The invention discloses a road berth illegal occupation management method and system based on a machine learning algorithm, and relates to the field of intelligent road parking management, and the method comprises the steps: obtaining an idle berth of which the idle time is greater than or equal to a preset threshold value from each berth according to the parking data of each berth before the illegal occupation judgment; according to the parking space parking data of the idle parking spaces with the idle time larger than or equal to a preset threshold value, the occupation types of the idle parking spaces are obtained through a preset machine learning algorithm; the illegal occupation behavior of the idle parking space is processed according to the occupation type of the idle parking space so that real-time identification, acquisition and acquisition of the state of each parking space can be avoided, unnecessary operation resource waste can be reduced, misidentification of passing vehicles and non-motor vehicles can be avoided, and the accuracy of the identification of the passing vehicles and the non-motor vehicles can be enhanced. And the recognition accuracy of illegal occupation of the road berths is improved.
本发明公开一种基于机器学习算法的道路泊位违规占用管理方法及系统,涉及智能道路停车管理领域,包括:在进行违规占用判定之前,首先根据各个泊位的停车数据从所述各个泊位中获取空闲时间大于或等于预设阈值的空闲泊位;并根据所述空闲时间大于或等于预设阈值的空闲泊位的泊位停车数据,通过预置机器学习算法获取所述空闲泊位的占用类型;再根据所述空闲泊位的占用类型对所述空闲泊位的违规占用行为进行处理,可以避免实时识别获取采集各个泊位的状态,减少不必要的运算资源浪费,同时也可以避免过路车辆和非机动车辆的误识别,提升道路泊位违规占用的识别准确率。
Road berth illegal occupation management method and system based on machine learning algorithm
一种基于机器学习算法的道路泊位违规占用管理方法及系统
23.06.2023
Patent
Elektronische Ressource
Chinesisch
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