Abstract
Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and
timely rainfall prediction can be very helpful to take effective security measures in dvance
regarding: on-going construction projects, transportation activities, agricultural tasks, flight
operations and flood situation, etc. Data mining techniques can effectively predict the rainfall
by extracting the hidden patterns among available features of past weather data. This research
contributes by providing a critical analysis and review of latest data mining techniques, used for
rainfall prediction. In our proposed system we propose a new forecasting method that uses a
Convolutional Neural Network monthly rainfall for a selected location. In our proposed system
we are going to forecast the rainfall result based on the mean square error, mean absolute
error and root mean square error, which we get in train and test of the dataset based deep
learning technique.