Modeling and predicting sunspot activity - state space reconstruction plus artificial neural network methods

被引：8
|
作者：
Kulkarni, DR [1 ]
Pandya, AS [1 ]
Parikh, JC [1 ]
机构：
[1] Phys Res Lab, Ahmedabad 380009, Gujarat, India
来源：
GEOPHYSICAL RESEARCH LETTERS | 1998年 / 25卷 / 04期
关键词：
D O I：
10.1029/98GL00136
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Ideas of state space reconstruction of dynamics are combined with nonparametric artificial neural network approach to model sunspot activity. The structural aspects of the model are for the most part determined from the sunspot data. The model gives a very good fit to the data. Further it predicts weaker solar activity in the current (23-rd) cycle, with a maximum of 144 +/- 36.
引用
收藏
页码：457 / 460
页数：4
相关论文
共 50 条
  • [21] Predicting Product Precision in Fused Deposition Modeling Based on Artificial Neural Network
    Ji, Liangbo
    Zhou, Tianrui
    ADVANCED SCIENCE LETTERS, 2011, 4 (6-7) : 2193 - 2197
  • [22] Artificial neural network applied to the discrimination of antibacterial activity by topological methods
    Tomás-Vert, F
    Pérez-Giménez, F
    Salabert-Salvador, MT
    García-March, FJ
    Jaén-Oltra, J
    JOURNAL OF MOLECULAR STRUCTURE-THEOCHEM, 2000, 504 : 249 - 259
  • [23] Comparison of artificial neural network efficiency for predicting the geomagnetic activity index Dst
    Barkhatov, N.A.
    Belliustin, N.S.
    Levitin, A.E.
    Sakharov, S.Yu.
    Izvestiya Vysshikh Uchebnykh Zavedenij. Radiofizika, 2000, 43 (05): : 385 - 395
  • [24] Predicting Fibrous Filter’s Efficiency by Two Methods: Artificial Neural Network (ANN) and Integration of Genetic Algorithm and Artificial Neural Network (GAINN)
    Abdolghader P.
    Haghighat F.
    Bahloul A.
    Bahloul, Ali (ali.bahloul@irsst.qc.ca), 2018, Springer (02) : 197 - 205
  • [25] Modeling of activity for biological samples using artificial neural network.
    Sardari, S
    Parang, K
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2003, 226 : U66 - U66
  • [26] Thermodynamic modeling of the KCl plus formamide/glucose/proline plus water ternary systems and activity coefficient prediction based on artificial neural network
    Ghalami-Choobar, Bahram
    Choobar, Behnam Ghalami
    JOURNAL OF MOLECULAR LIQUIDS, 2015, 207 : 136 - 144
  • [27] A STATE-SPACE NEURAL NETWORK FOR MODELING DYNAMICAL NONLINEAR SYSTEMS
    Amoura, Karima
    Wira, Patrice
    Djennoune, Said
    NCTA 2011: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NEURAL COMPUTATION THEORY AND APPLICATIONS, 2011, : 369 - 376
  • [28] Phase equilibrium modeling in ethanol plus congener mixtures using an artificial neural network
    Faundez, Claudio A.
    Quiero, Felipe A.
    Valderrama, Jose O.
    FLUID PHASE EQUILIBRIA, 2010, 292 (1-2) : 29 - 35
  • [29] Face recognition using state space parameters and artificial neural network classifier
    Kabeer, V.
    Narayanan, N. K.
    ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL III, PROCEEDINGS, 2007, : 250 - 254
  • [30] Modeling and predicting building's energy use with artificial neural networks: Methods and results
    Karatasou, S.
    Santamouris, M.
    Geros, V.
    ENERGY AND BUILDINGS, 2006, 38 (08) : 949 - 958
12345