Prediction of Monthly Rainfall in Tamilnadu Using MSARIMA Models
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.
KeywordsSeasonality Sea surface temperature Prediction
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