Elucidating the role of topological pattern discovery and support vector machine in generating predictive models for Indian summer monsoon rainfall

摘要: The present paper reports a study, where growing hierarchical self-organising map (GHSOM) has been applied to achieve visual cluster analysis the Indian rainfall dataset consisting of 142 years data so that yearly can be segregated into small groups visualise pattern clustering behaviour due changes in monthly for each year. Also, through support vector machine (SVM), it observed generation clusters impacts positively on prediction summer monsoon rainfall. Results have presented statistical and graphical analyses.