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Title: Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches
Authors: Vathsala, H.
Koolagudi, S.G.
Issue Date: 2017
Citation: Theoretical and Applied Climatology, 2017, Vol.130, 43862, pp.19-33
Abstract: This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969 2005). 2016, Springer-Verlag Wien.
Appears in Collections:1. Journal Articles

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