Temporal and spatial forecasting of the foF2 values up to twenty four hours in advance

Autor:	E. Tulunay, Yurdanur Tulunay, Cem Ozkaptan
Rok vydání:	2000
Předmět:	Root mean square Nonlinear system Meteorology Artificial neural network Physics::Space Physics Range (statistics) General Earth and Planetary Sciences Ionosphere Very low frequency Backpropagation Mathematics Radio wave
Zdroj:	Physics and Chemistry of the Earth, Part C: Solar, Terrestrial & Planetary Science. 25:281-285
ISSN:	1464-1917
DOI:	10.1016/s1464-1917(00)00017-9
Popis:	Radio waves of a wide range of frequencies from very low frequency (VLF) to high frequency (HF), (broadly 3 to 30 MHz) can be propagated to great distances via the ionosphere. Since the largest variability occurs in the F-region the objective of this paper is to demonstrate a neural network model with the backpropagation algorithm which is designed to forecast the foF2 values of the highly nonlinear ionosphere up to 24 hours in advance. In other words, the model forecasts all values from 1 to 24 hours ahead. By using foF2 data for three European Ionospheric stations this neural network based model can forecast foF2 values both in time and in space for those three stations. The model seems promising for practical work since the root mean square errors involved are within reasonable limits.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8a7b0dd347a6b0acaac2d0ef01b3b17a https://doi.org/10.1016/s1464-1917(00)00017-9 Zobrazit plný text záznamu Full Text from ScienceDirect