A Case Study on Natural Gas Price Prediction Using Machine Learning Algorithms

Abstract — Natural gas (also known as fossil gas) is a hydrocarbon gas mixture that occurs naturally and is mostly composed of methane. It is a clean and efficient fuel that is frequently recommended. Its price fluctuates on a daily basis, based on a variety of factors such as location, demand, and manufacturing, to name a few. In this model, we are using the Machine learning algorithms to help predict the values. We chose Decision-Tree Regression Algorithm in this model. Algorithm based on decision trees belongs to the supervised learning algorithms category. It is suitable for both continuous and intermittent use in addition to category output variables.