DocumentCode
427475
Title
Artificial neural networks for meteorological nowcast
Author
Pasero, Eros ; Moniaci, Walter
fYear
2004
fDate
14-16 July 2004
Firstpage
36
Lastpage
39
Abstract
Weather forecast are a typical problem where a huge amount of data coming from different types of sensors must be elaborated by means of complex, time-consuming algorithms. This work presents a new approach where the data fusion is performed with soft computing techniques. A statistical-neural system is used to "nowcast" meteorological data measured by a weather station. The system is able to forecast the evolution of these parameters in next three hours, giving precious indications about the possibility of rain, ice, and fog in next future.
Keywords
geophysics computing; neural nets; sensor fusion; weather forecasting; artificial neural networks; data fusion; nowcast meteorological data; soft computing; statistical neural system; time consuming algorithm; weather forecast system; Artificial neural networks; Atmosphere; Atmospheric modeling; Ice; Meteorology; Optical computing; Predictive models; Roads; Snow; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Measurement Systems and Applications, 2004. CIMSA. 2004 IEEE International Conference on
Print_ISBN
0-7803-8341-9
Type
conf
DOI
10.1109/CIMSA.2004.1397226
Filename
1397226
Link To Document