Title :
Artificial neural networks for meteorological nowcast
Author :
Pasero, Eros ; Moniaci, Walter
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;
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2004. CIMSA. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8341-9
DOI :
10.1109/CIMSA.2004.1397226