Exploring the Application of Artificial Intelligence in Understanding Urban Spaces (Case Study: Zanjan City)

This study examines the application of artificial intelligence in analyzing and understanding the urban morphology of Zanjan. The primary objective of this research is to propose a machine learning-based framework for the structural and functional analysis of urban fabrics. The research methodology involves collecting spatial and descriptive data from the city of Zanjan, processing these data using neural network algorithms, and analyzing the results through statistical approaches. By utilizing machine learning models, spatial patterns and relationships between various urban elements are identified, and urban transformation trends are analyzed. The findings indicate that artificial intelligence algorithms can identify hidden patterns within urban fabrics, enhance the accuracy of urban data processing, and enable the prediction of future changes in urban structures. This study also highlights how the physical and functional characteristics of urban fabrics influence sustainable urban development, demonstrating the potential of artificial intelligence in optimizing urban planning processes. The results can assist policymakers and urban planners in developing more effective strategies for the intelligent management of cities, ultimately contributing to the sustainable management of urban spaces.