DocumentCode :
578408
Title :
Strong convective echoes identification based on rough set theory
Author :
Lu, Zhi-ying ; Wang, Jian-pei
Author_Institution :
Dept. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
Volume :
4
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
1345
Lastpage :
1349
Abstract :
In this paper radar reflectivity image, a range of weather conditions, and image processing technology were applied to extract features of strong convective echoes (hail, torrential rain) from the radar images. Area, vertically integrated liquid water (VIL), vertically integrated liquid water density (VTLD) and other features were obtained to construct the characteristic database. Rough set theory was used to dig out useful rules that can form the knowledge base, thereby the objective model of identifying strong convection weather was established. Finally the objective model was used to identify and forecast hail and torrential rain. Test results indicated that the three features properties of hail and torrential rain had effective recognition results, and prediction accuracy was 76.25% which meets the requirements of preliminary classification.
Keywords :
radar imaging; rough set theory; convective echoes identification; image processing technology; radar reflectivity image; rough set theory; vertically integrated liquid water; weather conditions; Abstracts; Accuracy; Feature extraction; Uncertainty; Feature extraction; Rough sets; Strong convective echoes; Vertically Integrated Liquid water Density (VTLD);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6359560
Filename :
6359560
Link To Document :
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