Predictive analytics

Prediction of rainfall data was done with the help of time series analysis. ARIMA is one of the models used for time series analysis. Figure 2.10 shows the normal flow of time series.

Figure 2.11 explains the decomposition of additive and multiplicative time series of rainfall data. To make the data stationary, the components such as trend, seasonality, randomness should be considered. If there is increasing trend, the amplitude of seasonality will also increase. But in our rainfall data, seasonality sometimes increases and sometimes decreases. In additive time series the components are added together but in multiplicative time series components are multiplied together and log of data series is taken.