<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper combines the training method of generative adversarial network and the robust row layout design method of building based on CGAN, and selects pix2pix model to carry out the spatial layout design of intelligent building, to explore the actual effect of intelligent building design. Using the building layout design of a generative adversarial network, different parameters and residual block numbers are set to compare the impact of building texture generation. The intelligent building using GAN technology is selected to carry out the spatial design characterization of both Light and shadow and luminance, and the SD spatial environment evaluation factor is used to refine the discussion of the spatial design experience of intelligent buildings designed using generative adversarial technology. The Light and shadow distribution of intelligent building design is mainly presented as four types, in which the light and shadow location types of reading room, hall, rest space and exhibition hall are primarily offered as horizontal division types. In a public intelligent building, the rest area is separated into 25% of the distance and 25% of the vertical division, with an improved design balance.</p>
</abstract>

This paper combines the training method of generative adversarial network and the robust row layout design method of building based on CGAN, and selects pix2pix model to carry out the spatial layout design of intelligent building, to explore the actual effect of intelligent building design. Using the building layout design of a generative adversarial network, different parameters and residual block numbers are set to compare the impact of building texture generation. The intelligent building using GAN technology is selected to carry out the spatial design characterization of both Light and shadow and luminance, and the SD spatial environment evaluation factor is used to refine the discussion of the spatial design experience of intelligent buildings designed using generative adversarial technology. The Light and shadow distribution of intelligent building design is mainly presented as four types, in which the light and shadow location types of reading room, hall, rest space and exhibition hall are primarily offered as horizontal division types. In a public intelligent building, the rest area is separated into 25% of the distance and 25% of the vertical division, with an improved design balance.

Analysis of the Effectiveness of Generative Adversarial Technology in Intelligent Buildings in terms of Design

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper combines the training method of generative adversarial network and the robust row layout design method of building based on CGAN, and selects...

Analysis of the Effectiveness of Generative Adversarial Technology in Intelligent Buildings in terms of Design

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 15. Apr. 2024

Akzeptiert: 24. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0934

Schlüsselwörter
CGAN, Pix2pix model, Architectural texture generation, Generative adversarial technology, SD space evaluation

© 2024 Lu Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of the Effectiveness of Generative Adversarial Technology in Intelligent Buildings in terms of Design

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 15. Apr. 2024

Akzeptiert: 24. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0934

SchlüsselwörterCGAN, Pix2pix model, Architectural texture generation, Generative adversarial technology, SD space evaluation

© 2024 Lu Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
CGAN, Pix2pix model, Architectural texture generation, Generative adversarial technology, SD space evaluation