基于深度学习非线性数据的现代社区可持续景观设计与公共环境感知研究

Q3 Environmental Science
Wangming Hu, Gulong Wang
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引用次数: 0

摘要

为了研究深度学习非线性数据下的现代社区可持续景观设计的影响及其在公众环境感知中的作用,本文讨论了深度学习非线性数据下的传统景观设计理念和现代社区可持续园林设计理念,并对相关要素进行了比较分析,通过统计方法分析景观建筑的功能表现和综合效果。结果具有统计学意义。通过分析验证,基于深度学习非线性数据的现代社区可持续景观设计能够更好地促进景观、人文与环境的融合,提高社区环境质量,从而改善公众身心健康,满足公众对环境的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Sustainable Landscape Design and Public Environmental Perception of Modern Communities Based on Deep Learning Nonlinear Data
In order to study the impact of modern community sustainable landscape design under deep learning nonlinear data and its role in public environmental perception, this paper discusses the traditional landscape design concept and the modern community sustainable landscape design concept under deep learning nonlinear data, and compares and analyzes the relevant elements, the functional performance of landscape architecture and the comprehensive effect through statistical methods. The results are statistically significant. Through analysis and verification, modern community sustainable landscape design based on deep learning nonlinear data can better promote the integration of landscape, humanities and environment, improve the quality of community environment, so as to improve the physical and mental health of the public and meet the public’s needs for the environment.
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来源期刊
Strategic Planning for Energy and the Environment
Strategic Planning for Energy and the Environment Environmental Science-Environmental Science (all)
CiteScore
1.50
自引率
0.00%
发文量
25
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