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基于前馈三层神经网络模型的城市文化空间建设布局优化。

Layout Optimization of Urban Cultural Space Construction Based on Forward Three-Layer Neural Network Model.

机构信息

Zhejiang University City College, Zhejiang, Hangzhou 310015, China.

出版信息

Comput Intell Neurosci. 2022 Jun 3;2022:6558512. doi: 10.1155/2022/6558512. eCollection 2022.

DOI:10.1155/2022/6558512
PMID:35694587
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9187448/
Abstract

The change of urban cultural space layout is a multi-variable, multi-objective, and restricted research process. The optimization of urban cultural space construction and layout is a multi-objective decision-making problem that needs to be solved urgently. Based on the forward three-layer neural network theory, this paper constructs an optimization model for the construction and layout of urban cultural space evaluation of the layout of cultural space. This paper first analyzes the feasibility of combining the forward three-layer neural network model with the optimization and adjustment of cultural space layout structure. Taking the three-layer feedforward network as an example, the structure optimization model based on the forward three-layer neural network is selected, and the established model is used to reflect the internal environment of the objective world. Structure and perform dynamic simulation. In the process of simulation modeling, from the aspects of system description, model structure, logical analysis, reasoning, and interpretation, two effective computer dynamic simulation methods, namely, forward three-layer neural network model and system dynamics SD model, were carried out for theoretical comparison and identification. The experimental results show that the feasibility and calculation error of the application of the optimization model are relatively good, reaching 0.897 and 6.21%, respectively. The number of newly added cultural spaces and the expansion speed show an increasing trend, expanding at an average annual speed of about 35 km, effectively increasing the quality of regional planning and construction layout.

摘要

城市文化空间布局的改变是一个多变量、多目标、受限制的研究过程。城市文化空间建设和布局的优化是一个亟待解决的多目标决策问题。基于前向三层神经网络理论,构建了城市文化空间布局的文化空间布局建设和布局评价优化模型。本文首先分析了将前向三层神经网络模型与文化空间布局结构的优化调整相结合的可行性。以三层前馈网络为例,选择基于前向三层神经网络的结构优化模型,建立的模型用于反映客观世界的内部环境。结构并进行动态模拟。在模拟建模过程中,从系统描述、模型结构、逻辑分析、推理和解释等方面,对两种有效的计算机动态模拟方法,即前向三层神经网络模型和系统动力学 SD 模型,进行了理论比较和识别。实验结果表明,优化模型的应用具有较高的可行性和计算误差,分别达到 0.897 和 6.21%。新增文化空间数量和扩张速度呈上升趋势,平均每年以约 35km 的速度扩张,有效提高了区域规划和建设布局的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/a1b7c4c8bf6c/CIN2022-6558512.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/2e243010da8f/CIN2022-6558512.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/95498c4eee99/CIN2022-6558512.002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/59e6703b4c71/CIN2022-6558512.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/3564d0246d4c/CIN2022-6558512.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/c133e3ec8526/CIN2022-6558512.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/a1b7c4c8bf6c/CIN2022-6558512.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/2e243010da8f/CIN2022-6558512.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/95498c4eee99/CIN2022-6558512.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/756840362364/CIN2022-6558512.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/e967684564a0/CIN2022-6558512.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/076fedac02fe/CIN2022-6558512.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/59e6703b4c71/CIN2022-6558512.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/3564d0246d4c/CIN2022-6558512.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/c133e3ec8526/CIN2022-6558512.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b89/9187448/a1b7c4c8bf6c/CIN2022-6558512.009.jpg

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