Applied Weather Forecasting using Machine Learning Approach

Weather plays an important role in our daily life. Every year, we face different types of weather conditions. So accurate weather prediction will be a great sign for us to live well. Now, the weather has an impact on the production of several primary sectors. Nowadays, the climate is changing rapidly. So previous weather forecast systems were less effective and more time-consuming. We need better and more reliable weather forecast technologies to solve these challenges. These forecasts have an impact on people's lives and the economy of a country. The primary motivation for this research is to develop a weather forecasting system that can be utilized in remote places. To determine weather conditions, we use data analytics techniques and machine learning methods to predict the weather accurately. So, in this experiment, we propose a new knowledge-based system for weather prediction using KNN, SVM, NB, DT, RF and LR for data modelling, and we got a maximum of 95.89% accuracy from the Gaussian Naive Bayes (GNB) algorithm. So, our plan is to develop weather prediction using the machine learning concept.