Abstract

The methodology of data mining techniques has been presented for the rain forecasting models for the Cuddalore (11°43′ N/79°49′ E) station of Tamilnadu in East Coast of India. Data mining approaches like classification and association mining was applied to generate results for rain prediction before 48 hour of the actual occurrence of the rain. The objective of this study is to demonstrate what relationship models are there between various atmospheric variables and to interconnect these variables according to the pattern obtained out of data mining technique. Using this approach rainfall estimates can be obtained to support the decisions to launch cloud- seeding operations. There are 3 main parts in this study. First, the obtained raw data was filtered using discretization approach based on the best fit ranges. Then, association mining has been performed on it using Predictive Apriori algorithm. Thirdly, the data has been validated using K* classifier approach. Results show that the overall classification accuracy of the data mining technique is satisfactory.

Keywords:

Apriori algorithm, association mining, classification, K* algorithm, rainfall prediction,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.