Paper Info
Title
A Neural Network Tool for the Interpolation of foF2 Data in the Presence of Sporadic E Layer.
Abstract
This paper presents the application of Neural Networks for the interpolation of (critical frequency) foF2 data over Cyprus in the presence of sporadic E layer which is a frequent phenomenon during summer months causing inevitable gaps in the foF2 data series. This ionospheric characteristic (foF2) constitutes the most important parameter in HF (High Frequency) communications since it is used to derive the optimum operating frequency in HF links and therefore interpolating missing data is very important in preserving the data series which is used in long-term prediction procedures and models.
Year
DOI
Venue
2011
10.1007/978-3-642-23957-1_35
IFIP Advances in Information and Communication Technology
Keywords
Field
DocType
Ionosphere,HF communications,F2 layer critical frequency
Data mining,Operating frequency,Computer science,Ionosphere,Interpolation,Sporadic E propagation,Data series,Critical frequency,Missing data,Artificial neural network
Conference
Volume
ISSN
Citations 
363
1868-4238
2
PageRank 
References 
Authors
0.53
2
3
Name
Order
Citations
PageRank
Haris Haralambous1366.72
Antonis Ioannou220.53
Harris Papadopoulos321926.33