Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1587/transinf.2013EDP7384 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
office lighting, energy saving system, radial basis function neural networks | Computer vision,Computer science,Artificial intelligence | Journal |
Volume | Issue | ISSN |
E97D | 12 | 1745-1361 |
Citations | PageRank | References |
2 | 0.40 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wa Si | 1 | 4 | 2.46 |
| Xun Pan | 2 | 4 | 2.46 |
| Harutoshi Ogai | 3 | 13 | 9.93 |
| Katsumi Hirai | 4 | 5 | 4.55 |
| N. Yamauchi | 5 | 4 | 1.79 |
| Tansheng Li | 6 | 7 | 1.73 |