Výsledky vyhledávání
- 1.0575836 - ÚTIA 2024 RIV CZ eng J - Článek v odborném periodiku
Uglickich, Evženie - Nagy, Ivan
Using Poisson proximity-based weights for traffic flow state prediction.
Neural Network World. Roč. 33, č. 4 (2023), s. 291-315. ISSN 1210-0552
Grant CEP: GA MŠMT 8A21009
Institucionální podpora: RVO:67985556
Klíčová slova: traffic counts * traffic flow state * cluster prediction * Poisson mixture * recursive mixture estimation
Obor OECD: Statistics and probability
Impakt faktor: 0.8, rok: 2022
Způsob publikování: Open access
http://library.utia.cas.cz/separaty/2023/ZS/uglickich-0575836.pdf http://nnw.cz/doi/2023/NNW.2023.33.017.pdf
Trvalý link: https://hdl.handle.net/11104/0345847 - 2.0557467 - ÚTIA 2023 RIV CZ eng V - Výzkumná zpráva
Uglickich, Evženie - Nagy, Ivan
Recursive mixture estimation with univariate multimodal Poisson variable.
Prague: UTIA AV ČR, v. v. i.,, 2022. 14 s. Research Report, 2394.
Grant CEP: GA MŠMT(CZ) 8A19009
Klíčová slova: recursive mixture estimation * mixture of Poisson distributions * clustering and classification
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2022/ZS/uglickich-0557467.pdf
Trvalý link: http://hdl.handle.net/11104/0331506Název souboru Staženo Velikost Komentář Verze Přístup 0557467.pdf 1 686.8 KB Jiná povolen - 3.0544576 - ÚTIA 2022 RIV PT eng C - Konferenční příspěvek (zahraniční konf.)
Uglickich, Evženie - Nagy, Ivan - Petrouš, Matej
Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data.
Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics. Setúbal: Scitepress, 2021 - (Gusikhin, O.; Nijmeijer, H.; Madani, K.), s. 600-608. ISBN 978-989-758-522-7. ISSN 2184-2809.
[International Conference on Informatics in Control, Automation and Robotics 2021 /18./. Setúbal (online) (PT), 06.07.2021-08.07.2021]
Grant CEP: GA MŠMT(CZ) 8A19009
Institucionální podpora: RVO:67985556
Klíčová slova: Poisson Distribution Prediction * Discrete Data * Discretization * Mixture based Clustering * Bayesian Recursive Mixture Estimation
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2021/ZS/uglickich-0544576.pdf
Trvalý link: http://hdl.handle.net/11104/0321816 - 4.0507883 - ÚTIA 2020 RIV NL eng J - Článek v odborném periodiku
Suzdaleva, Evženie - Nagy, Ivan
Two-layer pointer model of driving style depending on the driving environment.
Transportation Research. Part B: Methodological. Roč. 128, č. 1 (2019), s. 254-270. ISSN 0191-2615. E-ISSN 1879-2367
Grant CEP: GA MŠMT(CZ) 8A17006
Institucionální podpora: RVO:67985556
Klíčová slova: driving style * driving environment * fuel consumption * two-layer pointer * recursive mixture estimation * mixture-based clustering
Obor OECD: Statistics and probability
Impakt faktor: 4.796, rok: 2019
Způsob publikování: Omezený přístup
http://library.utia.cas.cz/separaty/2019/ZS/suzdaleva-0507883.pdf https://www.sciencedirect.com/science/article/pii/S0191261519301559
Trvalý link: http://hdl.handle.net/11104/0298856 - 5.0504124 - ÚTIA 2021 RIV CH eng M - Část monografie knihy
Suzdaleva, Evženie - Nagy, Ivan
Practical Initialization of Recursive Mixture-Based Clustering for Non-negative Data.
Informatics in Control, Automation and Robotics. ICINCO 2017.. Cham: Springer, 2020 - (Gusikhin, O.; Madani, K.), s. 679-698. Lecture Notes in Electrical Engineering, 495. ISBN 978-3-030-11292-9
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: Mixture-based clustering * Recursive mixture estimation * Different components * Non-negative data * Bayesian estimation
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2019/ZS/suzdaleva-0504124.pdf
Trvalý link: http://hdl.handle.net/11104/0295982 - 6.0484197 - ÚTIA 2018 RIV CZ eng L4 - Software
Nagy, Ivan - Suzdaleva, Evženie - Pecherková, Pavla
Clustering and Classification Using Recursive Mixture Estimation. Software package.
Interní kód: 20180108T101918Z-001 ; 2018
Technické parametry: software package
Ekonomické parametry: The main contribution of the project was to propose and implement the algorithms for mixture-based clustering and classi cation for various combinations of components as well as pointer models in the programming free and open source environment Scilab (www.scilab.org)
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: software * mixture-based clustering * recursive mixture estimation
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0484197.pdf http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0484197.zip
Trvalý link: http://hdl.handle.net/11104/0279549 - 7.0482566 - ÚTIA 2018 RIV JP eng C - Konferenční příspěvek (zahraniční konf.)
Suzdaleva, Evgenia - Nagy, Ivan - Petrouš, Matej
Recursive Clustering Hematological Data Using Mixture of Exponential Components.
Proceedings of International Conference on Intelligent Informatics and BioMedical Sciences ICIIBMS 2017. Piscataway: IEEE, 2017, s. 63-70. ISBN 978-1-5090-6665-0.
[International Conference on Intelligent Informatics and BioMedical Sciences ICIIBMS 2017. Okinawa (JP), 24.11.2017-26.11.2017]
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: mixture-based clustering * recursive mixture estimation * exponential components
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0482566.pdf
Trvalý link: http://hdl.handle.net/11104/0278141 - 8.0481220 - ÚTIA 2019 RIV NL eng J - Článek v odborném periodiku
Suzdaleva, Evgenia - Nagy, Ivan
An online estimation of driving style using data-dependent pointer model.
Transportation Research. Part C: Emerging Technologies. Roč. 86, č. 1 (2018), s. 23-36. ISSN 0968-090X. E-ISSN 1879-2359
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: driving style * fuel consumption * mixture-based clustering * data-dependent pointer * recursive mixture estimation
Obor OECD: Statistics and probability
Impakt faktor: 5.775, rok: 2018
http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0481220.pdf
Trvalý link: http://hdl.handle.net/11104/0277004 - 9.0477300 - ÚTIA 2018 RIV CH eng B - Monografie kniha jako celek
Nagy, Ivan - Suzdaleva, Evgenia
Algorithms and Programs of Dynamic Mixture Estimation. Unified Approach to Different Types of Components.
Cham: Springer, 2017. 113 s. SpringerBriefs in Statistics. ISBN 978-3-319-64670-1
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: dynamic mixture * recursive mixture estimation * algorithms and programs
Obor OECD: Statistics and probability
https://link.springer.com/book/10.1007/978-3-319-64671-8
Trvalý link: http://hdl.handle.net/11104/0274040 - 10.0476595 - ÚTIA 2018 RIV ES eng C - Konferenční příspěvek (zahraniční konf.)
Suzdaleva, Evgenia - Nagy, Ivan - Pecherková, Pavla - Likhonina, Raissa
Initialization of Recursive Mixture-based Clustering with Uniform Components.
Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017). Setúbal: SCITEPRESS, 2017, s. 449-458. ISBN 978-989-758-263-9.
[The 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017). Madrid (ES), 26.07.2017-28.07.2017]
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: Mixture-based Clustering * Recursive Mixture Estimation * Uniform Components
Obor OECD: Statistics and probability
http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0476595.pdf
Trvalý link: http://hdl.handle.net/11104/0273534