Rainfall prediction using generative adversarial networks with convolution neural network

In recent days, deep learning becomes a successful approach to solving complex problems and analyzing the huge volume of data. The proposed system developed a rainfall prediction system using generative adversarial networks to analyze rainfall data of India and predict the future rainfall. The proposed system used a GAN network in which long short-term memory (LSTM) network algorithm is used as a generator and convolution neural network model is used as a discriminator. LSTM is much suitable to predict time series data such as rainfall data. The experimental results reveal that the proposed system provides the predicted results with 99% of accuracy. Rainfall prediction helps farmers to cultivate their crops and improved their economy as well as country's economy.