Auswahl der wissenschaftlichen Literatur zum Thema „Heterogeneous oceanic data“
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Zeitschriftenartikel zum Thema "Heterogeneous oceanic data"
Jourdin, F., O. Francis, P. Vincent und P. Mazzega. „Some results of heterogeneous data inversions for oceanic tides“. Journal of Geophysical Research: Solid Earth 96, B12 (10.11.1991): 20267–88. http://dx.doi.org/10.1029/91jb00426.
Der volle Inhalt der QuelleSun, L. Charles. „Data Inter-Operability Driven by Oceanic Data Assimilation Needs“. Marine Technology Society Journal 33, Nr. 3 (01.01.1999): 55–66. http://dx.doi.org/10.4031/mtsj.33.3.7.
Der volle Inhalt der QuelleChen, Shan-Tai, Shung-Lin Dou und Wann-Jin Chen. „A Data Mining Approach to Rainfall Intensity Classification Using TRMM/TMI Data“. Journal of Advanced Computational Intelligence and Intelligent Informatics 12, Nr. 6 (20.11.2008): 516–22. http://dx.doi.org/10.20965/jaciii.2008.p0516.
Der volle Inhalt der QuelleYi, Shuang, und Kosuke Heki. „Heterogeneous oceanic mass distribution in GRACE observations and its leakage effect“. Geophysical Journal International 221, Nr. 1 (10.01.2020): 603–16. http://dx.doi.org/10.1093/gji/ggaa022.
Der volle Inhalt der QuelleSokolov, S. D., G. Ye Bondarenko, A. K. Khudoley, O. L. Morozov, M. V. Luchitskaya, M. I. Tuchkova und P. W. Layer. „Tectonic reconstruction of Uda-Murgal arc and the Late Jurassic and Early Cretaceous convergent margin of Northeast Asia–Northwest Pacific“. Stephan Mueller Special Publication Series 4 (17.09.2009): 273–88. http://dx.doi.org/10.5194/smsps-4-273-2009.
Der volle Inhalt der QuellePiontkovski, S. A., I. A. Minsky und Ya V. Meger. „LONG-TERM VARIABILITY OF OCEANIC ZOOPLANKTON BIOMASS“. Водные биоресурсы и среда обитания 6, Nr. 3 (2023): 52–65. http://dx.doi.org/10.47921/2619-1024_2023_6_3_52.
Der volle Inhalt der QuelleBoev, Blažo, Vladica Cvetković, Dejan Prelević, Kristina Šarić und Ivan Boev. „EAST VARDAR OPHIOLITES REVISITED: A BRIEF SYNTHESIS OF GEOLOGY AND GEOCHEMICAL DATA“. Contributions, Section of Natural, Mathematical and Biotechnical Sciences 39, Nr. 1 (02.07.2018): 51. http://dx.doi.org/10.20903/csnmbs.masa.2018.39.1.119.
Der volle Inhalt der QuelleKotowski, Alissa J., und Whitney M. Behr. „Length scales and types of heterogeneities along the deep subduction interface: Insights from exhumed rocks on Syros Island, Greece“. Geosphere 15, Nr. 4 (24.06.2019): 1038–65. http://dx.doi.org/10.1130/ges02037.1.
Der volle Inhalt der QuelleSrivastava, Rohit, und Ruchita Shah. „Study of Monsoonal Features Using Regional Climate Model over Heterogeneous Monsoon Dominated Region“. E3S Web of Conferences 101 (2019): 03004. http://dx.doi.org/10.1051/e3sconf/201910103004.
Der volle Inhalt der QuelleLücke, O. H., und I. G. Arroyo. „Density structure and geometry of the Costa Rican subduction zone from 3-D gravity modeling and local earthquake data“. Solid Earth Discussions 7, Nr. 3 (14.07.2015): 1941–77. http://dx.doi.org/10.5194/sed-7-1941-2015.
Der volle Inhalt der QuelleDissertationen zum Thema "Heterogeneous oceanic data"
Zambra, Matteo. „Méthodes IA multimodales dans des contextes d’observation océanographique et de surveillance maritime multi-capteurs hétérogènes“. Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0391.
Der volle Inhalt der QuelleThe aim of this thesis is to study the simultaneous use of heterogeneous ocean datasets to improve the performance of predictive models used in scientific and operational fields for the simulation and analysis of the ocean and marine environment. Two distinct case studies were explored in the course of the thesis work. The first study focuses on the local estimation of wind speed at the sea surface from underwater soundscape measurements and atmospheric model products. The second study considers the spatial extension of the problem and the use of observations at different scales and spatial resolutions, from pseudo-observations simulating satellite images to time series measured by in-situ infrastructures. The recurring theme of these investigations is the multi-modality of the data fed into the model. That is, to what extent and how the predictive model can benefit from the use of spatio-temporally heterogeneous information channels. The preferred methodological tool is a simulation system based on variational data assimilation and deep learning concepts
Buchteile zum Thema "Heterogeneous oceanic data"
Sims, K. W. W., H. E. Newsom und E. S. Gladney. „Chemical Fractionation During Formation Of The Earth’s Core And Continental Crust: Clues From As, Sb, W, And Mo“. In Origin of the Earth, 291–317. Oxford University PressNew York, NY, 1990. http://dx.doi.org/10.1093/oso/9780195066197.003.0017.
Der volle Inhalt der QuelleAlegret, Laia, Gabriela J. Arreguín-Rodríguez und Ellen Thomas. „Oceanic productivity after the Cretaceous/Paleogene impact: Where do we stand? The view from the deep“. In From the Guajira Desert to the Apennines, and from Mediterranean Microplates to the Mexican Killer Asteroid: Honoring the Career of Walter Alvarez. Geological Society of America, 2022. http://dx.doi.org/10.1130/2022.2557(21).
Der volle Inhalt der QuelleVignudelli, Stefano, und Francesco De Biasio. „Coastal Sea Level Trends from a Joint Use of Satellite Radar Altimetry, GPS and Tide Gauges: Case Study of the Northern Adriatic Sea“. In Geodetic Sciences - Theory, Applications and Recent Developments. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98243.
Der volle Inhalt der QuelleCaselli, Graziella, und Sven Drefahl. „Future Mortality in Low Mortality Countries“. In World Population & Human Capital in the Twenty-First Century. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198813422.003.0009.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Heterogeneous oceanic data"
Pinto, Jose, Paulo Sousa Dias, Joao Borges Sousa und Fernando L. Pereira. „Large scale data collection using networks of heterogeneous vehicles and sensors“. In OCEANS 2009-EUROPE (OCEANS). IEEE, 2009. http://dx.doi.org/10.1109/oceanse.2009.5278239.
Der volle Inhalt der QuelleVanMiddlesworth, Mark. „A heterogeneous rapid-turnaround visualization package for AUV data“. In OCEANS 2011 - SPAIN. IEEE, 2011. http://dx.doi.org/10.1109/oceans-spain.2011.6003655.
Der volle Inhalt der QuelleRong, Tian, ChenXu Wang, QingHua Luo und YingChun Li. „Underwater shipwreck target detection based on audio-visual heterogeneous data“. In OCEANS 2023 - Limerick. IEEE, 2023. http://dx.doi.org/10.1109/oceanslimerick52467.2023.10244537.
Der volle Inhalt der QuelleCamossi, Elena, Raffaele Grasso, Gabriele Ferri, Alessandro Faggiani, Kevin LePage und Sandro Carniel. „Maritime Linked Data for Situational Awareness Heterogeneous Sensor Networks“. In OCEANS 2021: San Diego – Porto. IEEE, 2021. http://dx.doi.org/10.23919/oceans44145.2021.9705759.
Der volle Inhalt der QuelleFalchetti, Silvia, Alberto Alvarez und Reiner Onken. „A relocatable EnKF ocean data assimilation tool for heterogeneous observational networks“. In OCEANS 2015 - Genova. IEEE, 2015. http://dx.doi.org/10.1109/oceans-genova.2015.7271359.
Der volle Inhalt der QuelleZhou, Junwu, Hongchang He, Xiaolan Xie und Ke Xu. „Research on Multi-source Heterogeneous Ocean Data Integration System“. In DSIT 2020: 2020 3rd International Conference on Data Science and Information Technology. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3414274.3414503.
Der volle Inhalt der QuelleBagga, Pawandeep, Pradeep Shukla und Chandrajyoti Chitroda. „Optimizing Completion Through Real-Time High-Resolution Resistivity Imaging Tool for Fracture Mapping in Horizontal Wells“. In Offshore Technology Conference Asia. OTC, 2024. http://dx.doi.org/10.4043/34858-ms.
Der volle Inhalt der QuelleSato, Takumi, Kangsoo Kim, Masahiko Sasano, Akihiro Okamoto, Shogo Inaba, Satoshi Kondo, Hiroshi Matsumoto, Takashi Murashima, Toshifumi Fujiwara und Hiroyuki Osawa. „Sea Trials of Multiple Heterogenous Cruising AUVs and ASV With Basic Formation Control“. In ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/omae2023-103370.
Der volle Inhalt der QuelleJing, Liu, und Yue Lin. „Research on data interaction of multi-source heterogeneous information in ocean strategy environment“. In 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA). IEEE, 2017. http://dx.doi.org/10.1109/icbda.2017.8078827.
Der volle Inhalt der QuelleMyshkin, Vyacheslav F., Valery A. Khan, Dmitriy A. Izhoykin, Aygul K. Orazymbetova, Nyrzhamal A. Ospanovа, Aliya N. Kargulova, Vadim V. Dudorov, Denis L. Gamov, Vladimir N. Lensky und Evgeniya S. Abramova. „Reduction of data processing error of heterogeneous system laser sensing“. In XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, herausgegeben von Oleg A. Romanovskii und Gennadii G. Matvienko. SPIE, 2018. http://dx.doi.org/10.1117/12.2506127.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Heterogeneous oceanic data"
Sommer, Stefan, Sascha Flögel, Michael Walter und Frank Wenzhöfer. Autonomous Robotic Network to Resolve Coastal Oxygen Dynamics : Cruise No. AL547, 20.10. – 31.10.2020, Kiel – Kiel, ARCODYN. GEOMAR Helmholtz Centre for Ocean Research Kiel, 2022. http://dx.doi.org/10.3289/cr_al547.
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