RETRACTED: Free Parking Space Prediction and Reliability Analysis Based on Big Data Analysis (Retracted Article)

被引：2
|
作者：
Zhang, Chao [1 ,2 ]
Wang, Xianwei [2 ]
Ma, Zhongjing [1 ]
机构：
[1] Beijing Inst Technol, Beijing 100081, Peoples R China
[2] Changchun Univ, Sch Elect Informat Engn, Changchun 130022, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
关键词：
Predictive models; Reliability; Vehicles; Data models; Analytical models; Space exploration; Big Data; Parking guidance; prediction model; free parking spaces (FPSs); big data analysis; REGRESSION MODEL; LOT OCCUPANCY; OPTIMIZATION;
D O I：
10.1109/ACCESS.2020.2986056
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The number of free parking spaces (FPSs) is highly dynamic and stochastic, calling for a parking guidance model that enables the driver to find the right parking lot. This paper explores the distribution of FPSs number in parking lots, predicts the number of FPSs, and proposes a parking guidance model with a solving algorithm. Firstly, the number of FPSs from several parking lots was subjected to big data analysis, revealing that the hourly number of FPSs obey similar trends on different weekdays. On this basis, the data on the FPSs number of the parking lots were classified by hourly, weekly and holiday features. Whereas the FPSs number obeys the normal distribution, a parking guidance model was established with the most reliable path to forecast the number of FPSs. Then, the solving algorithm was proposed based on the reliability boundary. Finally, the effectiveness of the model and algorithm was verified through simulation. Compared with the actual data, the prediction accuracy of the model is more than 95%. The research results shed new light on the development of parking guidance systems.
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页码：66609 / 66614
页数：6
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