Natural Gas Price Prediction Using Machine Learning

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T. Sai Santhoshini, P. Chandana, V. Pragna, M. Pravallika


   Around the world, natural gas has been proposed as a means of reducing environmental pollution and increasing energy supply security. Machine learning algorithms like regressions and decision tree algorithms play a significant role in predicting natural gas prices. The R2 score is also used to compare the prices we have with our predictions. After training and testing the model, we can move on to the next step, which is evaluation. Natural gas price prediction has gradually gained popularity thanks to machine learning algorithms. In this paper, we investigate linear regression and decision tree algorithms as predictive methods for predicting the price of natural gas. The outcomes indicate the precise month, year, and day natural gas price in dollars.

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