Illumination modeling method for office lighting control by using RBFNN

Wa Si, Xun Pan, Harutoshi Ogai, Katsumi Hirai, Noriyoshi Yamauchi, Tansheng Li

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

Original languageEnglish
Pages (from-to)3192-3200
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE97D
Issue number12
DOIs
Publication statusPublished - 2014 Dec 1

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Keywords

  • Energy saving system
  • Office lighting
  • Radial basis function neural networks

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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