Online HVAC system modeling with BMS data using recurrent neural networks

E. Togashi, S. Tanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationHB 2006 - Healthy Buildings
Subtitle of host publicationCreating a Healthy Indoor Environment for People, Proceedings
Pages407-410
Number of pages4
Publication statusPublished - 2006 Dec 1
EventHealthy Buildings: Creating a Healthy Indoor Environment for People, HB 2006 - Lisboa, Portugal
Duration: 2006 Jun 42006 Jun 8

Publication series

NameHB 2006 - Healthy Buildings: Creating a Healthy Indoor Environment for People, Proceedings
Volume4

Conference

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

Keywords

  • BMS
  • Online modeling
  • Recurrent neural networks

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Online HVAC system modeling with BMS data using recurrent neural networks'. Together they form a unique fingerprint.

  • Cite this

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