Employing fuzzy logic techniques and fuzzy neural networks to predict rainfall (mountainous region as a model)
Abstract
The research dealt with the use of Fuzzy Logic and Fuzzy Neural Network techniques to predict the possibility of rain precipitation through the digital classification of clouds using digital data for the satellite visualizations of the Meteosat satellite and within the visible and thermal spectral fields (Visible & Infrared) as well as daily data Rain amounts for the years 2006 - 2008 for the mountainous region stations from Iraq. The American satellite data, GOES, was used for the same spectral fields above as well as hourly data for the 2011 and 2012 rains for the Colorado region in the United States of America. This data was processed with a set of programs to achieve the research goal, such as Erdas 9.3, Arc GIS V.9.3, Global Mapper, Excel, Mat lab. The results of the regional stations were compared with the United States stations by conducting data checks and training and a different degree of accuracy was obtained. To classify clouds within the two regions and will be identified within the research axes.
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