Prediction of Monthly Rainfall in Tamilnadu Using MSARIMA Models

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 309)

Abstract

One of the most important problems in the hydrological cycle is the prediction of rainfall. Many researchers are working hardly into it, but are still unable to get a perfect model because of its unsure and unexpected variation. Understanding the variability is very much needed because of its vast applications in real-life scenario. The prediction of seasonality is very much essential with respect to the nature of the data. In this paper, we have framed a Seasonal Autoregressive Integrated Moving-Average model with the help of a data set of sea surface temperature for a period of 59 years with a total of 708 readings.

Keywords

Seasonality Sea surface temperature Prediction 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Faculty of ComputingSathyabama UniversityChennaiIndia

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