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 language | English |
|---|---|
| Pages (from-to) | 3192-3200 |
| Number of pages | 9 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E97D |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2014 Dec 1 |
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Keywords
- Energy saving system
- Office lighting
- Radial basis function neural networks
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Software
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition
Cite this
Illumination modeling method for office lighting control by using RBFNN. / Si, Wa; Pan, Xun; Ogai, Harutoshi; Hirai, Katsumi; Yamauchi, Noriyoshi; Li, Tansheng.
In: IEICE Transactions on Information and Systems, Vol. E97D, No. 12, 01.12.2014, p. 3192-3200.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Illumination modeling method for office lighting control by using RBFNN
AU - Si, Wa
AU - Pan, Xun
AU - Ogai, Harutoshi
AU - Hirai, Katsumi
AU - Yamauchi, Noriyoshi
AU - Li, Tansheng
PY - 2014/12/1
Y1 - 2014/12/1
N2 - 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.
AB - 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.
KW - Energy saving system
KW - Office lighting
KW - Radial basis function neural networks
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U2 - 10.1587/transinf.2013EDP7384
DO - 10.1587/transinf.2013EDP7384
M3 - Article
VL - E97D
SP - 3192
EP - 3200
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 12
ER -