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Akademický článek

Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks

Autor: G. S. Nearing, D. Klotz, J. M. Frame, M. Gauch, O. Gilon, F. Kratzert, A. K. Sampson, G. Shalev, S. Nevo

Publikováno v: Hydrology and Earth System Sciences, Vol 26, Pp 5493-5513 (2022)

Ingesting near-real-time observation data is a critical component of many operational hydrological forecasting systems. In this paper, we compare two strategies for ingesting near-real-time streamflow observations into long short-term memory (LSTM) r

Externí odkaz: https://doaj.org/article/b85f88847fe5433c93431e7f7cad3a51

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Akademický článek

Deep learning rainfall–runoff predictions of extreme events

Autor: J. M. Frame, F. Kratzert, D. Klotz, M. Gauch, G. Shelev, O. Gilon, L. M. Qualls, H. V. Gupta, G. S. Nearing

Publikováno v: Hydrology and Earth System Sciences, Vol 26, Pp 3377-3392 (2022)

The most accurate rainfall–runoff predictions are currently based on deep learning. There is a concern among hydrologists that the predictive accuracy of data-driven models based on deep learning may not be reliable in extrapolation or for predicti

Externí odkaz: https://doaj.org/article/1ef8b1f9cdd0413c9f0aea6a8ad269f1

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Post‐Processing the National Water Model with Long Short‐Term Memory Networks for Streamflow Predictions and Model Diagnostics

Autor: Mashrekur Rahman, F. Salas, J. M. Frame, Frederik Kratzert, Austin Raney, Grey Nearing

Publikováno v: JAWRA Journal of the American Water Resources Association. 57:885-905

We build three Long Short-Term Memory (LSTM) daily streamflow prediction models (deep learning networks) for 531 basins across the contiguous United States (CONUS), and compare their performance: (1) a LSTM post-processor trained on the U.S. National

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bbc005495f39609594d74ce9d1a743c5
https://doi.org/10.1111/1752-1688.12964

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Schätzung der Verdunstung mithilfe von Machine- und Deep Learning-Methoden

Autor: Grey Nearing, Karsten Schulz, Claire Brenner, J. M. Frame

Publikováno v: Österreichische Wasser- und Abfallwirtschaft. 73:295-307

ZusammenfassungDie Verdunstung ist ein entscheidender Prozess im globalen Wasser‑, Energie- sowie Kohlenstoffkreislauf. Daten zur räumlich-zeitlichen Dynamik der Verdunstung sind daher von großer Bedeutung für Klimamodellierungen, zur Abschätzu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8661186a97d0c40878647f994af2f8da
https://doi.org/10.1007/s00506-021-00768-y

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Technical Note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks

Autor: J. M. Frame, Martin Gauch, Alden Keefe Sampson, Guy Shalev, Daniel Klotz, Sella Nevo, Frederik Kratzert, Grey Nearing

Ingesting near-real-time observation data is a critical component of many operational hydrological forecasting systems. In this paper we compare two strategies for ingesting near-real-time streamflow observations into Long Short-Term Memory (LSTM) ra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2637c6e7320fbad8e11d43aa06efc326
https://hess.copernicus.org/preprints/hess-2021-515/

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Deep learning rainfall-runoff predictions of extreme events

Autor: Martin Gauch, Grey Nearing, Daniel Klotz, Frederik Kratzert, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, Guy Shelev, J. M. Frame

The most accurate rainfall-runoff predictions are currently based on deep learning. There is a concern among hydrologists that data-driven models based on deep learning may not be reliable in extrapolation or for predicting extreme events. This study

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a96e5356f057cd9c5f88bed7519ec05
https://doi.org/10.5194/hess-2021-423

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Hematopoietic stem cell development: Using the zebrafish to identify extrinsic and intrinsic mechanisms regulating hematopoiesis

Autor: J M, Frame, S-E, Lim, T E, North

Publikováno v: Methods in cell biology. 138

Hematopoietic stem cells (HSCs) reside at the apex of the hematopoietic hierarchy, giving rise to each of the blood lineages found throughout the lifetime of the organism. Since the genetic programs regulating HSC development are highly conserved bet

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::6fbfd23914a61e6e514bcf0bfd27fa0d
https://pubmed.ncbi.nlm.nih.gov/28129843

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The NRL Cyclotron Ion Optics System

Autor: R. B. Theus, J. M. Frame, P. Shapiro

Publikováno v: IEEE Transactions on Nuclear Science. 12:917-921

A 9 foot radius, 135 degree, double focusing magnet, having a second order energy resolution less than 2 × 10-4 for 1 mm slits, is the principal element in the NRL Cyclotron Ion Optics System. A 21.5 inch wide pole face and 4.75 inch gap provide rad

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::32e722621108b91a191eae4ef6510117
https://doi.org/10.1109/tns.1965.4323758

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