AI-Driven Construction and Application of Gardens: Optimizing Design and Sustainability with Machine Learning

doi:10.14569/IJACSA.2025.01602121

	AI-Driven Construction and Application of Gardens: Optimizing Design and Sustainability with Machine Learning
	Wang, Jingyi1 ; Song, Yan 2; Yang, Haozhong 1; Li, Han3 ; Zhou, Minglan 4,5
	2025
发表期刊	International Journal of Advanced Computer Science and Applications
卷号	16 期号:2 页码:1231-1239
摘要	Artificial intelligence (AI) integration into environ mental analysis has revolutionized various fields. Including the construction and application of gardens, by enabling precise classification and decision-making for sustainable practices. This paper presents a strong AI-driven framework uses convolutional neural network (CNN) and pretrained models like VGG16 and InceptionV3 to classify eight distinct environmental classes. The CNN achieved superior performance Among the tested models and reaching an impressive 98% accuracy with optimized batch sizes. This demonstrate its effectiveness for precise environmental condition classification. This work highlights the crucial role of AI in advancing the construction and application of gardens. It offers insights into optimizing garden design through accurate environmental data analysis. The diverse dataset used ensures the framework’s adaptability to real-world applications, making it a valuable resource for sustainable development and eco-friendly design strategies. This paper not only contributes to the field of AI-driven environmental analysis but also provides a foundation for future innovations in garden management and sustainability, paving the way for intelligent solutions in the evolving landscape of ecological design. © (2025), (Science and Information Organization). All rights reserved.
关键词	Convolutional neural networks - Ecodesign - Sustainable development Construc tion and application of garden design - Convolutional neural net work - Convolutional neural network - Decisions makings - Inceptionv3 - Intelligence integration - Machine-learning - Net work - Optimizing design - VGG16
DOI	10.14569/IJACSA.2025.01602121
收录类别	EI
ISSN	2158-107X
语种	英语
出版者	Science and Information Organization
EI入藏号	20251118024096
EI主题词	Adversarial machine learning
EI分类号	904 Design - 1101.2 Machine Learning - 1101.2.1 Deep Learning - 1501.1 Sustainable Development
原始文献类型	Journal article (JA)
EISSN	2156-5570
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/38944
专题	财税与公共管理学院金融学院
作者单位	1.School of Architecture, Xi’an University of Architecture & Technology, Xi’an; 710055, China; 2.Survey Institute of Shaanxi Land Engineering Construction Group, Xi’an; 710065, China; 3.CSCES AECOM CONSULTANTS CO. LTD, Lanzhou; 730000, China; 4.School of Housing, Building and Planning, Universiti Sains Malaysia, Gelugor, Penang, 11800, Malaysia; 5.School of Art, Lanzhou University of Finance and Economics, China
推荐引用方式 GB/T 7714	Wang, Jingyi,Song, Yan,Yang, Haozhong,et al. AI-Driven Construction and Application of Gardens: Optimizing Design and Sustainability with Machine Learning[J]. International Journal of Advanced Computer Science and Applications,2025,16(2):1231-1239.
APA	Wang, Jingyi,Song, Yan,Yang, Haozhong,Li, Han,&Zhou, Minglan.(2025).AI-Driven Construction and Application of Gardens: Optimizing Design and Sustainability with Machine Learning.International Journal of Advanced Computer Science and Applications,16(2),1231-1239.
MLA	Wang, Jingyi,et al."AI-Driven Construction and Application of Gardens: Optimizing Design and Sustainability with Machine Learning".International Journal of Advanced Computer Science and Applications 16.2(2025):1231-1239.