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Title: Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]
  1. Los Alamos National Laboratory Los Alamos NM USA, School of GeosciencesThe University of Oklahoma OK USA
  2. Los Alamos National Laboratory Los Alamos NM USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1600854
Alternate Identifier(s):
OSTI ID: 1600855
Resource Type:
Published Article
Journal Name:
Space Weather
Additional Journal Information:
[Journal Name: Space Weather Journal Volume: 18 Journal Issue: 2]; Journal ID: ISSN 1542-7390
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English

Citation Formats

Pires de Lima, Rafael, Chen, Yue, and Lin, Youzuo. Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms. United States: N. p., 2020. Web. doi:10.1029/2019SW002399.
Pires de Lima, Rafael, Chen, Yue, & Lin, Youzuo. Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms. United States. doi:10.1029/2019SW002399.
Pires de Lima, Rafael, Chen, Yue, and Lin, Youzuo. Sat . "Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms". United States. doi:10.1029/2019SW002399.
@article{osti_1600854,
title = {Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms},
author = {Pires de Lima, Rafael and Chen, Yue and Lin, Youzuo},
abstractNote = {},
doi = {10.1029/2019SW002399},
journal = {Space Weather},
number = [2],
volume = [18],
place = {United States},
year = {2020},
month = {2}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1029/2019SW002399

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Works referenced in this record:

Neural networks and physical systems with emergent collective computational abilities.
journal, April 1982

  • Hopfield, J. J.
  • Proceedings of the National Academy of Sciences, Vol. 79, Issue 8
  • DOI: 10.1073/pnas.79.8.2554

Machine Learning Reveals the State of Intermittent Frictional Dynamics in a Sheared Granular Fault
journal, July 2019

  • Ren, C. X.; Dorostkar, O.; Rouet‐Leduc, B.
  • Geophysical Research Letters, Vol. 46, Issue 13
  • DOI: 10.1029/2019GL082706

Linear prediction filter analysis of relativistic electron properties at 6.6 R E
journal, January 1990

  • Baker, D. N.; McPherron, R. L.; Cayton, T. E.
  • Journal of Geophysical Research, Vol. 95, Issue A9
  • DOI: 10.1029/JA095iA09p15133

Deep learning
journal, May 2015

  • LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey
  • Nature, Vol. 521, Issue 7553
  • DOI: 10.1038/nature14539

Automatic classification of seismic events within a regional seismograph network
journal, February 2016


Steps toward Artificial Intelligence
journal, January 1961


High- Z energetic particles at geosynchronous orbit during the Great Solar Proton Event Series of October 1989
journal, January 1992

  • Belian, R. D.; Gisler, G. R.; Cayton, T.
  • Journal of Geophysical Research, Vol. 97, Issue A11
  • DOI: 10.1029/92JA01139

Definitions, methods, and applications in interpretable machine learning
journal, October 2019

  • Murdoch, W. James; Singh, Chandan; Kumbier, Karl
  • Proceedings of the National Academy of Sciences, Vol. 116, Issue 44
  • DOI: 10.1073/pnas.1900654116

Statistical Controls on Induced Seismicity
conference, January 2018

  • Sinha, Saurabh; Wen, Yunjie; De Lima, Rafael Pires
  • Proceedings of the 6th Unconventional Resources Technology Conference
  • DOI: 10.15530/urtec-2018-2897507

Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
journal, January 2019

  • Kong, Weicong; Dong, Zhao Yang; Jia, Youwei
  • IEEE Transactions on Smart Grid, Vol. 10, Issue 1
  • DOI: 10.1109/TSG.2017.2753802

The Magnetic Electron Ion Spectrometer (MagEIS) Instruments Aboard the Radiation Belt Storm Probes (RBSP) Spacecraft
journal, June 2013

  • Blake, J. B.; Carranza, P. A.; Claudepierre, S. G.
  • Space Science Reviews, Vol. 179, Issue 1-4
  • DOI: 10.1007/s11214-013-9991-8

Forecasting the Earth’s radiation belts and modelling solar energetic particle events: Recent results from SPACECAST
journal, January 2013

  • Horne, Richard B.; Glauert, Sarah A.; Meredith, Nigel P.
  • Journal of Space Weather and Space Climate, Vol. 3
  • DOI: 10.1051/swsc/2013042

PreMevE: New Predictive Model for Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt
journal, March 2019

  • Chen, Yue; Reeves, Geoffrey D.; Fu, Xiangrong
  • Space Weather, Vol. 17, Issue 3
  • DOI: 10.1029/2018SW002095

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
journal, May 2016

  • Tajbakhsh, Nima; Shin, Jae Y.; Gurudu, Suryakanth R.
  • IEEE Transactions on Medical Imaging, Vol. 35, Issue 5
  • DOI: 10.1109/TMI.2016.2535302

Multiyear Measurements of Radiation Belt Electrons: Acceleration, Transport, and Loss
journal, April 2019

  • Baker, Daniel N.; Hoxie, Vaughn; Zhao, Hong
  • Journal of Geophysical Research: Space Physics
  • DOI: 10.1029/2018JA026259

Convolutional neural networks as aid in core lithofacies classification
journal, August 2019

  • Pires de Lima, Rafael; Suriamin, Fnu; Marfurt, Kurt J.
  • Interpretation, Vol. 7, Issue 3
  • DOI: 10.1190/INT-2018-0245.1

Prediction of the electron flux environment in geosynchronous orbit using a neural network technique
journal, December 2011


Hybrid speech recognition with Deep Bidirectional LSTM
conference, December 2013

  • Graves, Alex; Jaitly, Navdeep; Mohamed, Abdel-rahman
  • 2013 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), 2013 IEEE Workshop on Automatic Speech Recognition and Understanding
  • DOI: 10.1109/ASRU.2013.6707742

Data-derived forecasting model for relativistic electron intensity at geosynchronous orbit: MEV ELECTRON FLUX FORECASTING
journal, May 2004

  • Ukhorskiy, A. Y.; Sitnov, M. I.; Sharma, A. S.
  • Geophysical Research Letters, Vol. 31, Issue 9
  • DOI: 10.1029/2004GL019616

ImageNet Large Scale Visual Recognition Challenge
journal, April 2015

  • Russakovsky, Olga; Deng, Jia; Su, Hao
  • International Journal of Computer Vision, Vol. 115, Issue 3
  • DOI: 10.1007/s11263-015-0816-y

Medical image retrieval using deep convolutional neural network
journal, November 2017


Forecasting and remote sensing outer belt relativistic electrons from low Earth orbit: FORECASTING NOWCASTING MEV ELECTRONS FROM LEO
journal, February 2016

  • Chen, Yue; Reeves, Geoffrey D.; Cunningham, Gregory S.
  • Geophysical Research Letters, Vol. 43, Issue 3
  • DOI: 10.1002/2015GL067481

Quantitative Prediction of High-Energy Electron Integral Flux at Geostationary Orbit Based on Deep Learning
journal, July 2018

  • Wei, Lihang; Zhong, Qiuzhen; Lin, Ruilin
  • Space Weather, Vol. 16, Issue 7
  • DOI: 10.1029/2018SW001829

The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting
journal, August 2019


Algorithm AS 136: A K-Means Clustering Algorithm
journal, January 1979

  • Hartigan, J. A.; Wong, M. A.
  • Applied Statistics, Vol. 28, Issue 1
  • DOI: 10.2307/2346830

Framewise phoneme classification with bidirectional LSTM and other neural network architectures
journal, July 2005


Global time-dependent chorus maps from low-Earth-orbit electron precipitation and Van Allen Probes data: Chen et al.: Derive Global Time-dependent Chorus Maps
journal, February 2014

  • Chen, Yue; Reeves, Geoffrey D.; Friedel, Reiner H. W.
  • Geophysical Research Letters, Vol. 41, Issue 3
  • DOI: 10.1002/2013GL059181

Convolutional neural network for earthquake detection and location
journal, February 2018

  • Perol, Thibaut; Gharbi, Michaël; Denolle, Marine
  • Science Advances, Vol. 4, Issue 2
  • DOI: 10.1126/sciadv.1700578

Deep convolutional neural networks as a geological image classification tool
journal, June 2019

  • Pires de Lima, Rafael; Bonar, Alicia; Coronado, David Duarte
  • The Sedimentary Record, Vol. 17, Issue 2
  • DOI: 10.2110/sedred.2019.2.4

Long Short-Term Memory
journal, November 1997


Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit
journal, June 2000

  • Hahnloser, Richard H. R.; Sarpeshkar, Rahul; Mahowald, Misha A.
  • Nature, Vol. 405, Issue 6789
  • DOI: 10.1038/35016072

Magnetic coordinates
journal, August 1966


Principal component analysis and K-means analysis of airborne gamma-ray spectrometry surveys
conference, August 2018


A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs
journal, August 2019

  • Valentín, Manuel Blanco; Bom, Clécio R.; Coelho, Juliana M.
  • Journal of Petroleum Science and Engineering, Vol. 179
  • DOI: 10.1016/j.petrol.2019.04.030

Science Objectives and Rationale for the Radiation Belt Storm Probes Mission
journal, September 2012