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Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm
There are many problems in the practical application of landscape lighting design. In order to solve these problems more specifically, based on the relevant theories of interactive genetic algorithm, radial basis function and hesitation degree are introduced into genetic algorithm. Through the analy...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424039/ https://www.ncbi.nlm.nih.gov/pubmed/36045946 http://dx.doi.org/10.1155/2022/1771617 |
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author | Shi, Haixiao Zheng, Jie |
author_facet | Shi, Haixiao Zheng, Jie |
author_sort | Shi, Haixiao |
collection | PubMed |
description | There are many problems in the practical application of landscape lighting design. In order to solve these problems more specifically, based on the relevant theories of interactive genetic algorithm, radial basis function and hesitation degree are introduced into genetic algorithm. Through the analysis and processing of the data to get the optimized interactive genetic algorithm, the algorithm can analyze and optimize the landscape lighting design. Based on this model, the lighting design can be predicted and analyzed, and the prediction result is relatively good. Relevant studies show that the interactive genetic algorithm can be divided into three typical change stages according to the different results of intensity calculation, of which the first stage mainly presents the trend of gradual decline. The fluctuation phenomenon is obvious in the second paragraph. The third paragraph shows a gradual increasing trend of change. The corresponding relationship between the two fitness functions is obvious. With the increase of experts in independent variables, the corresponding fitness values show a trend of gradual decline on the whole. Through the calculation and analysis of five different indicators of landscape lighting by using interactive genetic algorithm, it can be seen that electrification has a relatively small impact on landscape lighting. The results of intelligent and environmental protection calculation are relatively high, and the corresponding range of change is relatively large, which shows that these two indicators are very important for improving the lighting design level of landscape. Finally, the model is verified by comparing data and model curves. Interactive genetic algorithm is very important to improve the lighting design of landscape, and the optimization model can be widely used in other fields. |
format | Online Article Text |
id | pubmed-9424039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94240392022-08-30 Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm Shi, Haixiao Zheng, Jie Comput Math Methods Med Research Article There are many problems in the practical application of landscape lighting design. In order to solve these problems more specifically, based on the relevant theories of interactive genetic algorithm, radial basis function and hesitation degree are introduced into genetic algorithm. Through the analysis and processing of the data to get the optimized interactive genetic algorithm, the algorithm can analyze and optimize the landscape lighting design. Based on this model, the lighting design can be predicted and analyzed, and the prediction result is relatively good. Relevant studies show that the interactive genetic algorithm can be divided into three typical change stages according to the different results of intensity calculation, of which the first stage mainly presents the trend of gradual decline. The fluctuation phenomenon is obvious in the second paragraph. The third paragraph shows a gradual increasing trend of change. The corresponding relationship between the two fitness functions is obvious. With the increase of experts in independent variables, the corresponding fitness values show a trend of gradual decline on the whole. Through the calculation and analysis of five different indicators of landscape lighting by using interactive genetic algorithm, it can be seen that electrification has a relatively small impact on landscape lighting. The results of intelligent and environmental protection calculation are relatively high, and the corresponding range of change is relatively large, which shows that these two indicators are very important for improving the lighting design level of landscape. Finally, the model is verified by comparing data and model curves. Interactive genetic algorithm is very important to improve the lighting design of landscape, and the optimization model can be widely used in other fields. Hindawi 2022-08-22 /pmc/articles/PMC9424039/ /pubmed/36045946 http://dx.doi.org/10.1155/2022/1771617 Text en Copyright © 2022 Haixiao Shi and Jie Zheng. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Shi, Haixiao Zheng, Jie Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title | Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title_full | Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title_fullStr | Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title_full_unstemmed | Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title_short | Exploration of Landscape Lighting Design Based on Interactive Genetic Algorithm |
title_sort | exploration of landscape lighting design based on interactive genetic algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424039/ https://www.ncbi.nlm.nih.gov/pubmed/36045946 http://dx.doi.org/10.1155/2022/1771617 |
work_keys_str_mv | AT shihaixiao explorationoflandscapelightingdesignbasedoninteractivegeneticalgorithm AT zhengjie explorationoflandscapelightingdesignbasedoninteractivegeneticalgorithm |