IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-15-8892-1_119.html
   My bibliography  Save this book chapter

Research on Energy Consumption Analysis and Optimization of Dormitory Buildings Based on Data Mining

In: Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Jiayuan Wang

    (Shenzhen University)

  • Zhuoling Zhong

    (Shenzhen University)

  • Cheng Fan

    (Shenzhen University)

  • Bo Yu

    (Shenzhen University)

  • Yong Sun

    (Shenzhen University)

Abstract

Data mining (DM) is gradually applied to building energy domain with its high efficiency and intelligence to solve the problems that traditional statistical methods can’t effectively identify hidden knowledge in massive data. This study aims to construct a DM framework to analyze and optimize the dormitory building energy consumption. The daily energy consumption of each dormitory is recorded by smart meters in real time. Combining with the student basic information, the exploration analysis, cluster analysis, and decision tree are used to explore the students’ energy consumption characteristics. Finally, a dynamic optimization model is built to optimize the building energy. The results show that it can achieve energy saving potential of 15.8% through change the allocation of students, which is conducive to building energy efficiency.

Suggested Citation

  • Jiayuan Wang & Zhuoling Zhong & Cheng Fan & Bo Yu & Yong Sun, 2021. "Research on Energy Consumption Analysis and Optimization of Dormitory Buildings Based on Data Mining," Springer Books, in: Gui Ye & Hongping Yuan & Jian Zuo (ed.), Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, pages 1695-1710, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-8892-1_119
    DOI: 10.1007/978-981-15-8892-1_119
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-15-8892-1_119. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.