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基于联合调度优化模型的共享汽车分析
引用本文:徐可超,王涵笑,霍思远,谷晓彤.基于联合调度优化模型的共享汽车分析[J].时代汽车,2022(1):40-41.
作者姓名:徐可超  王涵笑  霍思远  谷晓彤
作者单位:山东科技大学 山东省青岛市266510
摘    要:共享汽车行业曾在几年前广为繁荣,但由于其所具有的重模式、高成本、难以盈利等弊端,造成企业难以持续融资,行业难以持续繁荣的困境。如今,随着汽车车型更新换代日益迅速,加之疫情影响经济发展,消费者更倾向于轻便的用车模式,使得具有“分时租赁”特点的共享汽车获得很大发展机遇。本文综合利用Excel、Python软件,先以经纬度为横纵目标对附件数据进行离群值剔除与可视化展示,并将其在空间上划分成25个区域,从而更准确地研究其空间特征;其次,使用Matlab软件构建DBSCAN聚类算法模型,将不同区域共享汽车的实际密度情况以热力图形式在地图上可视展现,得出共享汽车分布主要集中在经度34.78377、纬度32.0556等区域附近,这些区域大多集中位于城市中心,人口密度相对高,共享汽车使用频率高的结论,同时编程得出不同型号车辆在整体区域信息的出现频率次数表,进行不同维度变化分析,得到共享汽车使用集中在早午晚高峰期,该时间段内人流量大,用车需求量高,汽车使用频率高的结论。

关 键 词:联合调度优化模型  共享汽车  DBSCAN  聚类算法

Analysis of Shared Cars Based on Joint Scheduling Optimization Model
Authors:Xu Kechao  Wang Hanxiao  Huo Siyuan  Gu Xiaotong
Abstract:The shared car industry once prospered a few years ago,but due to its heavy model,high cost,and difficulty in profitability,it is difficult for companies to continue financing and the industry to continue to prosper.Nowadays,with the increasingly rapid replacement of car models and the impact of the epidemic on economic development,consumers are more inclined to use the light-weight car model,making shared cars with the characteristics of“time-sharing lease”a great opportunity for development.In this paper,using Excel and Python software comprehensively,outlier removal and visual display of the attachment data are first performed with the latitude and longitude as the horizontal and vertical targets,and the space is divided into 25 regions,so as to more accurately study its spatial characteristics:secondly.Using Matlab software to build the DBSCAN clustering algorithm model,the actual density of shared cars in different areas is visually displayed on the map in the form of heat maps.It is concluded that the distribution of shared cars is mainly concentrated in areas near longitude 34.78377 and latitude 32.0556.Most of these areas is concentrated in the center of the city,the population density is relatively high,and the frequency of shared cars is high.At the same time,it is programmed to draw the frequency table of the appearance frequency of different types of vehicles in the overall area,and analyze the changes in different dimensions.It is obtained that the use of shared cars is concentrated in the morning,afternoon and evening.During the peak period,the flow of people is large,the demand for cars is high,and the frequency of car use is high.
Keywords:joint scheduling optimization model  car sharing  DBSCAN clustering algorithm
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