[1] 敬舒奇, 魏东, 王旭, 等. 室内LED照明控制策略与技术研究进展[J]. 建筑科学, 2020, 36(6): 136-146.

Jing S Q, Wei D, Wang X, et al. Research progress of indoor LED lighting control strategies and technologies [J]. Building Science, 2020, 36(6): 136-146. (in Chinese)
[2] Tang S, Kalavally V, Ng K Y, et al. Development of a prototype smart home intelligent lighting control architecture using sensors onboard a mobile computing system [J]. Energy & Buildings, 2017, 138: 368-376.
[3] Silver D, Huang A, Maddison C J, et al. Mastering the game of Go with deep neural networks and tree search [J]. Nature, 2016, 529(7587): 484-489. doi:  10.1038/nature16961
[4] Patorski K, Trusiak M, Tkaczyk T. Optically-sectioned two-shot structured illumination microscopy with Hilbert-Huang processing [J]. Opt Express, 2014, 22(8): 9517-9527. doi:  10.1364/OE.22.009517
[5] Kandasamy N K, Karunagaran G, Spanos C, et al. Smart lighting system using ANN-IMC for personalized lighting control and daylight harvesting [J]. Building and Environment, 2018, 139: 170-180. doi:  10.1016/j.buildenv.2018.05.005
[6] Nagy Z, Yong F Y, Schlueter A. Occupant centered lighting control: A user study on balancing comfort, acceptance, and energy consumption [J]. Energy and Buildings, 2016, 126: 310-322. doi:  10.1016/j.enbuild.2016.05.075
[7] Paulauskaite-Taraseviciene A, Morkeviciu N, Janaviciute A, et al. The usage of artificial neural networks for intelligent lighting control based on resident’s behavioural pattern [J]. Elektronika Ir Elektrotechnika, 2015, 21(2): 72-79.
[8] Wen Y J, Agogino A M. Personalized dynamic design of networked lighting for energy-efficiency in open-plan offices [J]. Energy & Buildings, 2011, 43(8): 1919-1924.
[9] Cheng Z, Zhao Q, Wang F, et al. Satisfaction based Q-learning for integrated lighting and blind control [J]. Energy & Buildings, 2016, 127: 43-55.
[10] Yin Z D, Jiang X, Yang Z T, et al. WUB-IP: A high precision UWB positioning scheme for indoor multiuser applications [J]. IEEE Syst J, 2019, 13(1): 279-288. doi:  10.1109/JSYST.2017.2766690
[11] Wu Y, Jiang B, Lu N. A descriptor system approach for estimation of incipient faults with application to high-speed railway traction devices [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(10): 2108-2118. doi:  10.1109/TSMC.2017.2757264
[12] Xiao B, Lin Q, Chen Y. A vision-based method for automatic tracking of construction machines at nighttime based on deep learning illumination enhancement [J]. Automation in Construction, 2021, 127: 103721-1-13. doi:  10.1016/j.autcon.2021.103721
[13] 郭俊凯. 公路隧道照明精确检测与智能控制系统研究[J]. 隧道建设, 2020, 40(2): 76-81.

Guo J K. Study on lighting accurate detection and intelligent control system in highway tunnel [J]. Tunnel Construction, 2020, 40(2): 76-81. (in Chinese)
[14] 高淑芝, 李天池. 基于单片机的教室照明智能控制系统设计[J]. 控制工程, 2020, 27(11): 2010-2015.

Gao S Z, Li T C. Design of intelligent control system of classroom lighting based on single chip microcomputer [J]. Control Engineering of China, 2020, 27(11): 2010-2015. (in Chinese)
[15] 霍一, 马晓轩. ZigBee与神经网络的智能节能照明控制系统设计[J]. 现代电子技术, 2020, 43(20): 61-66.

Huo Y, Ma X X. Design of intelligent energy-saving lighting control system based on ZigBee and neural network [J]. Modern Electronics Technique, 2020, 43(20): 61-66. (in Chinese)
[16] Pandharipande A, Newsham G R. Lighting controls: Evolution and revolution [J]. Lighting Research & Technology, 2018, 50(1): 115-128.