Visual Data Mining for Identification of Patterns and Outliers in Weather Stations' Data
نویسندگان
چکیده
Quality control of climate data of weather stations is essential to ensure reliability of research and services. A way to do it is comparing data of one station with data of close stations which somehow are expected to have similar behavior. The purpose of this work is to evaluate some visual data mining techniques to identify groupings/outliers of weather stations using historical precipitation data in a specific time interval. We present and discuss the techniques’ details, variants, results and applicability on this problem.
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