一种基于大数据聚合分析的非法加油站识别方法及应用

针对当前国内非法加油站经营隐蔽、危害大、查处难等情况,文中结合当前商用车信息化现状,提出了通过商用车运营轨迹大数据、重型柴油车燃料加注数据及车辆加油停靠行为特征(时段、时间间隔、经营区域等),提取车辆加油停靠点信息,并利用地图聚合分析算法智能识别加油站地点,剔除正常加油站点信息的方式,通过该方式获得疑似非法加油站的位置,并推送执法部门进行现场查处。文中提出的非法加油站智能识别方法在上海进行了应用,证明其能够准确提取非法加油站信息,并提交执法部门查处,为非法加油站的治理提供了有力的技术支持。

Illegal Gas Station Identification Method Based on Big Data Aggregation Analysis and Its Application

In view of the current situation of domestic illegal gas stations that the position is hidden, the harm is large and law enforcement is difficult,based on the current information status of commercial vehicle, this paper studies the method that obtains the refueling stop point of vehicle by using the big data of vehicle track, the refueling data of heavy duty diesel vehicle and the characteristic data of vehicle refueling behavior(time quantum,time interval,region etc.). First, the method identifies gas station location by map aggregation analysis algorithm, secondly, eliminates the normal gas station and obtains the illegal gas stations, finally, pushes the name list to the law enforcement departments who conduct investigation and punishment. The method of this paper is useful to be proved by application in Shanghai. The experiment in Shanghai can accurately obtain the information of illegal gas stations, and the information is provided to law enforcement authorities for investigation and punishment.