caa a22 4500 477047491 CHVBK 20180405111334.0 cr unu---uuuuu 170330e19960201xx s 000 0 eng 10.1007/BF00876675 doi (NATIONALLICENCE)springer-10.1007/BF00876675 Thomson A. British Geological Survey, West Mains Road, EH9 3LA, Edinburgh, Scotland, UK aut Non-linear predictions of Ap by activity class and numerical value [Elektronische Daten] [A. Thomson] Two neural network algorithms are applied to the short-term,1 to 3 days, prediction of theAp geomagnetic index. A multi-layer, back-propagation (MBP) network is used to implement a self-prediction filter forAp and this provides a forecast of the numerical value of the index. A probabilistic neural network (PNN) is used to estimate the probability distribution of theAp index, in six activity classes, and to provide a forecast of the single most likely activity class for each day. BothAp and an index of solar activity, based on the daily reports issued by the Space Environment Services Centre (Boulder), are input to the probabilistic net. It is found that the numerical forecasts of the MBP filter are most accurate at low, non-storm, levels of activity. This non-linear method provides quantitatively better estimates of activity than are produced by an existing linear prediction filter, particularly with increasing forward forecasting lag. At high levels of the solar activity index the PNN is found to anticipate storm classAp with around 60% accuracy in 1992 and 1993. Some details of the algorithms and implementation issues are described. It is concluded that interplanetary field and solar wind data will be significant components of any of the possible future developments which are discussed. Birkhäuser Verlag, 1996 Ap geomagnetic index nationallicence magnetic activity forecasting nationallicence non-linear prediction nationallicence back-propagation neural network nationallicence probabilistic neural network nationallicence pure and applied geophysics Birkhäuser-Verlag 146/1(1996-02-01), 163-193 0033-4553 146:1<163 1996 146 24 https://doi.org/10.1007/BF00876675 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00876675 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Thomson A. British Geological Survey, West Mains Road, EH9 3LA, Edinburgh, Scotland, UK aut NATIONALLICENCE 773 0- pure and applied geophysics Birkhäuser-Verlag 146/1(1996-02-01), 163-193 0033-4553 146:1<163 1996 146 24 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer