Applications of Sustainable Transportation and AI Models for Regional Economic Growth Prediction

Khalid zeghaiton chaloob; Qusay  h khalaf

Khalid zeghaiton chaloob Lecturer at Falluja University
Qusay h khalaf Ministry of Higher Education and Scientific Research, Scientific Supervision and Evaluation Authority

Keywords: Sustainable Transportation, Artificial Intelligence, Economic Growth, Cost-Benefit Analysis, Regional Development

Abstract

The interplay role between sustainable transportation infrastructure and regional economy is indispensable. It accentuates the transformative action of artificial intelligence (AI) in predictive economic modeling. Analyzing the economic impacts on the transport systems (highway, railway, maritime, and airways) highlights how transport modes deepen the connectivity, reduce costs, and stimulate growth in various industries. Cost-Benefit Analysis (CBA) and Computable General Equilibrium (CGE) are frameworks that frequently implemented to evaluating empirical models. Advanced AI models explored covering transformer models and federated learning to forecast economic trends with higher accuracy. Four case studies reviewed from regions including Brazil, India, South Africa, and Japan. The findings emphasize essential integrating of AI with traditional statistical models addressing data complexity and improving policy making. Our contribution is to present the adopted sustainable development and technological innovation in economic planning.

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