Forecasting Meteorological Analysis using Machine Learning Algorithms

Abstract

Weather prediction is gaining up ubiquity quickly in the current period of Machine learning and Technologies. It is fundamental to foresee the temperature of the climate for quite a while. Decision trees, K-NN, Random Forest algorithms are an integral asset which has been utilized in several prediction works for instance, flood prediction, storm detection etc. In this paper, a simple approach for weather prediction of future years by utilizing the past data analysis is proposed by the decision tree, K-NN and random forest algorithm calculations and showing the best accuracy result of these three algorithms. Weather prediction plays a significant job in everyday applications and in this paper the prediction is done based on the temperature changes of the certain area. All these algorithms calculate the mean values, median, confidence values, probability and show the difference between plots of all the three algorithms etc. Finally, using these algorithms in this work we can predict whether the temperature increases or decreases, is it a rainy day or not. The dataset is completely based on the weather of certain area including few objects like year, month, and temperature, predicted values and so on.