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 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.

Authors

Publication Details

Journal
Molecular & cellular biomechanics
Published
2024-11-20
DOI
https://doi.org/10.62617/mcb643
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on optimization method of landscape design based on computer algorithms

Wei Zhang
Molecular & cellular biomechanics
Digital Media and Visual Art
article

Research on optimization method of landscape design based on computer algorithms

Wei Zhang
article en

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.

Molecular & cellular biomechanicsVol. 21(3)
Sustainable cities and communities
Openalex Percentile: Top 58%
Digital Media and Visual Art
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