Analysis on a New Machine Learning-Based Artificial Neural Network Technique for Natural Gas Price Prediction

People use natural gas widely since it is the cleanest energy source. As the world's population grows, natural gas is becoming one of the most important energy sources. It is suggested as one of the ways to increase global environmental pollution reduction and energy production protection. Not only is it the most fuel for civilian employ, but it is moreover an essential component for many mechanical applications and the production of electricity. Because of its important natural advantages, natural gas is becoming more and more important to the future of global vitality, making research and price forecasting imperative. In competitive normal gas marketplaces, the ability to estimate characteristic gas costs has proven to be a highly valuable tool for all showcase members due to its various benefits. Machine learning algorithms have led to the development of widely used tools for estimating common gas costs. The purpose of this project is to investigate data-driven predictive models based on popular ML methods, such as ANN, for common gas cost estimation.