Implementation of data mining techniques for meteorological data analysis

Abstract

Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. Weather is one of the meteorological data that is rich by important knowledge. In this paper we try to extract useful knowledge from weather daily historical data collected locally at Gaza Strip city. The data include nine years period [1977-1985]. After data preprocessing, we apply outlier analysis, clustering, prediction, classification and association rules mining techniques. For each mining technique, we present the extracted knowledge and describe its importance in meteorological field.