Research on optimization method of landscape design based on computer algorithms

Traditional landscape design primarily depends on the experience and subjective judgment of designers, lacking systematic and scientific algorithmic support, making it difficult to find the optimal solution in large-scale and complex scenes. This article proposes an interactive genetic algorithm for...

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Vydáno v:Molecular & cellular biomechanics Ročník 21; číslo 3; s. 643
Hlavní autor: Zhang, Wei
Médium: Journal Article
Jazyk:angličtina
Vydáno: 20.11.2024
ISSN:1556-5297, 1556-5300
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Abstract Traditional landscape design primarily depends on the experience and subjective judgment of designers, lacking systematic and scientific algorithmic support, making it difficult to find the optimal solution in large-scale and complex scenes. This article proposes an interactive genetic algorithm for landscape design, which searches for the optimal solution in large-scale design spaces and improves design efficiency. Collect a large amount of landscape-related data, preprocess it, and ensure its quality, and ensure the quality of the data. Introduce elements such as plants, water bodies, and hard structures to initially design the space, extract features from landscape design images, and perform 3D reconstruction to obtain richer design space information. Generate initial design schemes using genetic algorithms and introduce subjective opinions from designers through interactive processes. The experimental results show that the average aesthetic score of interactive genetic algorithm for landscape design optimization is 9.0, and the average design time of interactive genetic algorithm is 34.5 days. Introducing the subjective opinions of designers into landscape design optimization based on heritage algorithms can effectively improve design aesthetics and shorten the total design time.
AbstractList Traditional landscape design primarily depends on the experience and subjective judgment of designers, lacking systematic and scientific algorithmic support, making it difficult to find the optimal solution in large-scale and complex scenes. This article proposes an interactive genetic algorithm for landscape design, which searches for the optimal solution in large-scale design spaces and improves design efficiency. Collect a large amount of landscape-related data, preprocess it, and ensure its quality, and ensure the quality of the data. Introduce elements such as plants, water bodies, and hard structures to initially design the space, extract features from landscape design images, and perform 3D reconstruction to obtain richer design space information. Generate initial design schemes using genetic algorithms and introduce subjective opinions from designers through interactive processes. The experimental results show that the average aesthetic score of interactive genetic algorithm for landscape design optimization is 9.0, and the average design time of interactive genetic algorithm is 34.5 days. Introducing the subjective opinions of designers into landscape design optimization based on heritage algorithms can effectively improve design aesthetics and shorten the total design time.
Author Zhang, Wei
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