@inproceedings{2f5b9f9752554ae987cb42a68ecba68a,
title = "Real-time daylight modeling method for lighting systems based on RBFNN",
abstract = "Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.",
keywords = "Daylight modeling, Lighting control, RBFNN",
author = "Wa Si and Xun Pan and Harutoshi Ogai",
year = "2017",
month = feb,
day = "18",
doi = "10.1145/3057039.3057100",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "318--325",
booktitle = "Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017",
note = "9th International Conference on Computer and Automation Engineering, ICCAE 2017 ; Conference date: 18-02-2017 Through 21-02-2017",
}