Trend Prediction and CAD Application of Interior Design Style Using Big Data

被引:0
|
作者
Liu Y. [1 ]
机构
[1] Department of Architecture, Henan Technical College of Construction, Zhengzhou
来源
Computer-Aided Design and Applications | 2024年 / 21卷 / S21期
关键词
Big Data; CAD; Interior Design; Trend Prediction;
D O I
10.14733/cadaps.2024.S21.259-275
中图分类号
学科分类号
摘要
CAD technology can not only improve design efficiency but also make design solutions more intuitive and realistic through technologies such as 3D modelling and virtual reality, making it easier for users to understand and choose. This article proposes a design strategy that combines big data analysis with predicting interior design style trends. Through in-depth mining of massive data, it is possible to reveal the true preferences of users, the evolution patterns of design styles, and potential market demands. Through the application of CAD technology, designers can complete design proposals more quickly and efficiently, reducing design costs and risks. By assigning computing tasks to multiple processing units for simultaneous execution or utilizing specific hardware features for acceleration, this method can complete calculations in a shorter time and further improve response speed. This interior design scheme has achieved significant success in three key areas: functionality, aesthetics, and comfort. This not only reflects the professional competence and design ability of designers but also reflects good communication and cooperation between designers and users. © 2024 U-turn Press LLC.
引用
收藏
页码:259 / 275
页数:16
相关论文
共 50 条
  • [21] Prediction Algorithm of Digital Economy Development Trend Based on Big Data
    Pan Xiangyan
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [22] TREND OF CAD FRAMEWORK AND DESIGN-DATA MANAGEMENT-SYSTEM
    TOMITA, T
    KAMBE, T
    SHARP TECHNICAL JOURNAL, 1994, (59): : 34 - 38
  • [23] Design and Application of a Prediction Model for User Purchase Intention Based on Big Data Analysis
    Zhang R.
    Zhang, Ruixue (zrx@dlnu.edu.cn); Zhang, Ruixue (zrx@dlnu.edu.cn), 1600, International Information and Engineering Technology Association (25): : 311 - 317
  • [24] Big data based stock trend prediction using deep CNN with reinforcement-LSTM model
    Ishwarappa
    Anuradha, J.
    INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2021,
  • [25] Stock Price Prediction using Artificial Neural Model: An Application of Big Data
    Shastri, Malav
    Roy, Sudipta
    Mittal, Mamta
    EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS, 2019, 6 (20) : 1 - 8
  • [26] Ecological prediction at macroscales using big data: Does sampling design matter?
    Soranno, Patricia A.
    Cheruvelil, Kendra Spence
    Liu, Boyang
    Wang, Qi
    Tan, Pang-Ning
    Zhou, Jiayu
    King, Katelyn B. S.
    McCullough, Ian M.
    Stachelek, Jemma
    Bartley, Meridith
    Filstrup, Christopher T.
    Hanks, Ephraim M.
    Lapierre, Jean-Francois
    Lottig, Noah R.
    Schliep, Erin M.
    Wagner, Tyler
    Webster, Katherine E.
    ECOLOGICAL APPLICATIONS, 2020, 30 (06)
  • [27] Visual Analysis of Brand Packaging Design Data Based on CAD and Big Data Technology
    Wang X.
    Jiang J.
    Computer-Aided Design and Applications, 2024, 21 (S21): : 309 - 324
  • [28] Learning Style Preferences of College Students Using Big Data
    Viloria, Amelec
    Petro Gonzalez, Ingrid Regina
    Pineda Lezama, Omar Bonerge
    10TH INT CONF ON EMERGING UBIQUITOUS SYST AND PERVAS NETWORKS (EUSPN-2019) / THE 9TH INT CONF ON CURRENT AND FUTURE TRENDS OF INFORMAT AND COMMUN TECHNOLOGIES IN HEALTHCARE (ICTH-2019) / AFFILIATED WORKOPS, 2019, 160 : 461 - 466
  • [29] Prediction of crop yield using big data
    Wu Fan
    Chen Chong
    Guo Xiaoling
    Yu Hua
    Wang Juyun
    2015 8TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2015, : 255 - 260
  • [30] Design and application research on data service platform for big data
    Liu, Yun-Feng
    Li, Li
    Wang, Su-Mei
    Wang, Qian-Yi
    Yang, Xu
    Ouyang, Rong-Bin
    Long, Xin-Zheng
    Tongxin Xuebao/Journal on Communications, 2013, 34 (SUPPL.2): : 170 - 174