Detecting Anomalies in Meteorological Data Using Support Vector Regression

Detecting Anomalies in Meteorological Data Using Support Vector Regression

Significant errors exist in automated meteorological data, and identifying them is very important. In this paper, we present a novel method for determining abnormal values in meteorological observations based on support vector regression (SVR). SVR is used to predict the observation value from a spa...

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Bibliographic Details
Main Authors:	Min-Ki Lee, Seung-Hyun Moon, Yourim Yoon, Yong-Hyuk Kim, Byung-Ro Moon
Format:	Article
Language:	English
Published:	Wiley 2018-01-01
Series:	Advances in Meteorology
Online Access:	http://dx.doi.org/10.1155/2018/5439256
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