Combining geographic information and climate data to develop urban building energy prediction models in Taichung, Taiwan

被引：0
|
作者：
Chang, Cing [1 ]
Chen, Chieh-Yu [1 ]
Lin, Tzu-Ping [1 ]
机构：
[1] Department of Architecture, National Cheng Kung University, No.1, University Road, Tainan City,701, Taiwan
来源：
Sustainable Cities and Society | 2024年 / 117卷
关键词：
D O I：
10.1016/j.scs.2024.105949
中图分类号：
学科分类号：
摘要：
46
引用
收藏
相关论文
共 44 条
  • [41] Artificial Neural Network-Based Residential Energy Consumption Prediction Models Considering Residential Building Information and User Features in South Korea
    Kim, Mansu
    Jung, Sungwon
    Kang, Joo-won
    SUSTAINABILITY, 2020, 12 (01)
  • [42] Systematic review of the efficacy of data-driven urban building energy models during extreme heat in cities: Current trends and future outlook
    Nilabhra Mondal
    Prashant Anand
    Ansar Khan
    Chirag Deb
    David Cheong
    Chandra Sekhar
    Dev Niyogi
    Mattheos Santamouris
    Building Simulation, 2024, 17 : 695 - 722
  • [43] Systematic review of the efficacy of data-driven urban building energy models during extreme heat in cities: Current trends and future outlook
    Mondal, Nilabhra
    Anand, Prashant
    Khan, Ansar
    Deb, Chirag
    Cheong, David
    Sekhar, Chandra
    Niyogi, Dev
    Santamouris, Mattheos
    BUILDING SIMULATION, 2024, 17 (05) : 695 - 722
  • [44] Urban micro-climate prediction through long short-term memory network with long-term monitoring for on-site building energy estimation
    Zhang, Muxing
    Zhang, Xiaosong
    Guo, Siyi
    Xu, Xiaodong
    Chen, Jiayu
    Wang, Wei
    SUSTAINABLE CITIES AND SOCIETY, 2021, 74
12345