Artificial neural networks for meteorological noweast

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.

Identifiers

DOI

10.1109/cimsa.2004.1397226

Citations and references