Research on Interior Space Design of New Rural Residential Buildings Based on Bayesian Networks
Year: 2025
Type: conference-paper
Abstract: In order to understand the research methods for interior space design of new rural residential buildings, a Bayesian network-based indoor environment space layout optimization system design is proposed. This article first completes the hardware design of the system based on Bayesian networks, by designing the basic data module, spatial layout management module, and communication link module for indoor environmental spatial layout. Secondly, by establishing an indoor environment space layout model and designing an optimization process for indoor environment space layout, the software design of the system was completed, achieving the optimization of indoor environment space layout. Finally, the test results show that when using the Bayesian network-based indoor environment space layout optimization system to optimize the indoor environment space layout, the average optimization accuracy is 98.29%; The average indoor environment spatial layout optimization accuracy of the point light source small disturbance environment spatial layout optimization system is 47.48%; The spatial layout optimization system for three-dimensional reconstruction of the spatial pattern of urban landscape interlocking zones achieved an average optimization accuracy of 69.59% when optimizing indoor spatial layout. The indoor environment space layout optimization system based on Bayesian networks can not only reduce the energy consumption of indoor environment space layout optimization, but also improve the optimization accuracy of indoor environment space layout, thereby greatly improving the performance of the indoor environment space layout optimization system.
Author: Ming Sun
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413602333