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《Journal of Jiangxi Normal University(Natural Science Edition)》 2017-06
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The Study on Lighting System of Urban Street Lamp Based on DAG-SVM Algorithm

WANG Feiwen;WANG Zhonghua;School of Information Engineering,Nanchang Hangkong University;  
Aiming at the power waste and low intelligent degree after using the manual,inductive and timing control methods,the lighting system of urban street lamp is studied. The system consists of fourtier structures of street node controller,centralized controller,cloud server and backstage management system. Depended on the system structure,the six classification dimming of directed acyclic graph support vector machine( DAG-SVM) algorithm is proposed. Firstly,the six classification hyperplanes are constructed according to the different environment data around street lamps; secondly,the six classification dimming model by using the classification hyperplane training is used to judge the dimming level of street lamps. Experimental results show that compared with the manual,inductive and timing control methods,the street lighting system adopted DAG-SVM algorithm can not only be more intelligent and accurate,but also improve the system energy efficiency increased by 57. 5 percent,14. 5 percent and 5. 0 percent,saved up to 63 percent.
【Fund】: 国家自然科学基金(61362036);; 研究生创新专项基金(YC2016045)资助项目
【CateGory Index】: TP273;TU113.666
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