Title :
Rainfield tracking using radial basis functions
Author :
Dell´Acqua, F. ; Gamba, P.
Author_Institution :
Dipt. di Elettronica, Pavia Univ., Italy
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.703743
