يعرض 1 - 20 نتائج من 289 نتيجة بحث عن '"Liemohn, M. W."', وقت الاستعلام: 0.63s تنقيح النتائج
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    المساهمون: Climate and Space Sciences and Engineering, Finnish Meteorological Institute, Ann Arbor

    مصطلحات موضوعية: Atmospheric, Oceanic and Space Sciences, Science, Engineering

    وصف الملف: application/pdf

    Relation: Machine Learning in Heliophysics; Swiger, B. M., Liemohn, M. W., Ganushkina, N. Y., & Dubyagin, S. V. (2022). Energetic electron flux predictions in the near-Earth plasma sheet from solar wind driving. Space Weather, 20, e2022SW003150. https:// doi.org/10.1029/2022SW003150; https://hdl.handle.net/2027.42/175139; https://dx.doi.org/10.7302/6600; Space Weather; orcid:0000-0002-7039-2631; orcid:0000-0002-9259-850X; orcid:0000-0002-0888-2517; Liemohn, Michael; 0000-0002-7039-2631; Ganushkina, Natalia; 0000-0002-9259-850X; dubyagin, stepan; 0000-0002-0888-2517

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    المساهمون: Institut de recherche en astrophysique et planétologie (IRAP), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)

    المصدر: ISSN: 2169-9380.

    Relation: BIBCODE: 2021JGRA.12630014G

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    وصف الملف: application/pdf

    Relation: Simms, L. E.; Ganushkina, N. Yu.; Kamp, M.; Balikhin, M.; Liemohn, M. W. (2023). "Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Comparison of Models." Space Weather 21(5): n/a-n/a.; https://hdl.handle.net/2027.42/176809; Space Weather; Roeder, J. L., Chen, M. W., Fennell, J. F., & Friedel, R. ( 2005 ). Empirical models of the low-energy plasma in the inner magnetosphere. Space Weather, 3 ( 12 ). https://doi.org/10.1029/2005SW000161; Pakhotin, I. P., Drozdov, A. Y., Shprits, Y. Y., Boynton, R. J., Subbotin, D. A., & Balikhin, M. A. ( 2014 ). Simulation of high-energy radiation belt electron fluxes using NARMAX-VERB coupled codes. Journal of Geophysical Research: Space Physics, 119 ( 10 ), 8073 – 8086. https://doi.org/10.1002/2014JA020238; Paulikas, G., & Blake, J. ( 1979 ). Effects of the solar wind on magnetospheric dynamics: Energetic electrons at the synchronous orbit. In Quantitative modeling of magnetospheric processes (pp. 180 – 202 ). American Geophysical Union (AGU). https://doi.org/10.1029/GM021p0180; Reeves, G. D., Morley, S. K., Friedel, R. H. W., Henderson, M. G., Cayton, T. E., Cunningham, G., et al. ( 2011 ). On the relationship between relativistic electron flux and solar wind velocity: Paulikas and Blake revisited. Journal of Geophysical Research, 116 ( A2 ), A02213. https://doi.org/10.1029/2010JA015735; Rowland, W., & Weigel, R. S. ( 2012 ). Intracalibration of particle detectors on a three-axis stabilized geostationary platform. Space Weather, 10 ( 11 ). https://doi.org/10.1029/2012SW000816; Saito, T., & Rehmsmeier, M. ( 2015 ). The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLoS One, 10 ( 3 ), e0118432. https://doi.org/10.1371/journal.pone.0118432; Schaefer, J. T. ( 1990 ). The critical success index as an indicator of warning skill. Weather and Forecasting, 5 ( 4 ), 570 – 575. https://doi.org/10.1175/1520-0434; Shi, Y., Zesta, E., & Lyons, L. R. ( 2009 ). Features of energetic particle radial profiles inferred from geosynchronous responses to solar wind dynamic pressure enhancements. Annales Geophysicae, 27 ( 2 ), 851 – 859. https://doi.org/10.5194/angeo-27-851-2009; Sicard-Piet, A., Bourdarie, S., Boscher, D., Friedel, R. H. W., Thomsen, M., Goka, T., et al. ( 2008 ). A new international geostationary electron model: IGE-2006, from 1 keV to 5.2 MeV. Space Weather, 6 ( 7 ). https://doi.org/10.1029/2007SW000368; Sillanpää, I., Ganushkina, N. Y., Dubyagin, S., & Rodriguez, J. V. ( 2017 ). Electron fluxes at geostationary orbit from GOES MAGED data. Space Weather, 15 ( 12 ), 1602 – 1614. https://doi.org/10.1002/2017SW001698; Simms, L. E., & Engebretson, M. ( 2020 ). Classifier neural network models predict relativistic electron events at geosynchronous orbit better than multiple regression or ARMAX models. Journal of Geophysical Research: Space Physics, 125 ( 5 ), e2019JA027357. https://doi.org/10.1029/2019JA027357; Simms, L. E., Engebretson, M., Clilverd, M., Rodger, C., Lessard, M., Gjerloev, J., & Reeves, G. ( 2018 ). A distributed lag autoregressive model of geostationary relativistic electron fluxes: Comparing the influences of waves, seed and source electrons, and solar wind inputs. Journal of Geophysical Research: Space Physics, 123 ( 5 ), 3646 – 3671. https://doi.org/10.1029/2017JA025002; Simms, L. E., Engebretson, M., & Reeves, G. ( 2022 ). Removing diurnal signals and longer term trends from electron flux and ULF correlations: A comparison of spectral subtraction, simple differencing, and ARIMAX models. Journal of Geophysical Research, 127 ( 2 ), e2021JA030021. https://doi.org/10.1029/2021JA030021; Simms, L. E., Engebretson, M. J., Clilverd, M. A., Rodger, C. J., & Reeves, G. D. ( 2018 ). Nonlinear and synergistic effects of ULF Pc5, VLF Chorus, and EMIC waves on relativistic electron flux at geosynchronous orbit. Journal of Geophysical Research: Space Physics, 123 ( 6 ), 4755 – 4766. https://doi.org/10.1029/2017JA025003; Simms, L. E., Engebretson, M. J., Pilipenko, V., Reeves, G. D., & Clilverd, M. ( 2016 ). Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis. Journal of Geophysical Research: Space Physics, 121 ( 4 ), 3181 – 3197. https://doi.org/10.1002/2016JA022414; Simms, L. E., Engebretson, M. J., Rodger, C. J., Gjerloev, J. W., & Reeves, G. D. ( 2019 ). Predicting lower band chorus with autoregressive-moving average transfer function (ARMAX) models. Journal of Geophysical Research: Space Physics, 124 ( 7 ), 5692 – 5708. https://doi.org/10.1029/2019ja026726; Simms, L. E., Ganushkina, N. Y., van de Kamp, M., Liemohn, M. W., & Dubyagin, S. ( 2022 ). Using ARMAX models to determine the drivers of 40-150 keV GOES electron fluxes. Journal of Geophysical Research, 127 ( 9 ), e2022JA030538. https://doi.org/10.1029/2022JA030538; Simms, L. E., Pilipenko, V., Engebretson, M. J., Reeves, G. D., Smith, A. J., & Clilverd, M. ( 2014 ). Prediction of relativistic electron flux at geostationary orbit following storms: Multiple regression analysis. Journal of Geophysical Research: Space Physics, 119 ( 9 ), 7297 – 7318. https://doi.org/10.1002/2014JA019955; Smirnov, A. G., Berrendorf, M., Shprits, Y. Y., Kronberg, E. A., Allison, H. J., Aseev, N. A., et al. ( 2020 ). Medium energy electron flux in Earth’s outer radiation belt (MERLIN): A machine learning model. Space Weather, 18 ( 11 ), e2020SW002532. https://doi.org/10.1029/2020SW002532; Smith, G. ( 2018 ). Step away from stepwise. Journal of Big Data, 5 ( 32 ), 32. https://doi.org/10.1186/s40537-018-0143-6; Stepanov, N. A., Sergeev, V. A., Sormakov, D. A., Andreeva, V. A., Dubyagin, S. V., Ganushkina, N., et al. ( 2021 ). Superthermal proton and electron fluxes in the plasma sheet transition region and their dependence on solar wind parameters. Journal of Geophysical Research: Space Physics, 126 ( 4 ), e2020JA028580. https://doi.org/10.1029/2020JA028580; Subbotin, D. A., & Shprits, Y. Y. ( 2009 ). Three-dimensional modeling of the radiation belts using the Versatile Electron Radiation Belt (VERB) code. Space Weather, 7 ( 10 ). https://doi.org/10.1029/2008SW000452; Swiger, B. M., Liemohn, M. W., Ganushkina, N. Y., & Dubyagin, S. ( 2022 ). Energetic electron flux predictions in the near-earth plasma sheet from solar wind driving. Space Weather, 20 ( 11 ), e2022SW003150. https://doi.org/10.1029/2022SW003150; Thomsen, M. F., Henderson, M. G., & Jordanova, V. K. ( 2013 ). Statistical properties of the surface-charging environment at geosynchronous orbit. Space Weather, 11 ( 5 ), 237 – 244. https://doi.org/10.1002/swe.20049; Tofallis, C. ( 2015 ). 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Correlation of changes in the outer-zone relativistic-electron population with upstream solar wind and magnetic field measurements. Geophysical Research Letters, 24 ( 8 ), 927 – 929. https://doi.org/10.1029/97GL00859; Boynton, R. J., Amariutei, O. A., Shprits, Y. Y., & Balikhin, M. A. ( 2019 ). The system science development of local time-dependent 40-keV electron flux models for geostationary orbit. Space Weather, 17 ( 6 ), 894 – 906. https://doi.org/10.1029/2018SW002128; Boynton, R. J., Balikhin, M. A., & Billings, S. A. ( 2015 ). Online NARMAX model for electron fluxes at GEO. Annales Geophysicae, 33 ( 3 ), 405 – 411. https://doi.org/10.5194/angeo-33-405-2015; Boynton, R. J., Balikhin, M. A., Billings, S. A., Reeves, G. D., Ganushkina, N., Gedalin, M., et al. ( 2013 ). The analysis of electron fluxes at geosynchronous orbit employing a NARMAX approach. Journal of Geophysical Research: Space Physics, 118 ( 4 ), 1500 – 1513. https://doi.org/10.1002/jgra.50192; Boynton, R. J., Balikhin, M. A., Billings, S. A., Wei, H. L., & Ganushkina, N. ( 2011 ). Using the NARMAX OLS-ERR algorithm to obtain the most influential coupling functions that affect the evolution of the magnetosphere. Journal of Geophysical Research, 116 ( A5 ), A05218. https://doi.org/10.1029/2010JA015505; Boynton, R. J., Balikhin, M. A., Sibeck, D. G., Walker, S. N., Billings, S. A., & Ganushkina, N. ( 2016 ). Electron flux models for different energies at geostationary orbit. Space Weather, 14 ( 10 ), 846 – 860. https://doi.org/10.1002/2016SW001506; Camporeale, E., Wilkie, G. J., Drozdov, A. Y., & Bortnik, J. ( 2022 ). Data-driven discovery of fokker-planck equation for the earth’s radiation belts electrons using physics-informed neural networks. Journal of Geophysical Research: Space Physics, 127, e2022JA030377. https://doi.org/10.1029/2022JA030377; Capman, N. S. S., Simms, L. E., Engebretson, M. J., Clilverd, M. A., Rodger, C. J., Reeves, G. D., et al. ( 2019 ). Comparison of multiple and logistic regression analyses of relativistic electron flux enhancement at geosynchronous orbit following storms. Journal of Geophysical Research: Space Physics, 124 ( 12 ), 10246 – 10256. https://doi.org/10.1029/2019JA027132; Chakraborty, S., & Morley, S. K. ( 2020 ). Probabilistic prediction of geomagnetic storms and the Kp index. Journal of Space Weather and Space Climate, 10, 36. https://doi.org/10.1051/swsc/2020037; Chen, M. W., Lemon, C. L., Orlova, K., Shprits, Y., Hecht, J., & Walterscheid, R. L. ( 2015 ). Comparison of simulated and observed trapped and precipitating electron fluxes during a magnetic storm. Geophysical Research Letters, 42 ( 20 ), 8302 – 8311. https://doi.org/10.1002/2015GL065737; Chicco, D., & Jurman, G. ( 2020 ). The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC Genomics, 21 ( 6 ), 6. https://doi.org/10.1186/s2864-019-6413-7; Choi, H. 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W., Sicard, A., & Payan, D. ( 2021 ). Worst-case severe environments for surface charging observed at LANL satellites as dependent on solar wind and geomagnetic conditions. Space Weather, 19 ( 9 ), e2021SW002732. https://doi.org/10.1029/2021SW002732; Ginet, G. P., O’Brien, T. P., Huston, S. L., Johnston, W. R., Guild, T. B., Friedel, R., et al. ( 2013 ). AE9, AP9 and SPM: New models for specifying the trapped energetic particle and space plasma environment. Space Science Reviews, 179 ( 1–4 ), 579 – 615. https://doi.org/10.1007/s11214-013-9964-y; Glauert, S. A., Horne, R. B., & Meredith, N. P. ( 2014 ). Three-dimensional electron radiation belt simulations using the BAS radiation belt model with new diffusion models for chorus, plasmaspheric hiss, and lightning-generated whistlers. Journal of Geophysical Research: Space Physics, 119 ( 1 ), 268 – 289. https://doi.org/10.1002/2013JA019281; Hartley, D. P., Denton, M. H., & Rodriguez, J. V. ( 2014 ). 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    المصدر: eISSN: 1432-0576

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    Relation: info:eu-repo/grantAgreement/EC/FP7/262468; https://angeo.copernicus.org/articles/30/177/2012/

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    وصف الملف: application/pdf

    Relation: Simms, L. E.; Ganushkina, N. Yu.; Kamp, M.; Liemohn, M. W.; Dubyagin, S. (2022). "Using ARMAX Models to Determine the Drivers of 40–150 keV GOES Electron Fluxes." Journal of Geophysical Research: Space Physics 127(9): n/a-n/a.; https://hdl.handle.net/2027.42/174933; Journal of Geophysical Research: Space Physics; Roeder, J. L., Chen, M. W., Fennell, J. F., & Friedel, R. ( 2005 ). Empirical models of the low-energy plasma in the inner magnetosphere. Space Weather, 3 ( 12 ). https://doi.org/10.1029/2005SW000161; Pulkkinen, T. I., Dimmock, A. P., Lakka, A., Osmane, A., Kilpua, E., Myllys, M., et al. ( 2016 ). Magnetosheath control of solar wind–magnetosphere coupling efficiency. Journal of Geophysical Research: Space Physics, 121 ( 9 ), 8728 – 8739. https://doi.org/10.1002/2016JA023011; Reeves, G. D., Morley, S. K., Friedel, R. H. W., Henderson, M. G., Cayton, T. E., Cunningham, G., et al. ( 2011 ). 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Russian Journal of Earth Sciences, 17 ( 2 ), 1 – 13. https://doi.org/10.2205/2017ES000597

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    Academic Journal

    المصدر: Seki, K.; Nagy, A.; Jackman, C. M.; Crary, F.; Fontaine, D.; Zarka, P.; Wurz, Peter; Milillo, A.; Slavin, J. A.; Delcourt, D. C.; Wiltberger, M.; Ilie, R.; Jia, X.; Ledvina, S. A.; Liemohn, M. W.; Schunk, R. W. (2015). A Review of General Physical and Chemical Processes Related to Plasma Sources and Losses for Solar System Magnetospheres. Space science reviews, 192(1-4), pp. 27-89. Kluwer Academic Publishers 10.1007/s11214-015-0170-y

    مصطلحات موضوعية: 530 Physics

    وصف الملف: application/pdf

  14. 14
    Academic Journal
  15. 15
    Report
  16. 16
    Academic Journal

    مصطلحات موضوعية: Electrical Engineering, Engineering

    وصف الملف: application/pdf

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    المساهمون: National Space Science and Technology Center (NSSTC), NASA Marshall Space Flight Center (MSFC)-University of Alabama in Huntsville (UAH), Space Physics Research Laboratory Ann Arbor (SPRL), University of Michigan Ann Arbor, University of Michigan System-University of Michigan System, Computer Science Department, University of Alabama in Huntsville (UAH), GSFC Laboratory for Extraterrestrial Physics, NASA Goddard Space Flight Center (GSFC)

    المصدر: ISSN: 0992-7689.

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