Online HVAC system modeling with BMS data using recurrent neural networks

E. Togashi*, S. Tanabe

*この研究の対応する著者

研究成果

1 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルHB 2006 - Healthy Buildings
ホスト出版物のサブタイトルCreating a Healthy Indoor Environment for People, Proceedings
ページ407-410
ページ数4
出版ステータスPublished - 2006 12 1
イベントHealthy Buildings: Creating a Healthy Indoor Environment for People, HB 2006 - Lisboa, Portugal
継続期間: 2006 6 42006 6 8

出版物シリーズ

名前HB 2006 - Healthy Buildings: Creating a Healthy Indoor Environment for People, Proceedings
4

Conference

ConferenceHealthy Buildings: Creating a Healthy Indoor Environment for People, HB 2006
国/地域Portugal
CityLisboa
Period06/6/406/6/8

ASJC Scopus subject areas

  • 土木構造工学
  • 建築および建設
  • 健康、毒物学および変異誘発

フィンガープリント

「Online HVAC system modeling with BMS data using recurrent neural networks」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル