Fig. 2: Analysis of research paradigms in urban planning and safety AI studies. | npj Urban Sustainability

Fig. 2: Analysis of research paradigms in urban planning and safety AI studies.

From: Bridging urban theory and artificial intelligence: a multi-agent recommendation system for sustainable city development

Fig. 2: Analysis of research paradigms in urban planning and safety AI studies.The alternative text for this image may have been generated using AI.

a Distribution of research motivations among 1,123 papers, showing the dominance of technology-driven approaches (47.3%) over problem-driven research (8.6%). b Algorithm selection criteria priorities, revealing emphasis on technical novelty (59.0%) and computational efficiency (51.3%) over domain-specific applicability (12.8%) and geographical generalizability (5.1%).

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