  Importance of monsoon rainfall cannot be ignored as it affects round the year
activities ranging from agriculture to industrial. Accurate rainfall estimation
and prediction is very helpful in decision making in the sectors of water
resource management and agriculture. Due to dynamic nature of monsoon rainfall,
it's accurate prediction becomes very challenging task. In this paper, we
analyze and evaluate various deep learning approaches such as one dimensional
Convolutional Neutral Network, Multi-layer Perceptron and Wide Deep Neural
Networks for the prediction of summer monsoon rainfall in Indian state of
Rajasthan.For our analysis purpose we have used two different types of datasets
for our experiments. From IMD grided dataset, rainfall data of 484 coordinates
are selected which lies within the geographical boundaries of Rajasthan. We
have also collected rainfall data of 158 rain gauge station from water
resources department. The comparison of various algorithms on both these data
sets is presented in this paper and it is found that Deep Wide Neural Network
based model outperforms the other two approaches.
