Junho 2024 vol. 12 num. 3 - XXVII International Conference of the Ibero-American Society of Digital Graphics

Full Article - Open Access.

Idioma principal | Segundo idioma

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.

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.

Download (PDF)

Palavras-chave: Machine Learning, Neural Networks, Genetic Algorithms, Architectural Optimization, MEPS Method,

Palavras-chave: Machine Learning, Neural Networks, Genetic Algorithms, Architectural Optimization, MEPS Method,

DOI: 10.5151/sigradi2023-365

Referências bibliográficas
  • [1] -
Como citar:

Shimabukuro, Paulo; "Urban Design Sustainability Through AI and Genetic Algorithms: San Felipe Case Study", p. 1728-1739 . In: . São Paulo: Blucher, 2024.
ISSN 2318-6968, DOI 10.5151/sigradi2023-365

últimos 30 dias | último ano | desde a publicação


downloads


visualizações


indexações