Toward the Association Rules of Meteorological Data Mining Based on Cloud Computing

摘要

Data mining based on association rules (AR) can find out the potential relationship among the meteorological data to forecast the weather conditions; however, it is difficult for traditional AR algorithms to meet the requirement of massive meteorological data mining. To address this issue, we propose a frequent pattern (FP)-tree algorithm based on MapReduce to forecast weather in a cloud computing system. We conduct extensive experiment with real meteorological data to evaluate the performance of our algorithm.