Online HVAC system modeling with BMS data using recurrent neural networks

E. Togashi, Shinichi Tanabe

    研究成果: Conference contribution

    1 引用 (Scopus)

    抜粋

    This paper presents a method to develop and tune HVAC system models with BMS data using recurrent neural networks (RNN). To update RNN models automatically online, we eliminate ad hoc adjustment technique in three points. One is in selection of inputs variables. We propose a method of calculating the necessity of input variables with using connections' weights of neurons. Second is in the selection of hidden layers unit numbers. We introduce "Cross-validation" method and it gives criterion to evaluate parametric model. Last is in selection of training data. We apply cluster analysis to BMS data to evaluate scarcity of data. Proposed approaches are tested real measurements of actual buildings in Japan.

    元の言語English
    ホスト出版物のタイトルHB 2006 - Healthy Buildings: Creating a Healthy Indoor Environment for People, Proceedings
    ページ407-410
    ページ数4
    4
    出版物ステータスPublished - 2006
    イベントHealthy Buildings: Creating a Healthy Indoor Environment for People, HB 2006 - Lisboa
    継続期間: 2006 6 42006 6 8

    Other

    OtherHealthy Buildings: Creating a Healthy Indoor Environment for People, HB 2006
    Lisboa
    期間06/6/406/6/8

      フィンガープリント

    ASJC Scopus subject areas

    • Civil and Structural Engineering
    • Building and Construction
    • Health, Toxicology and Mutagenesis

    これを引用

    Togashi, E., & Tanabe, S. (2006). Online HVAC system modeling with BMS data using recurrent neural networks. : HB 2006 - Healthy Buildings: Creating a Healthy Indoor Environment for People, Proceedings (巻 4, pp. 407-410)