Research on Intelligent Landscape Design Based on Distributed Integrated Model

IF 4.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal on Semantic Web and Information Systems Pub Date : 2023-06-21 DOI:10.4018/ijswis.325002
Xihui Tang
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引用次数: 1

Abstract

Traditional landscape design methods rely entirely on the experience of designers and are difficult to adapt to the needs of modern society. This article proposes a landscape design method based on a distributed integrated model. Based on landscape design scheme data, the intelligent landscape design function is achieved by constructing a distributed geographic model, extracting features through data analysis and key point analysis, and using virtual environments in computer-aided design to display and restore the actual effects of landscape design. The results indicate that the landscape design method based on distributed integration mode is more in line with the needs of modern society and has significant advantages over traditional landscape design in terms of public interest and evaluation coefficient. The intelligent landscape design method based on distributed integrated models has important significance in modern urbanization construction, which can effectively improve the accuracy and speed of landscape design and create better living spaces for people.
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基于分布式集成模型的智能景观设计研究
传统的景观设计方法完全依靠设计师的经验,难以适应现代社会的需求。本文提出了一种基于分布式集成模型的景观设计方法。以景观设计方案数据为基础,构建分布式地理模型,通过数据分析和关键点分析提取特征,利用计算机辅助设计中的虚拟环境来展示和还原景观设计的实际效果,实现智能景观设计功能。结果表明,基于分布式集成模式的景观设计方法更符合现代社会的需求,在公共利益和评价系数方面都比传统景观设计具有显著优势。基于分布式集成模型的智能景观设计方法在现代城市化建设中具有重要意义,可以有效提高景观设计的准确性和速度,为人们创造更好的生活空间。
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来源期刊
CiteScore
6.20
自引率
12.50%
发文量
51
审稿时长
20 months
期刊介绍: The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.
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