Data Mining-based Enhancement of Environmental Art Design

被引：0
作者：
Zhang S. [1 ]
Xu C. [2 ]
机构：
[1] School of Art, Anhui Jianzhu University, Anhui, Hefei
[2] School of Marxism, Anhui Jianzhu University, Anhui, Hefei
来源：
Computer-Aided Design and Applications | 2024年 / 21卷 / S19期
关键词：
CAD; Data Mining; Environmental Art Design; Fuzzy Neural Network;
D O I：
10.14733/cadaps.2024.S19.132-147
中图分类号：
学科分类号：
摘要：
The core goal of environmental art design is to create a harmonious, beautiful, and functional spatial environment. Computer-aided design (CAD) technology provides a powerful creative platform for environmental art designers, enabling them to more conveniently and quickly transform their creativity into concrete 3D models. In this study, the DM algorithm is utilized to process and analyze extensive datasets within the CAD environment, enabling the extraction of valuable insights. Additionally, we introduce the Fuzzy Neural Network (FNN) to address the challenge of optimizing design parameters in environmental art design within the CAD context. Our method offers enhanced detail representation, improved modeling efficiency, and increased flexibility compared to traditional CAD modeling approaches. The results of our study demonstrate that the proposed method can generate more realistic and refined CAD models, significantly reducing the need for manual intervention and enhancing modeling efficiency. These advancements open up new avenues for innovation in the field of environmental art and design, contributing to improved design quality, shortened project timelines, and cost reduction. © 2024, CAD Solutions, LLC. All rights reserved.
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页码：132 / 147
页数：15
相关论文
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