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http://dx.doi.org/10.5391/JKIIS.2014.24.5.562

Design of Meteorological Radar Echo Classifier Using Fuzzy Relation-based Neural Networks : A Comparative Studies of Echo Judgement Modules  

Ko, Jun-Hyun (Dept of Electrical Engineering, The University of Suwon)
Song, Chan-Seok (Dept of Electrical Engineering, The University of Suwon)
Oh, Sung-Kwun (Dept of Electrical Engineering, The University of Suwon)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.24, no.5, 2014 , pp. 562-568 More about this Journal
Abstract
There exist precipitation echo and non-precipitation echo in the meteorological radar. It is difficult to effectively issue the right weather forecast because of a difficulty in determining these ambiguous point. In this study, Data is extracted from UF data of meteorological radar used. Input and output data for designing two classifier were built up through the analysis of the characteristics of precipitation and non-precipitation. Selected input variables are considered for better performance and echo classifier is designed using fuzzy relation-based nueral network. Comparative studies on the performance of echo classifier are carried out by considering both echo judgement module 1 and module 2.
Keywords
UF Data of Meteorological radar; Fuzzy Neural Network classifier; Echo Judgement modules; LSE;
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