DocumentCode
3529391
Title
Rainfield tracking using radial basis functions
Author
Dell´Acqua, F. ; Gamba, P.
Author_Institution
Dipt. di Elettronica, Pavia Univ., Italy
Volume
4
fYear
1998
fDate
6-10 Jul 1998
Firstpage
2068
Abstract
In this paper a representation of the images obtained by a weather radar by means of radial basis function (RBF) neural networks is presented. A further neural step is used to forecast the movements and geometric characteristics of significant meteorological structures. This processing algorithm is applied to actual weather radar data with very good results
Keywords
atmospheric techniques; feedforward neural nets; geophysical signal processing; image representation; meteorological radar; radar imaging; rain; weather forecasting; RBF neural networks; geometric characteristics; images; meteorological structures; movements; radial basis functions; rainfield tracking; representation; weather radar; Data mining; Demand forecasting; Meteorological radar; Neural networks; Predictive models; Radar measurements; Radar tracking; Radial basis function networks; Rain; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location
Seattle, WA
Print_ISBN
0-7803-4403-0
Type
conf
DOI
10.1109/IGARSS.1998.703743
Filename
703743
Link To Document