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乡村振兴背景下生态建筑空间布局的多目标规划决策模型构建。

Construction of Multiobjective Planning Decision-Making Model of Ecological Building Spatial Layout under the Background of Rural Revitalization.

机构信息

Anhui Rural Revitalization Research Institute, Anhui, Hefei 230601, China.

Wanjiang University of Technology, Maanshan 243031, China.

出版信息

J Environ Public Health. 2022 Aug 31;2022:7021770. doi: 10.1155/2022/7021770. eCollection 2022.

DOI:10.1155/2022/7021770
PMID:36089975
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9451979/
Abstract

In order to improve the spatial layout ability of ecological buildings under the background of rural revitalization, a multiobjective planning and decision-making model for the spatial layout of ecological buildings is constructed. Based on the visual impact detection of ecological building space, a three-dimensional rendering model is established. The block matrix matching and boundary contour parameter analysis methods are used to plan and design the layout boundary feature points, and the wavelet scale decomposition method is used to analyze the mixed tone of the layout image. Based on this, a multiobjective planning decision-making model for the spatial layout of ecological buildings is established, based on which the spatial layout design scheme of ecological buildings is output to realize the spatial layout planning of ecological buildings. The simulation results show that the spatial layout of ecological buildings using this method is more reasonable, and the expression ability of ecological aesthetics is stronger, which has a good application value in rural planning and design.

摘要

为了提升乡村振兴背景下生态建筑的空间布局能力,构建了生态建筑空间的多目标规划决策模型。基于生态建筑空间的视觉冲击检测,建立了三维渲染模型。采用块矩阵匹配和边界轮廓参数分析方法,规划设计布局边界特征点,并采用小波尺度分解方法,分析布局图像的混合色调。在此基础上,建立了生态建筑空间的多目标规划决策模型,输出生态建筑的空间布局设计方案,实现生态建筑的空间布局规划。仿真结果表明,采用该方法的生态建筑空间布局更加合理,生态美学的表现力更强,在乡村规划设计中具有良好的应用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cde/9451979/68d389523bbd/JEPH2022-7021770.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cde/9451979/5e65ffac946c/JEPH2022-7021770.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cde/9451979/68d389523bbd/JEPH2022-7021770.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cde/9451979/5e65ffac946c/JEPH2022-7021770.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cde/9451979/68d389523bbd/JEPH2022-7021770.005.jpg

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