Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
The use of neural networks in the architectural design pre-phase is becoming increasingly prevalent among designers. This article presents a method of textual and graphical analysis of construction sites using neural networks. On the example of two projects, which won the architectural competition,...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_05003.pdf |
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| Summary: | The use of neural networks in the architectural design pre-phase is becoming increasingly prevalent among designers. This article presents a method of textual and graphical analysis of construction sites using neural networks. On the example of two projects, which won the architectural competition, the following are considered: qualitative characteristics analysis of the territory using Autodesk Forma software, cultural context analysis using ChatGPT, image generation using MidJourney and 3D-models generation using the neural network Meshy.ai. In regard to ChatGPT, the "risks" method is presented as a means of achieving optimal results. The possibility of factual errors in ChatGPT text generations is indicated. |
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| ISSN: | 2267-1242 |