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	Application of DCGAN in Data Repair of Parking Lots
	Wan Zou; Huacheng Zhang; Lei Peng; Huiyun Li
	2018
会议日期	2018
会议地点	中国武夷山
英文摘要	Parking guidance system, as one of the main ways to improve urban traffic and improve people's travel efficiency, has become a hot research topic at present. Sufficient information on the number of empty parking spaces has become a necessary condition for relevant research, which is mainly obtained by sensors at the entrance and exit of the car park. However, because of the economic cost, installation and construction, it is impossible to deploy the sensor in every parking lot in the city, so there will be a large area of parking data missing in the city. This paper presents a new technology to repair the parking lot data with DCGAN(Deep Convolutional Generative Adversarial Networks). First, the parking lot is classified by the high-dimensional clustering in the geographical space and the parking data of the existing parking lot is mapped to the empty car rate curve image. The same kind of car parking rate image has been set up in DCGAN to generate the empty car rate image of this type of parking lot. Finally, the 2-D empty car rate image is mapped to one-dimensional time series. Experiments show that DCGAN has achieved good results in data repairing of parking lot.
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/13734]
专题	深圳先进技术研究院_集成所
推荐引用方式 GB/T 7714	Wan Zou,Huacheng Zhang,Lei Peng,et al. Application of DCGAN in Data Repair of Parking Lots[C]. 见:. 中国武夷山. 2018.

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