Olena Vynokurova

528 total citations
37 papers, 330 citations indexed

About

Olena Vynokurova is a scholar working on Artificial Intelligence, Control and Systems Engineering and Food Science. According to data from OpenAlex, Olena Vynokurova has authored 37 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 13 papers in Control and Systems Engineering and 7 papers in Food Science. Recurrent topics in Olena Vynokurova's work include Neural Networks and Applications (25 papers), Fuzzy Logic and Control Systems (17 papers) and Advanced Scientific Research Methods (7 papers). Olena Vynokurova is often cited by papers focused on Neural Networks and Applications (25 papers), Fuzzy Logic and Control Systems (17 papers) and Advanced Scientific Research Methods (7 papers). Olena Vynokurova collaborates with scholars based in Ukraine and Poland. Olena Vynokurova's co-authors include Yevgeniy Bodyanskiy, Dmytro Peleshko, Ivan Izonin, Nataliia Lotoshynska and Vitaliy Kolodyazhniy and has published in prestigious journals such as SHILAP Revista de lepidopterología, Information Sciences and Neurocomputing.

In The Last Decade

Olena Vynokurova

34 papers receiving 302 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Olena Vynokurova Ukraine	12	186	94	54	49	37	37	330
Dmytro Peleshko Ukraine	12	115 0.6×	39 0.4×	70 1.3×	25 0.5×	125 3.4×	38	369
Oleksii K. Tyshchenko Ukraine	13	177 1.0×	60 0.6×	64 1.2×	8 0.2×	47 1.3×	31	318
Тамара Радівілова Ukraine	11	132 0.7×	75 0.8×	55 1.0×	8 0.2×	33 0.9×	48	330
Maciej Krawczak Poland	8	121 0.7×	33 0.4×	18 0.3×	120 2.4×	13 0.4×	38	283
Marek Kisiel‐Dorohinicki Poland	12	241 1.3×	37 0.4×	91 1.7×	32 0.7×	33 0.9×	69	452
Rosanna Verde Italy	11	213 1.1×	27 0.3×	34 0.6×	62 1.3×	58 1.6×	30	383
Juan Carlos Figueroa–García Colombia	13	174 0.9×	157 1.7×	20 0.4×	240 4.9×	20 0.5×	63	442
Malek Sarhani Morocco	9	99 0.5×	24 0.3×	17 0.3×	53 1.1×	18 0.5×	23	246
J. A. Moreno Spain	6	91 0.5×	37 0.4×	11 0.2×	39 0.8×	12 0.3×	13	392
Tuve Löfström Sweden	12	284 1.5×	49 0.5×	37 0.7×	18 0.4×	48 1.3×	56	467

Countries citing papers authored by Olena Vynokurova

Since Specialization

Citations

This map shows the geographic impact of Olena Vynokurova's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Olena Vynokurova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olena Vynokurova more than expected).

Fields of papers citing papers by Olena Vynokurova

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olena Vynokurova. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Olena Vynokurova. The network helps show where Olena Vynokurova may publish in the future.

Co-authorship network of co-authors of Olena Vynokurova

This figure shows the co-authorship network connecting the top 25 collaborators of Olena Vynokurova. A scholar is included among the top collaborators of Olena Vynokurova based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Olena Vynokurova. Olena Vynokurova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Vynokurova, Olena, et al.. (2020). Hybrid Machine Learning System for Solving Fraud Detection Tasks. 1–5. 17 indexed citations

Vynokurova, Olena, et al.. (2019). A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting. Data. 4(3). 126–126. 21 indexed citations

Vynokurova, Olena, et al.. (2018). A Novel Neuro-Fuzzy Model for Multivariate Time-Series Prediction. Data. 3(4). 62–62. 6 indexed citations

Vynokurova, Olena, et al.. (2018). Hybrid Multidimensional Wavelet-Neuro-System and its Learning Using Cross Entropy Cost Function in Pattern Recognition. 305–309. 4 indexed citations

Bodyanskiy, Yevgeniy, et al.. (2018). Hybrid fuzzy-clustering algorithm of unevenly and asynchronously spaced time series in computer engineering. 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET). 8. 930–935.

Vynokurova, Olena, et al.. (2018). A Hybrid Neuro-Fuzzy Model for Stock Market Time-Series Prediction. 352–355. 12 indexed citations

Bodyanskiy, Yevgeniy, et al.. (2018). The Autoencoder Based on Generalized Neo-Fuzzy Neuron and its Fast Learning for Deep Neural Networks. 3698. 113–118. 3 indexed citations

Bodyanskiy, Yevgeniy, et al.. (2018). Deep Evolving Stacking Convex Cascade Neo-Fuzzy Network and Its Rapid Learning. SHILAP Revista de lepidopterología. 15. 29–33.

Bodyanskiy, Yevgeniy, et al.. (2018). Adaptive wavelet diagnostic neuro-fuzzy network for biomedical tasks. 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET). 1. 711–715. 13 indexed citations

10.

Bodyanskiy, Yevgeniy, et al.. (2017). Neo-Fuzzy Encoder and Its Adaptive Learning for Big Data Processing. SHILAP Revista de lepidopterología. 20(1). 2 indexed citations

11.

Bodyanskiy, Yevgeniy, et al.. (2016). Hybrid Clustering-Classification Neural Network in the Medical Diagnostics of the Reactive Arthritis. International Journal of Intelligent Systems and Applications. 8(8). 1–9. 12 indexed citations

12.

Bodyanskiy, Yevgeniy, et al.. (2015). Hybrid generalized additive neuro-fuzzy system and its adaptive learning algorithms. 328–333. 10 indexed citations

13.

Bodyanskiy, Yevgeniy, et al.. (2015). Hybrid neuro-neo-fuzzy system and its adaptive learning algorithm. 111–114. 16 indexed citations

14.

Bodyanskiy, Yevgeniy, et al.. (2015). Hybrid Generalised Additive Type-2 Fuzzy-Wavelet-Neural Network in Dynamic Data Mining. SHILAP Revista de lepidopterología. 18(1). 1 indexed citations

15.

Bodyanskiy, Yevgeniy, et al.. (2014). Least Squares Support Vector Machine Based on Wavelet-Neuron/ Uz wavelet neironiem balstītā minimālo kvadrātu atbalsta vektoru mašīna/ Машина опорных векторов наименьших квадратов на основе вэйвлет-нейрона. SHILAP Revista de lepidopterología. 17(1). 1 indexed citations

16.

Bodyanskiy, Yevgeniy, et al.. (2013). Flexible Neo-fuzzy Neuron and Neuro-fuzzy Network for Monitoring Time Series Properties. RePEc: Research Papers in Economics. 16(1). 10 indexed citations

17.

Bodyanskiy, Yevgeniy & Olena Vynokurova. (2011). Hybrid Type-2 Wavelet-neuro-fuzzy Network for Prediction of Business Processes. 21. 9–21. 3 indexed citations

18.

Bodyanskiy, Yevgeniy, et al.. (2011). HYBRID CASCADE NEURAL NETWORK BASED ON WAVELET-NEURON. 4 indexed citations

19.

Bodyanskiy, Yevgeniy, et al.. (2008). MULTIALGEBRAIC SYSTEMS IN INFORMATION GRANULATION. 1 indexed citations

20.

Bodyanskiy, Yevgeniy, et al.. (2004). Learning wavelet neuron based on the RASP-function. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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