Tomas Ruzgas

515 total citations
28 papers, 374 citations indexed

About

Tomas Ruzgas is a scholar working on Artificial Intelligence, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Tomas Ruzgas has authored 28 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 7 papers in Economics and Econometrics and 6 papers in Statistics and Probability. Recurrent topics in Tomas Ruzgas's work include Bayesian Methods and Mixture Models (6 papers), Advanced Statistical Methods and Models (5 papers) and Municipal Solid Waste Management (4 papers). Tomas Ruzgas is often cited by papers focused on Bayesian Methods and Mixture Models (6 papers), Advanced Statistical Methods and Models (5 papers) and Municipal Solid Waste Management (4 papers). Tomas Ruzgas collaborates with scholars based in Lithuania, Bulgaria and Russia. Tomas Ruzgas's co-authors include Гінтарас Денафас, Dainius Martuzevičius, Viktoras Račys, Christian Ludwig, Alexander Chusov, Daimantas Milonas, Mindaugas Jievaltas, Steven Joniau, Jurgita Bruneckienė and Renaldas Raišutis and has published in prestigious journals such as SHILAP Revista de lepidopterología, Resources Conservation and Recycling and Cancers.

In The Last Decade

Tomas Ruzgas

27 papers receiving 361 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomas Ruzgas Lithuania 9 201 124 40 34 30 28 374
Lili Qu China 9 136 0.7× 31 0.3× 65 1.6× 13 0.4× 39 1.3× 37 406
Óscar C. Vásquez Chile 10 139 0.7× 44 0.4× 45 1.1× 28 0.8× 22 0.7× 49 441
Elham Shadkam Iran 12 24 0.1× 29 0.2× 12 0.3× 53 1.6× 113 3.8× 40 385
Nur Ayvaz‐Çavdaroğlu Türkiye 7 158 0.8× 67 0.5× 62 1.6× 42 1.2× 74 2.5× 12 323
Razieh Rahimi Iran 6 97 0.5× 27 0.2× 70 1.8× 23 0.7× 135 4.5× 14 342
Xiang Cai China 7 141 0.7× 21 0.2× 35 0.9× 36 1.1× 8 0.3× 18 341
Hamid Ghaderi Iran 9 49 0.2× 11 0.1× 25 0.6× 27 0.8× 95 3.2× 26 606
Fanshun Zhang China 6 53 0.3× 53 0.4× 29 0.7× 9 0.3× 21 0.7× 17 295
Alireza Gharehbaghi Iran 7 25 0.1× 27 0.2× 25 0.6× 26 0.8× 52 1.7× 7 314
M. Paruccini Italy 9 124 0.6× 20 0.2× 49 1.2× 34 1.0× 77 2.6× 10 339

Countries citing papers authored by Tomas Ruzgas

Since Specialization
Citations

This map shows the geographic impact of Tomas Ruzgas'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 Tomas Ruzgas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomas Ruzgas more than expected).

Fields of papers citing papers by Tomas Ruzgas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tomas Ruzgas. 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 Tomas Ruzgas. The network helps show where Tomas Ruzgas may publish in the future.

Co-authorship network of co-authors of Tomas Ruzgas

This figure shows the co-authorship network connecting the top 25 collaborators of Tomas Ruzgas. A scholar is included among the top collaborators of Tomas Ruzgas 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 Tomas Ruzgas. Tomas Ruzgas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ruzgas, Tomas, et al.. (2024). Solving Linear and Nonlinear Delayed Differential Equations Using the Lambert W Function for Economic and Biological Problems. Mathematics. 12(17). 2760–2760. 3 indexed citations
2.
Ruzgas, Tomas, et al.. (2023). Reduced Clustering Method Based on the Inversion Formula Density Estimation. Mathematics. 11(3). 661–661. 4 indexed citations
3.
Ruzgas, Tomas, et al.. (2023). Tax Fraud Reduction Using Analytics in an East European Country. Axioms. 12(3). 288–288. 4 indexed citations
4.
Ruzgas, Tomas, et al.. (2023). Research of nonparametric density estimation algorithms by applying clustering methods. SHILAP Revista de lepidopterología. 46. 273–279. 1 indexed citations
5.
Pilinkienė, Vaida, et al.. (2022). Evaluation of News Sentiment in Economic Activity Forecasting. SHILAP Revista de lepidopterología. 7–7. 1 indexed citations
6.
Ruzgas, Tomas, et al.. (2022). A New Clustering Method Based on the Inversion Formula. Mathematics. 10(15). 2559–2559. 8 indexed citations
7.
Pilinkienė, Vaida, et al.. (2022). Economic Activity Forecasting Based on the Sentiment Analysis of News. Mathematics. 10(19). 3461–3461. 5 indexed citations
8.
9.
Ruzgas, Tomas, et al.. (2022). Data clustering and its applications in medicine. New Trends in Mathematical Science. 10(ISAME2022-Proceedings). 67–70. 2 indexed citations
10.
Ruzgas, Tomas, et al.. (2021). Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model. Mathematics. 9(21). 2717–2717. 7 indexed citations
11.
Milonas, Daimantas, et al.. (2021). The Significance of Prostate Specific Antigen Persistence in Prostate Cancer Risk Groups on Long-Term Oncological Outcomes. Cancers. 13(10). 2453–2453. 12 indexed citations
12.
13.
Keršienė, Milda, et al.. (2019). Composition and Processing Characteristics of Milk from Lithuanian Black and White Cows. Journal of food and nutrition research. 7(2). 114–121. 1 indexed citations
14.
Ruzgas, Tomas, et al.. (2018). Application of automatic statistical post-processing method for analysis of ultrasonic and digital dermatoscopy images. Libyan Journal of Medicine. 13(1). 1479600–1479600. 3 indexed citations
15.
Ruzgas, Tomas, et al.. (2016). Business Intelligence for Big Data Analytics. International Journal of Computer Applications Technology and Research. 6(1). 1–8. 4 indexed citations
16.
Ruzgas, Tomas, et al.. (2016). Forecasting medical waste generation using short and extra short datasets: Case study of Lithuania. Waste Management & Research The Journal for a Sustainable Circular Economy. 34(4). 378–387. 20 indexed citations
17.
Денафас, Гінтарас, et al.. (2016). FORECASTING HAZARDOUS WASTE GENERATION USING SHORT DATA SETS: CASE STUDY OF LITHUANIA / PAVOJINGŲJŲ ATLIEKŲ SUSIDARYMO PROGNOZAVIMAS NAUDOJANT TRUMPAS DUOMENŲ IMTIS: LIETUVOS ATVEJIS. SHILAP Revista de lepidopterología. 8(4). 357–364. 3 indexed citations
18.
Ruzgas, Tomas, et al.. (2016). Big Data Mining and Knowledge Discovery. 9. 5–5. 2 indexed citations
19.
Ruzgas, Tomas, et al.. (2011). Application and evaluation of forecasting methods for municipal solid waste generation in an eastern-European city. Waste Management & Research The Journal for a Sustainable Circular Economy. 30(1). 89–98. 85 indexed citations
20.
Ruzgas, Tomas, et al.. (2004). The projection-based multivariate density estimation. Acta et Commentationes Universitatis Tartuensis de Mathematica. 8. 135–141. 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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