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This paper introduces a method to study the relation among parameters that can cause the origin of M/X solar flares. Solar flares, especially flares of types M and X, make the Earth’s atmosphere more ionized and have an effect on radio signals, which can cause disruptions in wireless communications. This situation points out to the need for better identification of the parameters involved in M/X solar flares. The method is based on four categorical parameters and their relations. Relations are demonstrated by association rules which were extracted by the APRIORI algorithm and the most promising rules were filtered by support and confidence metrics. Results of the most promising rules had been compared by application to different periods of the 23rd and the 24th solar cycles.
association rules, solar flares, data mining
association rules, solar flares, data mining
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