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Volodymyr Lytvynenko
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- affiliation: Kherson National Technical University, Ukraine
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2020 – today
- 2024
- [c58]Volodymyr Lytvynenko, Oleksandr Naumov, Mariia Voronenko, Olha Naumov, Iryna Lurie, Petro Radovenchuk:
Application of Mutual Information Estimation Methods for Feature Selection in Regression Problems of Aviation Traffic Forecasting. ACIT 2024: 784-789 - [c57]Volodymyr Lytvynenko, Victor Sineglazov, Kirill Riazanovskiy, Olena Chumachenko:
Semi-supervised learning for medical images segmentation using 4D atlas priors. CIAW 2024: 187-198 - [c56]Svitlana Havenko, Marta Labetska, Mykola Havenko, Valeriy Zhydetskyy, Volodymyr Lytvynenko:
Diagnostics and assessment of imprint quality using pattern recognition methods and digital photography for image processing. ICyberPhyS 2024: 142-152 - [c55]Victor Sineglazov, Mykhailo Savchenko
, Volodymyr Lytvynenko:
Efficient Small and Overlapping Target Detection in Underwater Images. ProfIT AI 2024: 16-29 - [c54]Viktor Sineglazov, Kyrylo Lesohorskyi, Volodymyr Lytvynenko:
Intelligent Hyperspectral Image Processing for Landmine Detection and Classification. ProfIT AI 2024: 40-51 - 2023
- [c53]Mariia Voronenko, Elizaveta Mikhailova, Nataliia Savina, Iryna Lurie, Volodymyr Lytvynenko:
A Bayesian Network Approach to Measure the Impact of Factors Characterizing the State of Educational Institutions on the Gross Domestic Product. ACIT 2023: 316-320 - [c52]Volodymyr Mayik, Lyudmyla Mayik, Kseniya Bazylyuk, Myroslava Dubnevych, Volodymyr Lytvynenko:
Modeling of the Braille Font Elements Creation Process Using Regression Analysis. IntelITSIS 2023: 332-342 - [c51]Serge Olszewski, Iryna Lurie, Volodymyr Lytvynenko, Violetta Demchenko, Mariia Voronenko, Natalia Kornilovska, Oleg Boskin:
Regression Modeling for Monitoring Organochlorine Pesticide Residues. MoMLeT+DS 2023: 204-218 - [c50]Malgorzata Szatkowska, Waldemar Wójcik, Wojciech Legiec, Iryna Lurie, Serge Olszewski, Volodymyr Lytvynenko, Mariia Voronenko:
Novel Methodology for Detecting Effective Features in Patients with Multiple Myeloma. MoMLeT+DS 2023: 582-609 - [e11]Stefan Wolfgang Pickl, Volodymyr Lytvynenko, Maryna Zharikova, Volodymyr Sherstjuk:
Proceedings of the 3rd International Workshop on Computational & Information Technologies for Risk-Informed Systems (CITRisk 2022) co-located with XXII International scientific and technical conference on Information Technologies in Education and Management (ІТЕМ 2022), Online Event, Neubiberg, Germany, January 12, 2023. CEUR Workshop Proceedings 3422, CEUR-WS.org 2023 [contents] - [e10]Sergii Babichev, Volodymyr Lytvynenko:
Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making - 2022 International Scientific Conference "Intellectual Systems of Decision-Making and Problems of Computational Intelligence", Proceedings, ISDMCI 2022, Rivne, Ukraine, June 14-16, 2022. Lecture Notes on Data Engineering and Communications Technologies 149, Springer 2023, ISBN 978-3-031-16202-2 [contents] - [e9]Michael Emmerich, Victoria Vysotska, Volodymyr Lytvynenko:
Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2023), Lviv, Ukraine, June 3, 2023. CEUR Workshop Proceedings 3426, CEUR-WS.org 2023 [contents] - 2022
- [e8]Stefan Wolfgang Pickl, Volodymyr Lytvynenko, Maryna Zharikova, Volodymyr Sherstjuk:
Proceedings of the 2nd International Workshop on Computational & Information Technologies for Risk-Informed Systems (CITRisk 2021) co-located with XXI International Conference on Information Technologies in Education and Management (ITEM 2021), Kherson, Ukraine, September 16-17, 2021. CEUR Workshop Proceedings 3101, CEUR-WS.org 2022 [contents] - [e7]Sergii Babichev
Lecture Notes in Computational Intelligence and Decision Making - 2021 International Scientific Conference "Intellectual Systems of Decision-making and Problems of Computational Intelligence", Proceedings, ISDMCI 2021, Zalizny Port, Kherson region, Ukraine, May 24-28, 2021. Lecture Notes on Data Engineering and Communications Technologies 77, Springer 2022, ISBN 978-3-030-82013-8 [contents] - 2021
- [c49]Sergiy Gnatyuk, Dinara Ospanova, Volodymyr Lytvynenko, Zhazira Amirgaliyeva, Nurali Nabot Shohiyon:
Assessing Risk of Enterprise Bankruptcy by Indicators of Financial and Economic Activity Using Bayesian Networks. CITRisk 2021: 39-50 - [c48]Iryna Fefelova, Andrey Fefelov, Oleksii K. Tyshchenko, Volodymyr Lytvynenko:
An Object-Oriented Architecture of the Information System for Solving the Protein Folding Problem. IDAACS 2021: 791-796 - [c47]Sergii Babichev, Mykhailo Yasinskyi, Lyudmyla Yasinska-Damri, Yurii Ratushniak, Volodymyr Lytvynenko:
Current State of the Problem of Gene Expression Data Processing and Extraction to Solve the Reverse Engineering Tasks in the Field of Bioinformatics. IntelITSIS 2021: 62-71 - [c46]Andrii Safonyk, Maksym Mishchanchuk, Volodymyr Lytvynenko:
Intelligent Information System for the Determination of Iron in Coagulants Based on a Neural Network. IntelITSIS 2021: 142-150 - [c45]Serge Olszewski
Streaming Algorithm to the Decomposition of a Polyatomic Molecules Mass Spectra on the Polychlorinated Biphenyls Molecule Example. ISDMCI 2021: 39-53 - [c44]Iryna Fefelova
Prediction of Native Protein Conformation by a Hybrid Algorithm of Clonal Selection and Differential Evolution. ISDMCI 2021: 314-330 - [c43]Oleksandr Naumov
Using Bayesian Networks to Estimate the Effectiveness of Innovative Projects. ISDMCI 2021: 729-743 - [c42]Volodymyr Lytvynenko, Mariia Voronenko, Olena Kovalchuk, Ulzhalgas Zhunissova, Luidmyla Lytvynenko:
Bayesian Methods Application for the Differential Diagnosis of the Chronic Obstructive Pulmonary Disease. MoMLeT+DS 2021: 851-862 - [e6]Stefan Wolfgang Pickl, Volodymyr Lytvynenko, Maryna Zharikova, Volodymyr Sherstjuk:
Proceedings of the 1st International Workshop on Computational & Information Technologies for Risk-Informed Systems (CITRisk 2020) co-located with XX International scientific and technical conference on Information Technologies in Education and Management (ІТЕМ 2020), Kherson, Ukraine, October 15-16, 2020. CEUR Workshop Proceedings 2805, CEUR-WS.org 2021 [contents] - [e5]Sergii Babichev, Volodymyr Lytvynenko, Waldemar Wójcik, Svetlana Vyshemyrskaya:
Lecture Notes in Computational Intelligence and Decision Making - Proceedings of the 2020 International Scientific Conference "Intellectual Systems of Decision-making and Problems of Computational Intelligence", ISDMCI 2020, Kherson, Ukraine, May 25-29, 2020. Advances in Intelligent Systems and Computing 1246, Springer 2021, ISBN 978-3-030-54214-6 [contents] - [e4]Michael Emmerich, Vasyl Lytvyn, Victoria Vysotska, Vitor Basto-Fernandes, Volodymyr Lytvynenko:
Modern Machine Learning Technologies and Data Science Workshop. Proc. 3rd International Workshop (MoMLeT&DS 2021). Volume I: Main Conference, Lviv-Shatsk, Ukraine, June 5-6, 2021. CEUR Workshop Proceedings 2917, CEUR-WS.org 2021 [contents] - 2020
- [c41]Mariia Voronenko, Oleksandr Naumov
Analysis of the Effectiveness of an Investment Project Using Statistical Bayesian Networks. ACIT 2020: 408-411 - [c40]Viktor Perederyi, Eugene Borchik, Volodymyr Lytvynenko, Oksana Ohnieva:
Information Technology for Performance Assessment of Complex Multilevel Systems in Managing Technogenic Objects. CITRisk 2020: 175-188 - [c39]Sergey I. Vyatkin, Olexandr Romanyuk, Sergii Pavlov, Pavlo Mykhaylov, Roman Chekhmestruk, Oksana Vodzinska, Olena Prozor, Volodymyr Lytvynenko:
Manipulating Function-Based Objects with Interactive Collision Risk Models. CITRisk 2020: 324-334 - [c38]Mariia Voronenko, Dmytro Nikytenko, Jan Krejci, Nataliia Savina, Volodymyr Lytvynenko:
Assessing the possibility of a country's economic growth using static bayesian network models. CMIS 2020: 462-473 - [c37]Volodymyr Lytvynenko, Dmytro Nikytenko, Mariia Voronenko, Jan Krejci, Natalia Savina:
Comparative Study of Noisy-MAX Nodes and General Nodes in Bayesian Network Models. COLINS 2020: 56-66 - [c36]Volodymyr Lytvynenko, Dmytro Nikytenko
Assessing the Possibility of a Country's Economic Growth Using Dynamic Bayesian Network Models. CSIT (1) 2020: 36-39 - [c35]Mariia Voronenko
Dynamic Bayesian Network Model of a Country's Economic Extension. CSIT 2020: 145-159 - [c34]Mariia Voronenko
Dynamic Bayesian Networks Application for Economy Competitiveness Situational Modelling. CSIT 2020: 210-224 - [c33]Serge Olszewski
Expansion of the Capabilities of Chromatography-Mass Spectrometry Due to the Numerical Decomposition of the Signal with the Mutual Superposition of Mass Spectra. DSMP (Selected Papers) 2020: 218-237 - [c32]Oleksii Ivanov, Liudmyla Koretska, Volodymyr Lytvynenko:
Intelligent Modeling of Unified Communications Systems Using Artificial Neural Networks (short paper). IntelITSIS 2020: 77-84 - [c31]Olexander Barmak, Iurii Krak, Eduard Manziuk, Volodymyr Lytvynenko, Oleg Kalyta:
Classification Technology Based on Hyperplanes for Visual Analytics with Implementations for Different Subject Areas. IntelITSIS 2020: 96-106 - [c30]Volodymyr Lytvynenko
Dynamic Bayesian Networks Application for Evaluating the Investment Projects Effectiveness. ISDMCI 2020: 315-330 - [c29]Iryna Lurie
Application of Inductive Bayesian Hierarchical Clustering Algorithm to Identify Brain Tumors. ISDMCI 2020: 567-584 - [c28]Iryna Lurie, Volodymyr Lytvynenko, Serge Olszewski, Mariia Voronenko, Alexander I. Kornelyuk, Ulzhalgas Zhunissova, Oleg Boskin:
The Use of Inductive Methods to Identify Subtypes of Glioblastomas in Gene Clustering. MoMLeT+DS 2020: 406-418 - [c27]Violetta Demchenko, Serge Olszewski, Mariia Voronenko, Eva Zaets, Nataliia Savina, Iryna Lurie, Volodymyr Lytvynenko:
Modeling and Predicting the Organochlorine Pesticides Concentration in the Child's Body Based on their Accumulation in the Mother's Body. MoMLeT+DS 2020: 419-432 - [e3]Volodymyr Lytvynenko, Sergii Babichev, Waldemar Wójcik, Olena Vynokurova, Svetlana Vyshemyrskaya, Svetlana Radetskaya:
Lecture Notes in Computational Intelligence and Decision Making - Proceedings of the 15th International Scientific Conference "Intellectual Systems of Decision Making and Problems of Computational Intelligence", ISDMCI 2019, Salisnyj Port, Ukraine, May 21-25, 2019. Advances in Intelligent Systems and Computing 1020, Springer 2020, ISBN 978-3-030-26473-4 [contents] - [e2]Michael Emmerich, Vasyl Lytvyn, Victoria Vysotska, Vitor Basto-Fernandes, Volodymyr Lytvynenko:
Proceedings of the 2nd International Workshop on Modern Machine Learning Technologies and Data Science (MoMLeT+DS 2020). Volume I: Main Conference, Lviv-Shatsk, Ukraine, June 2-3, 2020. CEUR Workshop Proceedings 2631, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [j1]Viktor Mashkov
Diagnosis of Intermittently Faulty Units at System Level. Data 4(1): 44 (2019) - [c26]Volodymyr Lytvynenko
Development, Validation and Testing of the Bayesian Network to Evaluate the National Law Enforcement Agencies' work. ACIT 2019: 252-256 - [c25]Andrii Fefelov, Volodymyr Lytvynenko, Ali Taif, Natalia Savina, Maria Voronenko, Irina Lurie, Oleg Boskin:
Hybrid Immune Algorithms in the Gene Regulatory Networks Reconstruction Problems. CMIS 2019: 193-210 - [c24]Irina Lurie, Andrii Podlevskyi, Natalia Savina, Maria Voronenko, Anna Pashnina, Volodymyr Lytvynenko:
Inductive Technology of the Objective Cauterization of Enterprise's Economic Indicators of Ukraine. CMIS 2019: 848-859 - [c23]Viktor Mashkov, Jirí Fiser, Volodymyr Lytvynenko, Maria Voronenko:
Evaluation of Testing Assignment for System Level Self-Diagnosis. CMIS 2019: 1004-1019 - [c22]Volodymyr Lytvynenko
The use of Bayesian methods in the task of localizing the narcotic substances distribution. CSIT (2) 2019: 60-63 - [c21]Volodymyr Lytvynenko
Dynamic Bayesian Networks in the Problem of Localizing the Narcotic Substances Distribution. CSIT 2019: 421-438 - [c20]Volodymyr Lytvynenko
Development, Validation and Testing of the Bayesian Network of Educational Institutions Financing. IDAACS 2019: 412-417 - [c19]Volodymyr Lytvynenko
Development of the Dynamic Bayesian Network to Evaluate the National Law Enforcement Agencies' Work. IDAACS 2019: 418-423 - [c18]Volodymyr Osypenko, Irina Lurie, Maryna Yakobchuk, Nataliia Savina
About Innovation-Investment Designing of Complex Systems by Inductive Technology of System Information-Analytical Research. IDAACS 2019: 424-430 - [c17]Oleksandr Murzenko, Serge Olszewski, Oleg Boskin, Irina Lurie, Nataliia Savina
Application of a Combined Approach for Predicting a Peptide-Protein Binding Affinity Using Regulatory Regression Methods with Advance Reduction of Features. IDAACS 2019: 431-435 - [c16]Volodymyr Lytvynenko, Mariia Voronenko, Serge Sitalo, Oleg Boskin, Iryna Lurie, Natalia Savina, Yaroslav Tanasiichuk, Nataliia Krugla:
Using a Bayesian Network to Assess the Atmospheric Pollution Influence on Immunological Parameters. IDDM 2019: 222-233 - [c15]Serge Olszewski
Some Features of the Numerical Deconvolution of Mixed Molecular Spectra. ISDMCI 2019: 20-34 - [c14]Volodymyr Lytvynenko
Hybrid Methods of GMDH-Neural Networks Synthesis and Training for Solving Problems of Time Series Forecasting. ISDMCI 2019: 513-531 - [c13]Iryna Fefelova
Protein Tertiary Structure Prediction with Hybrid Clonal Selection and Differential Evolution Algorithms. ISDMCI 2019: 673-688 - [c12]Volodymyr Lytvynenko, Natalia Savina, Jan Krejci, Mariia Voronenko, Maryna Yakobchuk, Olena Kryvoruchko:
Bayesian Networks' Development Based on Noisy-MAX Nodes for Modeling Investment Processes in Transport. MoMLeT 2019: 1-10 - [c11]Volodymyr Lytvynenko, Irina Lurie, Jan Krejci, Mariia Voronenko, Natalia Savina, Mohamed Ali Taif:
Two Step Density-Based Object-Inductive Clustering Algorithm. MoMLeT 2019: 117-135 - [e1]David Luengo, Sergey Subbotin, Peter Arras, Yevgeniy V. Bodyanskiy, Karsten Henke, Ivan Izonin, Vitaly G. Levashenko, Volodymyr Lytvynenko, Anzhelika Parkhomenko, Andreas Pester, Natalya Shakhovska, Alexei Sharpanskykh, Galyna Tabunshchyk, Carsten Wolff, Heinz-Dietrich Wuttke, Elena Zaitseva:
Proceedings of the Second International Workshop on Computer Modeling and Intelligent Systems (CMIS-2019), Zaporizhzhia, Ukraine, April 15-19, 2019. CEUR Workshop Proceedings 2353, CEUR-WS.org 2019 [contents] - 2018
- [c10]Iryna Lurie, Volodymyr Lytvynenko
The Use of Inductive Methods for Determination of the Binding Affinity of Interacting Biological Molecules. CSIT (1) 2018: 1-5 - [c9]Viktor Mashkov
Credibility of System Self-Checking When Tests are Performed Randomly. CSIT (1) 2018: 396-399 - [c8]Sergii Babichev
Information Technology of Gene Expression Profiles Processing for Purpose of Gene Regulatory Networks Reconstruction. DSMP 2018: 336-341 - [c7]Viktor Mashkov
Self-Diagnosis of the Systems with Intermittently Faulty Units. DSMP 2018: 411-414 - 2017
- [c6]Sergii Babichev
Objective Clustering Inductive Technology of Gene Expression Sequences Features. BDAS 2017: 359-372 - [c5]Sergii Babichev
Gene expression sequences clustering based on the internal and external clustering quality criteria. CSIT (1) 2017: 91-94 - [c4]Sergii Babichev
Implementation of the objective clustering inductive technology based on DBSCAN clustering algorithm. CSIT (1) 2017: 479-484 - [c3]Serhii Okrenets, Andrii Fefelov
Synthesis and learning of fuzzy neural networks for solving forecasting problems. IDAACS 2017: 1088-1093 - 2016
- [c2]Viktor Mashkov
Evaluation of testing assignment for system level self-diagnosis. DSMP 2016: 15-18 - [c1]Sergii Babichev
Inductive model of data clustering based on the agglomerative hierarchical algorithm. DSMP 2016: 19-22
Coauthor Index
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last updated on 2024-12-26 00:48 CET by the dblp team
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