTM Neural-Like
Structures with RBF kernel for solving regression tasks was developed. The use of the RBF …

Committee of the SGTM neural-like structures with extended inputs for predictive analytics in insurance

R Tkachenko, I Izonin, M Greguš ml… - … Conference on Big Data …, 2019 - Springer
In this paper, we propose a new committee-based method for insurance data analytics
problem. The main idea of the method is to increase the prediction task's accuracy. The …

[PDF][PDF] Application of Global Optimization Methods to Increase the Accuracy of Classification in the Data Mining Tasks.

A Doroshenko, D Luengo, S Subbotin - CMIS, 2019 - ceur-ws.org
The article describes the solving of data mining task using neural-like structures of
Successive Geometric Transformations Model (NLS SGTM). The main problems of this task …