R. Tkachenko

发表

Self-organization Of Polynomial Regression Models In Neural Structures Of Geometric Transformations

R. Tkachenko, S. Demianchuk, 2014 .

Determination of the best microstructure and titanium alloy powders properties using neural network

A. Kovalchuk, V. Kulyk, A. Trostianchyn, 2018 .

Universal intraensemble method using nonlinear AI techniques for regression modeling of small medical data sets

R. Tkachenko, I. Izonin, 2022, Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data.

The Accelerated Method of Filling Gaps in Data Using a Linear SGTM Neural-Like Structure

R. Tkachenko, V. Pohrebennyk, Oleksandra Mishchuk, 2019 .

An Extended-Input GRNN and its Application

Natalia Kryvinska, Ivan Izonin, Khrystyna Zub, 2019, EUSPN/ICTH.

Stacking-based GRNN-SGTM Ensemble Model for Prediction Tasks

P. Tkachenko, R. Tkachenko, I. Dronyuk, 2020, 2020 International Conference on Decision Aid Sciences and Application (DASA).

Model and Principles for the Implementation of Neural-Like Structures Based on Geometric Data Transformations

Ivan Izonin, Roman Tkachenko, R. Tkachenko, 2018 .

Smart Web Service of Ti-Based Alloy’s Quality Evaluation for Medical Implants Manufacturing

N. Shakhovska, R. Tkachenko, Z. Duriagina, 2022, Applied Sciences.

Development of machine learning method of titanium alloy properties identification in additive technologies

Ivan Izonin, Roman Tkachenko, Z. A. Duriagina, 2018, Eastern-European Journal of Enterprise Technologies.

Boosting-based model for solving Sm-Co alloy’s maximum energy product prediction task

V. Kulyk, R. Tkachenko, Z. Duriagina, 2022, Archives of Materials Science and Engineering.

Protection of railway infrastructure objects against electrical corrosion

R. Tkachenko, L. Trykoz, S. Kamchatnaya, 2021, Anti-Corrosion Methods and Materials.

Sm-Co ALLOYS COERCIVITY PREDICTION USING STACKING HETEROGENEOUS ENSEMBLE MODEL

R. Tkachenko, Z. Duriagina, I. Izonin, 2021, Acta Metallurgica Slovaca.

Alloys selection based on the supervised learning technique for design of biocompatible medical materials

V. Kulyk, T.L. Tepla, I.V. Izonin, 2018, Archives of Materials Science and Engineering.

An Integral Software Solution of the SGTM Neural-Like Structures Implementation for Solving Different Data Mining Tasks

R. Tkachenko, 2021, Lecture Notes in Computational Intelligence and Decision Making.

Neuro-Fuzzy Diagnostics Systems Based on SGTM Neural-Like Structure and T-Controller

P. Tkachenko, R. Tkachenko, I. Izonin, 2021, Lecture Notes in Computational Intelligence and Decision Making.

The Additive Input-Doubling Method Based on the SVR with Nonlinear Kernels: Small Data Approach

Ivan Izonin, Nataliya Shakhovska, Nataliia Lotoshynska, 2021, Symmetry.

The Combined Use of the Wiener Polynomial and SVM for Material Classification Task in Medical Implants Production

Ivan Izonin, Nataliia Lotoshynska, Roman Tkachenko, 2018, International Journal of Intelligent Systems and Applications.

Imbalance Data Classification via Neural-Like Structures of Geometric Transformations Model: Local and Global Approaches

Bohdana Havrysh, Ivan Izonin, Yurii Tsymbal, 2018 .

An approach towards missing data management using improved GRNN-SGTM ensemble method

Ivan Izonin, Volodymyr Verhun, Khrystyna Zub, 2020 .

PNN-SVM Approach of Ti-Based Powder’s Properties Evaluation for Biomedical Implants Production

M. Greguš, N. Shakhovska, R. Tkachenko, 2022, Computers, Materials & Continua.

Hybrid Classifier via PNN-based Dimensionality Reduction Approach for Biomedical Engineering Task

Ivan Izonin, Roman Tkachenko, Michal Gregus, 2021, FNC/MobiSPC.

A Two-Step Data Normalization Approach for Improving Classification Accuracy in the Medical Diagnosis Domain

Krishnavir Singh, N. Shakhovska, R. Tkachenko, 2022, Mathematics.

An Approach towards Increasing Prediction Accuracy for the Recovery of Missing IoT Data based on the GRNN-SGTM Ensemble †

Ivan Izonin, Ivanna Dronyuk, Khrystyna Zub, 2020, Sensors.

A Non-Iterative Neural-Like Framework for Missing Data Imputation

Natalia Kryvinska, Ivan Izonin, Roman Tkachenko, 2019, Procedia Computer Science.

Hardware Components for Nonlinear Neuro-like Data Protection in Mobile Smart Systems

R. Tkachenko, V. Rabyk, I. Tsmots, 2022, 2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT).

Experimental Evaluation of the Effectiveness of ANN-based Numerical Data Augmentation Methods for Diagnostics Tasks

Ivan Izonin, Anatoliy Batyuk, Roman Tkachenko, 2021, IDDM.

Predictive modeling based on small data in clinical medicine: RBF-based additive input-doubling method.

P. Tkachenko, M. Greguš, R. Tkachenko, 2021, Mathematical biosciences and engineering : MBE.

A GRNN-based Approach towards Prediction from Small Datasets in Medical Application

Ivan Izonin, Khrystyna Zub, Roman Tkachenko, 2021, ANT/EDI40.

Recovery of Missing Sensor Data with GRNN-based Cascade Scheme

Ivan Izonin, Ivanna Dronyuk, Roman Tkachenko, 2020, International Journal of Sensors, Wireless Communications and Control.

Committee of the SGTM Neural-Like Structures with Extended Inputs for Predictive Analytics in Insurance

Ivan Izonin, Ivanna Dronyuk, Roman Tkachenko, 2019, Innovate-Data.

SGD-Based Wiener Polynomial Approximation for Missing Data Recovery in Air Pollution Monitoring Dataset

Ivan Izonin, Roman Tkachenko, Oleksandra Mishchuk, 2019, IWANN.

Missing Data Imputation Through SGTM Neural-Like Structure for Environmental Monitoring Tasks

Ivan Izonin, Roman Tkachenko, Oleksandra Mishchuk, 2019, Advances in Computer Science for Engineering and Education II.

PREDICTION OF HARDNESS, FLEXURAL STRENGTH, AND FRACTURE TOUGHNESS OF ZRO2 BASED CERAMICS USING ENSEMBLE LEARNING ALGORITHMS

R. Tkachenko, B. Vasyliv, Z. Duriagina, 2023, Acta Metallurgica Slovaca.

An Approach towards Missing Data Recovery within IoT Smart System

Ivan Izonin, Khrystyna Zub, Roman Tkachenko, 2019, Procedia Computer Science.

Learning-based image super-resolution using weight coefficients of synaptic connections

Ivan Izonin, Dmytro Peleshko, Taras Rak, 2015, 2015 Xth International Scientific and Technical Conference "Computer Sciences and Information Technologies" (CSIT).

Development of the Non-Iterative Supervised Learning Predictor Based on the Ito Decomposition and SGTM Neural-Like Structure for Managing Medical Insurance Costs

Ivan Izonin, Nataliia Lotoshynska, Roman Tkachenko, 2018, Data.

Piecewise-linear Approach for Medical Insurance Costs Prediction using SGTM Neural-Like Structure

Natalia Kryvinska, Ivan Izonin, Nataliia Lotoshynska, 2018, IDDM.

Input Doubling Method based on SVR with RBF kernel in Clinical Practice: Focus on Small Data

Ivan Izonin, Nataliia Lotoshynska, Khrystyna Zub, 2021, ANT/EDI40.

SGD-Based Cascade Scheme for Higher Degrees Wiener Polynomial Approximation of Large Biomedical Datasets

Shishir K. Shandilya, R. Tkachenko, I. Izonin, 2022, Mach. Learn. Knowl. Extr..

A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis

L. Rutkowski, R. Tkachenko, I. Izonin, 2023, Mathematical Biosciences and Engineering.

Classification of Imbalanced Classes Using the Committee of Neural Networks

Roman Tkachenko, Anastasiya Doroshenko, R. Tkachenko, 2018, 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT).

GRNN Approach Towards Missing Data Recovery Between IoT Systems

Natalia Kryvinska, Ivan Izonin, Khrystyna Zub, 2019, INCoS.

Recovery of Incomplete IoT Sensed Data using High-Performance Extended-Input Neural-Like Structure

Natalia Kryvinska, Ivan Izonin, Khrystyna Zub, 2019, EUSPN/ICTH.