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基于 BP 神经网络的视觉识别在建筑设计优化中的应用。

Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization.

机构信息

School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou, Guangdong 510090, China.

Faculty of Innovation and Design, City University of Macau, Taipa, Macau 999078, China.

出版信息

Comput Intell Neurosci. 2022 Sep 30;2022:3351196. doi: 10.1155/2022/3351196. eCollection 2022.

DOI:10.1155/2022/3351196
PMID:36211004
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9546661/
Abstract

In order to establish the mapping relationship between architectural design parameters and building performance and optimize architectural design parameters, an architectural design optimization method based on BP neural network is proposed. The selected main design parameters of building ventilation include spacing coefficient, air outlet area, and height from the bottom of the window sill to the ground. Take the comprehensive performance of building ventilation design as the main optimization objective to optimize the building design. First, nine groups of samples of building optimization design are obtained through uniform experimental design. Then, based on the architectural design sample data obtained by BP neural network training, the mapping relationship between architectural design parameters and building performance is established, and based on this mapping, the optimal design parameters of the building are calculated. The research results have a certain reference value for architectural design optimization.

摘要

为了建立建筑设计参数与建筑性能之间的映射关系，并优化建筑设计参数，提出了一种基于 BP 神经网络的建筑设计优化方法。所选的建筑通风主要设计参数包括间距系数、出风口面积和窗台底部到地面的高度。以建筑通风设计的综合性能为主要优化目标来优化建筑设计。首先，通过均匀实验设计得到了九组建筑优化设计样本。然后，基于 BP 神经网络训练得到的建筑设计样本数据，建立了建筑设计参数与建筑性能之间的映射关系，并基于此映射关系，计算了建筑的最优设计参数。该研究结果对建筑设计优化具有一定的参考价值。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/9091fcb02281/CIN2022-3351196.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/e538afe715d5/CIN2022-3351196.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/c763b759773f/CIN2022-3351196.003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/83085b4d7e0d/CIN2022-3351196.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/30a074332eca/CIN2022-3351196.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc2/9546661/f9d80591c248/CIN2022-3351196.008.jpg

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