An Intelligent Framework for Estimating the International Value of Iranian Natural Gas Using Artificial Intelligence Based on Global Indicators and Geopolitical Factors

This supplementary material accompanies the main article and contains all 15 images and 15 tables from the original paper. The content provides detailed technical information, high-resolution figures, and comprehensive data tables to support the findings presented in the main article. Contents include: Figures (15 files): Natural gas price trends (1998–2026) Mediator variable effects and expert system moderation Conceptual framework architecture Hybrid artificial intelligence system (HAIS) structure ANN forecast comparisons (actual vs. predicted) Neural network training and validation error curves Hybrid AI forecasting computational flow diagram Rule-based expert system architecture Web-based text mining processing stages Global market reference price (P_Global) vs. estimated Iranian gas value (P_Iran) Tables (15 tables): Fundamental comparison of crude oil vs. natural gas Independent variables (21 factors) Gas price forecasting results (January 2020 – May 2026) Sanctions-related variables Political and geopolitical variables Infrastructure and technical variables Target market variables Normal rules in the knowledge base (27 rules) Iran-oriented expert system rules Scenario analysis (5 scenarios) Keywords: Natural Gas Price Forecasting, Hybrid Artificial Intelligence, Artificial Neural Network (ANN), Expert System, Text Mining, Iran, South Pars, Sanctions Analysis, Energy Economics License: Creative Commons Attribution 4.0 International (CC BY)