{"title":"Environmental Art Design of Tourist Attractions with Regional Culture Fusion and Digital Innovation","authors":"Zhanfang Chen, Dan Song","doi":"10.2478/amns-2024-0510","DOIUrl":null,"url":null,"abstract":"\n In the rapid development of society, the combination of information technology and scenic environmental art design is getting closer, bringing a new creative perspective and broad space for the design field. This paper explores the integration path of information technology, regional culture and environmental art design based on this trend. It puts forward an innovative optimization strategy of ecological art design for tourist scenic spots and successfully applies it to scenic places. To verify the effectiveness of this design strategy, the article adopts BP neural network model. It combines it with genetic algorithm for deep optimization to enhance the objective evaluation of the design results. To verify the effectiveness of this design strategy, the article adopts the BP neural network model. It combines the genetic algorithm to optimize it in depth, enhancing the objectivity of evaluating the design results. After rigorous testing and analysis, the design strategy of this paper has achieved remarkable optimization effects in the lighting, ecological and cultural design of the scenic area, especially in the picturesque area of mountain diversity and forest landscape, showing a high degree of diversity, the average value reached 4.75% and 4.75% respectively. At the same time, the average value of the planting proportion of native tree species surpasses 4.6, which proves that the optimized design strategy plays a crucial role in protecting and enhancing the ecology and culture of the scenic spot.","PeriodicalId":52342,"journal":{"name":"Applied Mathematics and Nonlinear Sciences","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Nonlinear Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/amns-2024-0510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
In the rapid development of society, the combination of information technology and scenic environmental art design is getting closer, bringing a new creative perspective and broad space for the design field. This paper explores the integration path of information technology, regional culture and environmental art design based on this trend. It puts forward an innovative optimization strategy of ecological art design for tourist scenic spots and successfully applies it to scenic places. To verify the effectiveness of this design strategy, the article adopts BP neural network model. It combines it with genetic algorithm for deep optimization to enhance the objective evaluation of the design results. To verify the effectiveness of this design strategy, the article adopts the BP neural network model. It combines the genetic algorithm to optimize it in depth, enhancing the objectivity of evaluating the design results. After rigorous testing and analysis, the design strategy of this paper has achieved remarkable optimization effects in the lighting, ecological and cultural design of the scenic area, especially in the picturesque area of mountain diversity and forest landscape, showing a high degree of diversity, the average value reached 4.75% and 4.75% respectively. At the same time, the average value of the planting proportion of native tree species surpasses 4.6, which proves that the optimized design strategy plays a crucial role in protecting and enhancing the ecology and culture of the scenic spot.
在社会飞速发展的今天,信息技术与景区环境艺术设计的结合越来越紧密,为设计领域带来了全新的创作视角和广阔空间。本文基于这一趋势,探讨了信息技术、地域文化与环境艺术设计的融合路径。提出了旅游景区生态艺术设计的创新优化策略,并成功应用于景区。为了验证该设计策略的有效性,文章采用了 BP 神经网络模型。为了验证该设计策略的有效性,文章采用了 BP 神经网络模型,并将其与遗传算法相结合进行深度优化,以增强对设计结果的客观评价。为了验证该设计策略的有效性,文章采用了 BP 神经网络模型。它结合遗传算法进行深度优化,增强了设计结果评价的客观性。经过严格的测试和分析,本文的设计策略在景区的照明、生态和文化设计中取得了显著的优化效果,尤其是在山地多样性和森林景观的风景区中,表现出了较高的多样性,平均值分别达到了 4.75% 和 4.75%。同时,乡土树种种植比例的平均值超过了 4.6,这证明了优化设计策略在保护和提升景区生态和文化方面发挥了至关重要的作用。