Hostname: page-component-745bb68f8f-lrblm Total loading time: 0 Render date: 2025-01-09T15:27:56.370Z Has data issue: false hasContentIssue false
  • English
  • Français

Nonlinear Autoregressive Model (NARX) of Stationary Forbush Decrease Indices Based on Levenberg-Marquardt Feedback Algorithm

Published online by Cambridge University Press:  27 November 2018

Sankar Narayan Patra Open the ORCID record for Sankar Narayan Patra [Opens in a new window] ,
Subhash Chandra Panja ,
Amrita Prasad ,
Soumya Roy  and
Koushik Ghosh
Sankar Narayan Patra*
Affiliation:
Astronomical Instruments Design Laboratory, Instrumentation Science Dept., Jadavpur University, Kolkata, India
Subhash Chandra Panja
Affiliation:
Astronomical Instruments Design Laboratory, Instrumentation Science Dept., Jadavpur University, Kolkata, India
Amrita Prasad
Affiliation:
Astronomical Instruments Design Laboratory, Instrumentation Science Dept., Jadavpur University, Kolkata, India
Soumya Roy
Affiliation:
Astronomical Instruments Design Laboratory, Instrumentation Science Dept., Jadavpur University, Kolkata, India
Koushik Ghosh
Affiliation:
Astronomical Instruments Design Laboratory, Instrumentation Science Dept., Jadavpur University, Kolkata, India
*
Corresponding email id: sankar.n.patra@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Artificial Neural Network based Nonlinear Autoregressive Model is designed to reconstruct and predict Forbush Decrease (FD) Data obtained from Izmiran, Russia. Result indicates that the model seems adequate for short term prediction of the FD data.

Keywords

ANNAutoregressiveAdaptive L-M algorithmShort Term Prediction & MSE
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 13 , Symposium S340: Long-term Datasets for the Understanding of Solar and Stellar Magnetic Cycles , February 2018 , pp. 323 - 324
Copyright
Copyright © International Astronomical Union 2018 

References

Patra, S. N., Ghosh, K., & Panja, S. C., 2011, Ap&&SS, 334, 317Google Scholar
Patra, S. N., Ghosh, K., & Panja, S. C., 2011, IJEER, 3, 237Google Scholar
Gold, T., 1960, ApJs, 4, 406Google Scholar
Barnden, L. R., 1973, ICRC, 2, 1277Google Scholar
Nishida, A., 1983, JGR, 88, 785Google Scholar
Lockwood, J. A., 1971, SSRv, 12, 658Google Scholar
Burlaga, L., Sittler, E., Mariani, F., & Schwenn, R., 1981, JGRA, 86, 6673Google Scholar
Cane, H. V. & Richardson, I. G., 1995, JGRA, 100, 1755Google Scholar
Fluckiger, E. O., 1991, Proc. 22nd ICRC, 5, 273Google Scholar
Ifedili, S. O., 1996, Solar Phys., 168, 195Google Scholar
Shah, G. N., Mufti, S., Darzi, A., & Ishtiaq, P. M., 2005, ICRC, 1, 351Google Scholar
Kudo, S., Wadu, M., Tanskanen, & Kodama, M., 1985, Proc. of 19th ICRC (SH-5), 2376, 246Google Scholar
Iucci, N., Parisi, M., Storini, M., & Villoresi, G., 1985, Proc. of 19th ICRC, 2376, 226Google Scholar
Belov, A. V. et al., 2005, Proc. of 29th ICRC, 1, 375Google Scholar
Pucheta, J. A. et al., 2011, Computacin y Sistemas, 14, 423Google Scholar