と組み合わせたモデル開発を行うことにより、さらに社会に役立つ技術開発を推進したい。謝辞本稿の内容は筆者らの査読論文に基づいている。本研究は文部科学省科学研究費補助金（JP18H04451）の援助を受けている。また本業務の⼀部は、総務省委託業務「0155–0099電波伝搬の観測・分析等の推進」によって⾏われたものである。参考文献】【1 T. Kosugi, K. Matsuzaki, T. Sakao, T. Shimizu, Y. Sone, S. Yachikawa, T. Hashimoto, K. Minesugi, A. Ohnishi, T. Yamada, S. Tsuneta, H. Hara, K. Ichimoto, Y. Suematsu, M. Shimojo, T. Watanabe, S. Shimada, J.M. Davis, L.D. Hill, J.K. Owens, A.M. Title, J.L. Culhane, L.K. Harra, G.A. Doschek, and L. Golub, “The Hinode (Solar-B) mission: an overview,” Solar Physics, vol.243, pp.3–17, June 2007.2 W. Pesnell, B.J. Thompson, and P.C. Chamberlin, “The Solar Dynamics Observatory (SDO),” Solar Physics, vol.275, pp.3–15, Jan. 2012.3 R. Maeda and H. Inuki, “Magnitude of short-wave fade-out,” J. Radio Res. Lab., vol.18, no.99, pp.467–476, Nov. 1972.4 T. Sato, “Sudden fmin enhancements and sudden cosmic noise absorp-tions associated with solar X-ray flares,” J. Geomagnetism and Geo-electricity, vol.27, pp.95–112, 1975.5 C. Tao, M. Nishioka, S. Saito, D. Shiota, K. Watanabe, N. Nishizuka, T. Tsugawa, and M. Ishii, “Statistical analysis of short-wave fadeout for extreme space weather event estimation,” Earth, Planets and Space, vol.72, article id.173, pp.1–16, Dec. 2020.6 P.S. McIntosh, “The classification of sunspot groups,” Solar Physics, vol.125, pp.251–267, Sept. 1990.7 I. Sammis, F. Tang, and H. Zirin, “The dependences of large flare oc-currence on the magnetic structure of sunspots,” The Astrophysical Journal, vol.540, pp.583–587, Sept. 2000.8 P.T. Gallagher, Y.-J. Moon, H. Wang, “Active region monitoring and flare forecasting - I. Data processing and first results,” Solar Physics, vol.209, pp.171–183, Sept. 2002.9 K.D. Leka and G. Barnes, “Photospheric Magnetic Field Properties of Flaring versus flare-quiet active regions. II. Discriminant Analysis,” The Astrophysical Journal, vol.595, pp.1296–1306, Oct. 2003.10 Y. Bamba, K. Kusano, T.T. Yamamoto, and T.J. Okamoto, “Study on the triggering process of solar flares based on Hinode/SOT observations,” The Astrophysical Journal, vol.778, article id.48, pp.1–13, Nov. 2013.11 M.D. Crown, “Validation of the NOAA space weather prediction center’s solar flare forecasting look-up table and forecaster-issued probabilities,” Space Weather, vol.10, CiteID S06006, June 2012.12 A. Devos, C. Verbeeck, and E. Robbrecht, “Verification of space weather forecasting at the regional warning center in Belgium,” J. Space Weather and Space Climate, vol.4, id.A29, pp.1–15, October 2014.13 Y. Kubo, M. Den, and M. Ishii, “Verification of operational solar flare forecast: case of regional warning center Japan,” J. Space Weather and Space Climate, vol.7, id.A20, pp.1–16, Aug. 2017.14 K. Shibata and T. Magara, “Solar flares: magnetohydrodynamic pro-cesses,” Living Rev. Solar Physics, vol.8, article id.6, pp.1–99, Dec. 2011.15 K. Kusano, Y. Bamba, T.T. Yamamoto, Y. Iida, S. Toriumi, and A. Asai, “Magnetic field structures triggering solar flares and coronal mass ejec-tions,” The Astrophysical Journal, vol.760, article id.31, pp.1–9 , No-vember 2012.16 K. Kusano, T. Iju, Y. Bamba, and S. Inoue, “A Physics-based method that can predict imminent large solar flares,” Science, vol.369, pp.587–591, July 2020.17 C.M. Bishop, Pattern Recognition and Machine Learning: Information Science and Statistics, M. Jordan, J. Kleinberg, and M. Schölkopf, ed., New York: Springer, 1992.18 G.E. Hinton and R.R. Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science, vol.313, pp.504–507, July 2006.19 Y. LeCun, Y. Bengio, and G. E. Hinton, “Deep learning,” Nature, vol.521, pp.436–444, May 2015.20 N. Nishizuka, K. Sugiura, Y. Kubo, M. Den, and M. Ishii, “Deep Flare Net (DeFN) model for solar flare prediction,” The Astrophysical Journal, vol.858, article id.113, pp.1–8, May 2018.21 N. Nishizuka, K. Sugiura, Y. Kubo, M. Den, S. Watari, and M. Ishii, “Solar flare prediction model with three machine-learning algorithms using ultraviolet brightening and vector magnetograms,” The Astro-physical Journal, vol.835, article id.156, pp.1–10, Jan. 2017.22 K. Sugiura and H. Kawai, “Grounded language understanding for ma-nipulation instructions using GAN-based classifications,” Proc. IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp.519–524, Dec. 2017.23 M.G. Bobra and S. Couvidat, “Solar flare prediction using SDO/HMI vector magnetic field data with a machine-learning algorithm,” The Astrophysical Journal, vol.798, article id.135, pp.1–11, Jan. 2015.24 N. Nishizuka, Y. Kubo, K. Sugiura, M. Den, and M. Ishii, “Operational solar flare prediction model using Deep Flare Net,” Earth, Planets and Space, vol.73, article id.64, pp.1–12, March 2021.25 A.W. Hanseen and W.J.A. Kuipers, “On the relationship between the frequency of rain and various meteorological parameters,” Mededelin-gen en verhandelingen, no.81, 's-Gravenhage : Staatsdrukkerij- en Uitgeverijbedrijf, 1965.26 D.S. Bloomfield, P.A. Higgins, R.T.J. McAteer, and P.T. Gallagher, “To-ward reliable benchmarking of solar flare forecasting methods,” The Astrophysical Journal Letters, vol.747, article id.L41 (7pp), March 2012.27 L. Breiman, “Random forests,” Machine Learning, vol.45, pp.5–32, Jan. 2001.28 X. Huang, H. Wang, L. Xu, J. Liu, R. Li, and X. Dai, “Deep learning based solar flare forecasting model. I. Results for line-of-sight magne-tograms,” The Astrophysical Journal, vol.856, article id.7, (pp.1–11), March 2018.29 E. Park, Y.-J. Moon, S. Shin, K. Yi, D. Lim, H. Lee, and G. Shin, “Ap-plication of the deep convolutional neural network to the forecast of solar flare occurrence using full-disk solar magnetograms,” The Astro-physical Journal, vol.869, article id.91, pp.1–6, Dec. 2018.西塚直人 （にしづか なおと）電磁波研究所電磁波伝搬研究センター宇宙環境研究室テニュアトラック研究員博士（理学）太陽プラズマ物理、機械学習を用いた太陽フレア予測久保勇樹 （くぼ ゆうき）電磁波研究所電磁波伝搬研究センター宇宙環境研究室研究マネージャー／宇宙天気予報グループグループリーダー博士（学術）太陽物理学、予報評価技術154 情報通信研究機構研究報告 Vol.67 No.1 （2021）4 太陽・太陽風研究
元のページ ../index.html#160