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Singh, Shivangi; Böhm, Johannes; Krásná, Hana; Böhm, Sigrid; Balasubramanian, Nagarajan; Dikshit, Onkar (2026) Machine learning-based modelling of VLBI station heights using meteorological and land surface state variables. Journal of Geodesy, 100 (5). doi:10.1007/s00190-026-02058-5

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Reference TypeJournal (article/letter/editorial)
TitleMachine learning-based modelling of VLBI station heights using meteorological and land surface state variables
JournalJournal of Geodesy
AuthorsSingh, ShivangiAuthor
Böhm, JohannesAuthor
Krásná, HanaAuthor
Böhm, SigridAuthor
Balasubramanian, NagarajanAuthor
Dikshit, OnkarAuthor
Year2026 (May)Volume100
Issue5
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s00190-026-02058-5Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID20021535Long-form Identifiermindat:1:5:20021535:2
GUID0
Full ReferenceSingh, Shivangi; Böhm, Johannes; Krásná, Hana; Böhm, Sigrid; Balasubramanian, Nagarajan; Dikshit, Onkar (2026) Machine learning-based modelling of VLBI station heights using meteorological and land surface state variables. Journal of Geodesy, 100 (5). doi:10.1007/s00190-026-02058-5
Plain TextSingh, Shivangi; Böhm, Johannes; Krásná, Hana; Böhm, Sigrid; Balasubramanian, Nagarajan; Dikshit, Onkar (2026) Machine learning-based modelling of VLBI station heights using meteorological and land surface state variables. Journal of Geodesy, 100 (5). doi:10.1007/s00190-026-02058-5
In(2026, May) Journal of Geodesy Vol. 100 (5). Springer Science and Business Media LLC

References Listed

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Not Yet Imported: - journal-article : 10.1088/1538-3873/aaa22b

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Not Yet Imported: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - proceedings-article : 10.1145/2939672.2939785

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Çökerim K, Dobslaw H, Balidakis K, Jensen L, Peña C, Bedford J (2025) Modeling non-tidal surface fluid loading signatures in global vertical GNSS displacements with a deep learning framework. Authorea Preprints. https://doi.org/10.22541/essoar.172641527.77043060/v2
Crocetti L, Schartner M, Schneider R, Schindler K, Soja B (2025) Correction models for GNSS displacements in Europe based on environmental Variables and XGBoost. Authorea Preprints. https://doi.org/10.22541/essoar.175766821.13490649/v1
Not Yet Imported: - journal-article : 10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2

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Geron A (2019) Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow (2nd ed.). O’Reilly Media
Not Yet Imported: - journal-article : 10.1023/A:1012487302797

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Not Yet Imported: - book : 10.1007/978-1-4614-6849-3

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9781461468486
Lundberg SM, Lee S-I (2017) A Unified approach to interpreting model predictions. Advances in neural information processing systems, 30. https://doi.org/10.48550/arXiv.1705.07874
Petit G, Luzum B (2010) IERS Conventions 2010 IERS Technical Note No. 36, v 1.3.0. Tech. rep. International Earth rotation and reference systems service, Frankfurt am Main, Germany
Not Yet Imported: - book-chapter : 10.1007/1345_2015_218

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9783319456287
Not Yet Imported: - book : 10.1007/978-3-642-02687-4

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9783642026867
Not Yet Imported: - book-chapter : 10.1007/1345_2015_214

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Not Yet Imported: International Association of Geodesy Symposia - book-chapter : 10.1007/978-3-642-18861-9_15

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9783642623295
Singh S, Böhm J, Krásná H, Balasubramanian N, Dikshit O (2024) Geophysical loading correction comparison and assessment in VLBI analysis. In International Association of Geodesy Symposia. Springer. https://doi.org/10.1007/1345_2024_257
Not Yet Imported: - book : 10.1007/978-3-642-36932-2

If you would like this item imported into the Digital Library, please contact us quoting Book ID 9783642369315


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