RAINFALL PREDICTION USING MACHINE LEARNING AND DEEP LEARNING

COMPUTER ENGINEERING

Rainfall plays an important role in the formation of fauna and flora of natural life. It is not just significant for human beings but also for animals, plants and all living things. It plays a significant role in agriculture and farming . In India, Agriculture is the key point for survival and for agriculture, rainfall is most important. These days rainfall prediction has become a major problem. Prediction of rainfall gives awareness to people and they know in advance about rainfall to take certain precautions to protect their crops from rainfall. Many techniques came into existence to predict rainfall. Machine Learning algorithms are mostly useful in predicting rainfall. Some of the major Machine Learning algorithms are ARIMA Model( AutoRegressive Integrated Moving Average, Artificial Neural Network, Logistic Regression, Support Vector Machine and Self Organizing Map. Two commonly used models predict seasonal rainfall such as Linear and Non-Linear models. The first models are the ARIMA Model. While using Artificial Neural Network(ANN) predicting rainfall can be done using Back Propagation NN, Cascade NN or Layer Recurrent Network. Artificial NN is same as Biological Neural Networks

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