Author
Abstract
Garden landscape not only provides people with places of rest and entertainment, but also protects the natural environment and maintained ecological balance. Although the traditional garden architectural style could retain the classical landscape style, the modern garden facilities and conditions had been greatly improved, and people’s expectations for the construction level of garden landscape continued to improve. Therefore, the effect of traditional landscape design could no longer meet the requirements of social development. This article proposed an interactive genetic algorithm-based landscape space environment optimization design method, in order to provide a certain theoretical reference for landscape design. Firstly, by analyzing the relationship between landscape and buildings, the change in people’s demand for landscape space environment and the relevant characteristics of landscape, this article expounded on the basic principles and methods that landscape design should follow and gave the problems existing in landscape design. Secondly, the interactive genetic algorithm and its innovative design theory were summarized, and the optimization design method of garden landscape space environment based on interactive genetic algorithm was proposed. Finally, the evaluation index system of landscape spatial environment was constructed, and experimental analysis was carried out with a landscape design as a case. The results showed that compared with the traditional landscape design methods, the design scheme proposed in this article could achieve better evaluation results. The optimization design method of landscape space environment proposed in this article could provide some technical support and theoretical reference for landscape architecture and design.
Suggested Citation
Zhao Liu & Kai Guo, 2022.
"The Application of Genetic Algorithm in the Optimal Design of Landscape Space Environment,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, October.
Handle:
RePEc:hin:jnlmpe:8768974
DOI: 10.1155/2022/8768974
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:8768974. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.