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

<p>The rapid advancement of the internationalization process has led to the gradual labeling and commoditization of commercial space, which is detached from the connotation of regional culture. This paper establishes a commercial space layout model and a commercial space layout optimization design process based on Bayesian network, combined with the geometric characteristics and layout attributes of commercial space layout. It also utilizes Simpson’s index and kernel density analysis to explore the influencing factors of regional culture integration into commercial space design and finally takes the design of comprehensive commercial space with regional characteristics of culture in the Central Plains as a research case to specifically explore the feasibility of integrating regional cultural characteristics into commercial space design. The results show that in the process of designing the commercial space of regional culture in the Central Plains, the audiovisual comfort reaches its best when the space aspect ratio is about 1.42 and the color saturation is about 25.05. The layout effect is the best with a visual exposure degree of 995 for the row and column layout. The integration of regional culture into commercial space design can be referenced by this study.</p>
</abstract>

The rapid advancement of the internationalization process has led to the gradual labeling and commoditization of commercial space, which is detached from the connotation of regional culture. This paper establishes a commercial space layout model and a commercial space layout optimization design process based on Bayesian network, combined with the geometric characteristics and layout attributes of commercial space layout. It also utilizes Simpson’s index and kernel density analysis to explore the influencing factors of regional culture integration into commercial space design and finally takes the design of comprehensive commercial space with regional characteristics of culture in the Central Plains as a research case to specifically explore the feasibility of integrating regional cultural characteristics into commercial space design. The results show that in the process of designing the commercial space of regional culture in the Central Plains, the audiovisual comfort reaches its best when the space aspect ratio is about 1.42 and the color saturation is about 25.05. The layout effect is the best with a visual exposure degree of 995 for the row and column layout. The integration of regional culture into commercial space design can be referenced by this study.

The Application of Central Plains Regional Culture in Commercial Space Design under the View of Artificial Intelligence

Zhengzhou University of Economics and Business

Applied Mathematics and Nonlinear Sciences

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

The rapid advancement of the internationalization process has led to the gradual labeling and commoditization of commercial space, which is detached from the...

The Application of Central Plains Regional Culture in Commercial Space Design under the View of Artificial Intelligence

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 20 dic 2023

Accettato: 25 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0217

Parole chiave
Commercial space, Bayesian network, Spatial layout, Simpson’s index, Kernel density analysis

© 2024 Lu Yue, published by Sciendo

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

The Application of Central Plains Regional Culture in Commercial Space Design under the View of Artificial Intelligence

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 20 dic 2023

Accettato: 25 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0217

Parole chiaveCommercial space, Bayesian network, Spatial layout, Simpson’s index, Kernel density analysis

© 2024 Lu Yue, published by Sciendo

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

Parole chiave
Commercial space, Bayesian network, Spatial layout, Simpson’s index, Kernel density analysis