| id |
sigradi2023_365 |
| authors |
Shimabukuro, Paulo |
| year |
2023 |
| title |
Urban Design Sustainability Through AI and Genetic Algorithms: San Felipe Case Study |
| source |
García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1749–1760 |
| summary |
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 |
Machine Learning, Neural Networks, Genetic Algorithms, Architectural Optimization, MEPS Method |
| series |
SIGraDi |
| email |
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| full text |
 file.pdf (1,432,316 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/03/08 14:09 |
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