![]() ![]() However, the potential of ML has not yet been fully explored in research for urban planning decision support. They have been proven to perform better than the traditional methods. ML algorithms have been proposed to model the urban form’s indicators for intelligent urban planning decision making. ![]() The emergence of such groundbreaking methods has in turn helped to address the challenges of modern-day cities in several domains (health, security, mobility, etc). The rapid growth in terms of collection and big data storage capacities combined with the ever-increasing computational power of modern machines have made possible their efficient treatment using machine (ML) and deep learning (DL) algorithms. With the integration of new communication and information technologies (Smartphone, GIS, Drones, IoT, Sensors, etc.), urban activities have generated large volumes of urban data. Urban planners and designers must develop urban forms that address these challenges. Modern cities dynamically face several challenges including digitalization, sustainability, resilience and economic development. ![]()
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