Publication Type:

Journal Article

Source:

International Journal of Pure and Applied Mathematics , Volume 119, Number 10, p.597-605 (2018)

URL:

https://pdfs.semanticscholar.org/0242/31397ce6f0e9c718d53d021ab1e1bc8334f3.pdf

Keywords:

fuzzy C-Mean clustering, fuzzy rule-based classification, Rainfall data

Abstract:

Rainfall becomes an important aspect in agricultural countries like India. Rainfall prognostication has become one of the most accurately and theoretically demanding issues in the world. The aim of this study is to prognosticate Kerala Monsoon rainfall with an optimized set of parameters like Sea Level Pressure (SLP), Sea Surface Temperature (SST), humidity, zonal (u), and meridional (v) winds. With the aforesaid parameters given as input to a Fuzzy Rule-based classification (FRBCS), the FRBCS classification algorithm is used for training a period of 35 years (1962-1997) summer monsoon rainfall data and validated and tested with another 15 years of (1998-2012) data using the same.

Cite this Research Publication

K. S. Varsha and Maya L. Pai, “Rainfall Prediction Using Fuzzy C-Mean Clustering And Fuzzy Rule-Based Classification”, International Journal of Pure and Applied Mathematics , vol. 119, pp. 597-605, 2018.