Advanced Machine Learning Approach for Weather Prediction

Weather Prediction is a challenging task for all researchers of weather and the meteorological department. Many techniques are evolved in time for the prediction of weather since last many years. The advancement of science and tech- nology has helped the researchers to perform the prediction of weather simply and with less error rates. The soft computing techniques are the new technologies in computer science which are capable of making the weather prediction with promising output and less error rates. Weather prediction is done traditionally by use of many historical data in many models of physics. This prediction of weather is unsteady due to the change in weather condition. Because of change of weather system, the prediction is unstable. In this paper, we present different machine learning models that will make use of the historical data to train the models and then the model will be used to predict the weather whose accuracy is better than the traditional models. The evaluation of the models on the basis of accuracy shows that the models outperform and can be used as state-of-art technique to predict the weather in smarter way in less time. Keywords Random forest ·Decision tree · Support vector machine · Gradient boosting