Urban Design Sustainability Through AI and Genetic Algorithms: San Felipe Case Study

Urban Design Sustainability Through AI and Genetic Algorithms: San Felipe Case Study

Shimabukuro, Paulo

Full Article:

The research explores urban generative design in the San Felipe Residential Area using genetic algorithms, machine learning, and neural networks. Three urban scenarios are evaluated. The MEPS method (Spatial Metrics, Prediction and Segmentation) is introduced to analyze urban patterns and predict activities, producing an optimized pre-design whose urban spatial characteristics contribute to the sustainability of cities by maximizing their resources and minimizing their environmental impact.

The research explores urban generative design in the San Felipe Residential Area using genetic algorithms, machine learning, and neural networks. Three urban scenarios are evaluated. The MEPS method (Spatial Metrics, Prediction and Segmentation) is introduced to analyze urban patterns and predict activities, producing an optimized pre-design whose urban spatial characteristics contribute to the sustainability of cities by maximizing their resources and minimizing their environmental impact.

Keywords: None None

DOI: 10.5151/sigradi2023-365

Bibliographic References

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How to cite:

Shimabukuro, Paulo; "Urban Design Sustainability Through AI and Genetic Algorithms: San Felipe Case Study", p-1728-1739. In: . São Paulo: Blucher, 2024.
ISSN 23186968, DOI 10.5151/sigradi2023-365