Enhancing Natural Gas Price Prediction: A Machine Learning and Explainable AI Approach

This research includes an innovative approach to refine natural gas price predictions by employing advanced machine learning techniques, including Random Forest, Linear Regression, and Support Vector Machine algorithms. Against the backdrop of natural gas's increasing influence in the energy sector, both environmentally and economically, the study adopts a robust methodology using a comprehensive dataset from Kaggle. Through rigorous data preprocessing, feature engineering, and model training, the chosen algorithms are optimized to capture complex patterns within the data, demonstrating the potential to significantly enhance forecast precision. The application of these techniques aims to extract meaningful insights, providing stakeholders in the natural gas market with more accurate and reliable predictions, there by contributing to a deeper understanding of market dynamics and informed decision- making.