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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Bibliographic Details
Main Authors: Zatsepina Aleksandra, Bardina Galina, Shindina Polina
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
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.
ISSN:2267-1242