CN108712317B - A method and system for spatiotemporal dynamic perception of urban crowd based on mobile social network - Google Patents

A method and system for spatiotemporal dynamic perception of urban crowd based on mobile social network Download PDF

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CN108712317B
CN108712317B CN201810264531.XA CN201810264531A CN108712317B CN 108712317 B CN108712317 B CN 108712317B CN 201810264531 A CN201810264531 A CN 201810264531A CN 108712317 B CN108712317 B CN 108712317B
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王亚沙
邱昭鹏
王江涛
赵俊峰
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Abstract

本发明涉及一种基于移动社交网络的城市人群时空动态感知方法和系统。该方法的步骤包括:1)将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;2)在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;3)利用在不同感知位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。本发明每次都是选取感知收益最大的探针进行感知,仅需较少的探针数量就能感知到整个城市中用户的具体位置,并且具有良好的扩展性,能够通过大规模地动态地获取社交网络用户的时空特征来表征整个城市人群的时空动态特征。

Figure 201810264531

The present invention relates to a method and system for spatial and temporal dynamic perception of urban crowds based on a mobile social network. The steps of the method include: 1) discretizing the urban area into grids with a side length of a certain value, and taking the center position of each grid as a candidate sensing position set; 2) in the candidate sensing position set, selecting the current state that can produce the maximum sensing position The location of the income is used as the perception location, and the perception location is performed to obtain the user's distance information; 3) The user's distance information obtained at different perception locations is used to determine the specific location of each user through triangulation. The present invention selects the probe with the greatest perceptual benefit each time for perception, only needs a small number of probes to perceive the specific location of the user in the whole city, and has good scalability, and can dynamically The spatiotemporal characteristics of social network users are obtained to characterize the spatiotemporal dynamic characteristics of the entire urban population.

Figure 201810264531

Description

一种基于移动社交网络的城市人群时空动态感知方法和系统A method and system for spatiotemporal dynamic perception of urban crowd based on mobile social network

技术领域technical field

本发明涉及一种数据抓取方法,属于传感器数据处理领域,具体涉及一种基于移动社交网络的城市人群时空动态感知方法和系统。The invention relates to a data grabbing method, belonging to the field of sensor data processing, in particular to a method and system for spatial and temporal dynamic perception of urban crowds based on a mobile social network.

背景技术Background technique

城市人群的时空动态感知在城市计算等领域是一个重要的问题。基于对城市人群的时空动态感知结果,我们可以用于城市道路规划、功能区域划分、交通拥堵检测、传染病传播分析等问题。但是城市人群的时空动态感知是有挑战性的问题,如果在城市中部署有限的观测点会带来成本太高和数据稀疏等问题。而基于位置的移动社交网络已经成为人们生活的一部分,如微信等应用。这些基于位置的社交软件都具有定位功能,所以这些软件都保存有关于用户的轨迹信息,这部分用户时空动态特征能够很好的表征整个城市人群的时空动态特征。而为了保护用户隐私,应用不会显示用户的精确的经纬度位置,而只显示用户和用户之间的相对距离。通过访问应用的接口,可以获取用户之间的距离信息,但是需要根据这些距离值计算出用户的经纬度位置,相应地才能得到用户的时空动态信息。现有技术是针对一个用户的感知,而为了表征城市人群的时空特征,必然要大规模感知用户的时空特征,所以需要很高的感知效率。The spatiotemporal dynamic perception of urban crowds is an important issue in urban computing and other fields. Based on the spatiotemporal dynamic perception results of urban populations, we can use it for urban road planning, functional area division, traffic congestion detection, and infectious disease spread analysis. However, the spatial and temporal dynamic perception of urban population is a challenging problem. If limited observation points are deployed in the city, it will bring problems such as high cost and sparse data. And location-based mobile social networks have become a part of people's lives, such as WeChat and other applications. These location-based social software all have the function of positioning, so these software all save the user's trajectory information, and this part of the user's spatiotemporal dynamic characteristics can well represent the spatiotemporal dynamic characteristics of the entire urban population. In order to protect user privacy, the application will not display the user's precise latitude and longitude location, but only display the relative distance between the user and the user. By accessing the interface of the application, the distance information between users can be obtained, but the user's latitude and longitude position needs to be calculated according to these distance values, and the user's time-space dynamic information can be obtained accordingly. The prior art is aimed at the perception of one user, and in order to characterize the spatiotemporal characteristics of the urban population, the spatiotemporal characteristics of the user must be sensed on a large scale, so high perception efficiency is required.

而目前,现有技术并不存在能低成本大规模感知城市人群时空动态的技术。因此,开发一种基于移动社交网络的城市人群时空动态感知方法很有必要。At present, there is no technology that can sense the spatiotemporal dynamics of urban crowds on a large scale at a low cost. Therefore, it is necessary to develop a spatiotemporal dynamic perception method of urban crowds based on mobile social networks.

发明内容SUMMARY OF THE INVENTION

本发明主要是解决现有技术所存在的感知效率问题,提供了一种基于移动社交网络的城市人群时空动态感知方法和系统。采用该方法,能够通过大规模地动态地获取社交网络用户的时空特征来表征整个城市人群的时空动态特征。The present invention mainly solves the problem of perception efficiency existing in the prior art, and provides a method and system for spatial and temporal dynamic perception of urban crowds based on a mobile social network. With this method, the spatiotemporal dynamic characteristics of the entire urban population can be characterized by dynamically acquiring the spatiotemporal characteristics of social network users on a large scale.

本发明的上述技术问题主要是通过下述技术方案得以解决的:The above-mentioned technical problems of the present invention are mainly solved by the following technical solutions:

一种基于移动社交网络的城市人群时空动态感知方法,其步骤包括:A method for spatial and temporal dynamic perception of urban crowd based on mobile social network, the steps of which include:

1)将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;1) Discretize the urban area into grids with a side length of a certain value, and use the center position of each grid as a set of candidate perception positions;

2)在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;2) In the candidate perception location set, select the location that can generate the maximum perception benefit in the current state as the perception location, and perform perception at the perception location to obtain the distance information of the user;

3)利用在不同感知位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。3) Using the distance information of users obtained at different sensing positions, the specific position of each user is determined by triangulation.

下面具体说明上述方法。The above method will be specifically described below.

1)初始化步骤1) Initialization step

针对特定的城市,将整个城市区域离散化成边长为L的格子,将格子的中心位置作为候选感知位置集合。L可以固定为一个较小值如10米,仅需要保证当所有候选位置集合全部选中时能够定位城市中的所有用户。将用户的历史位置数据映射到相应的格子中,并计算每个用户出现在每个格子中的概率。有研究表明,用户出现在某个格子中的次数服从泊松分布,假设用户u在d天历史数据中,在第t时出现在格子c中k次,则用户在一天中第t时至少出现在格子c中一次的概率为:For a specific city, the entire urban area is discretized into a grid with side length L, and the center position of the grid is used as the set of candidate perception positions. L can be fixed to a small value such as 10 meters, and it is only necessary to ensure that all users in the city can be located when all candidate location sets are selected. Map the user's historical location data to the corresponding grid, and calculate the probability of each user appearing in each grid. Some studies have shown that the number of times a user appears in a certain grid follows a Poisson distribution. Assuming that user u appears in grid c k times in the t-th time in the d-day historical data, then the user appears at least at the t-th time in a day. The probability of being in cell c once is:

Figure BDA0001611054870000021
Figure BDA0001611054870000021

其中λu,c为用户u在格子c中出现的次数。where λ u,c is the number of times the user u appears in the grid c.

2)感知位置选取步骤2) Sensing location selection steps

该步骤用于在候选的感知位置集合中贪心选择当前最优的位置进行感知,我们称在一个感知位置进行感知是放一个探针。这一过程是一个迭代过程,每一轮选择当前状态下能够产生最大感知收益的位置进行感知。感知收益的定义和感知目标相关,感知目标是感知到城市中所有用户的具体位置,所以感知收益代表的是一个探针能够帮助定位所有用户的位置带来的帮助。如果一个探针能够感知的范围越大,能够帮助感知所有用户的帮助越大,感知到的距离信息能帮助更多的用户做三角定位,所带来的帮助越大。感知收益的具体定义如下:This step is used to greedily select the current optimal position for sensing in the set of candidate sensing positions. We call sensing at a sensing position as putting a probe. This process is an iterative process, and each round selects the position that can produce the greatest perception benefit in the current state for perception. The definition of perceived benefit is related to the perceived target. The perceived target is to perceive the specific location of all users in the city, so the perceived benefit represents the help that a probe can help to locate all users. If a probe can perceive the larger the range, the greater the help it can help to perceive all users, the perceived distance information can help more users to do triangulation, and the greater the help it brings. The specific definition of perceived benefit is as follows:

Bonus(p,S)=Utility(S∪{p})-Utility(S) (2)Bonus(p,S)=Utility(S∪{p})-Utility(S) (2)

Figure BDA0001611054870000022
Figure BDA0001611054870000022

Bonus(p,S)是加入探针p能带来的感知收益,也即感知能力Utility的差,S是已选择的探针集合,U是用户集合。感知能力由两部分组成,一部分和当前感知到的用户的状态相关,另一部分和感知范围相关。其中

Figure BDA0001611054870000023
是城市的总面积,Area(S)是已经选择的探针的感知范围的并集。每个探针都有一个圆形的感知范围,其大小由能感知到的最远的用户的距离值确定。S中所有探针的感知范围的并集就是Area(S)的大小。α是调和两个因素的权重值,其值可以通过控制变量的搜索方法来确定最优值。Bonus(p,S) is the perceptual benefit that can be brought by adding probe p, that is, the difference in perceptual ability Utility, S is the selected probe set, and U is the user set. The perception ability consists of two parts, one part is related to the current perceived user state, and the other part is related to the perception range. in
Figure BDA0001611054870000023
is the total area of the city, and Area(S) is the union of the sensing ranges of the probes that have been selected. Each probe has a circular sensing range, the size of which is determined by the distance value of the farthest user it can sense. The union of the sensing ranges of all probes in S is the size of Area(S). α is a weight value that reconciles the two factors, and its value can be determined by the search method of the control variable to determine the optimal value.

Prob(S,u,state)是S能把用户u定位到state状态的概率。每个用户只要被三个不同探针感知到,就可以利用三角定位的方法计算出用户的具体位置,所以用户有三个状态,即:只被一个探针感知到,被两个探针感知到以及被三个探针感知到。定义state的状态转移函数为:Prob(S, u, state) is the probability that S can locate the user u to the state state. As long as each user is sensed by three different probes, the user's specific location can be calculated by triangulation, so the user has three states, namely: only sensed by one probe, sensed by two probes and sensed by three probes. The state transition function that defines state is:

Figure BDA0001611054870000031
Figure BDA0001611054870000031

当用户没有被完全定位的情况下,每多被一个探针感知到,就能增加一份单位收益。而每一轮探针的选择是在探针被放到感知位置之前进行的,要估算每一个候选探针的感知收益,就需要估算每一个探针改变用户状态的概率。当p能感知到用户u,且u还未被完全定位时,p就改变了u的状态。所以通过估算p能感知u的概率Probabilityp(u),来计算Prob(p,u,state)。When the user is not fully located, each additional probe sensed by the user can increase a unit of revenue. Each round of probe selection is performed before the probe is placed in the sensing position. To estimate the sensing benefit of each candidate probe, it is necessary to estimate the probability of each probe changing the user's state. When p can perceive user u, and u has not been fully located, p changes the state of u. So Prob(p,u,state) is calculated by estimating the probability that p can perceive u, Probability p (u).

当S还未感知到u时,p能感知到u的概率需要根据历史数据进行估算,也即根据初始化步骤中的u出现在每个格子中的概率进行估算。根据上一个时刻用户的分布情况,可以估算出p的感知范围,进而根据u在格子中出现的概率,估算出u出现在p的感知范围中的概率。也即:When S has not yet perceived u, the probability that p can perceive u needs to be estimated according to historical data, that is, according to the probability of u appearing in each grid in the initialization step. According to the distribution of users at the last moment, the perceptual range of p can be estimated, and then the probability of u appearing in the perceptual range of p can be estimated according to the probability of u appearing in the grid. That is:

Figure BDA0001611054870000032
Figure BDA0001611054870000032

其中Cp是p的感知范围,Probability(u,c)代表u出现在c中的概率。where Cp is the perceptual range of p, and Probability(u, c) represents the probability of u appearing in c.

当S感知到u一次时,即之前有一个探针感知到u,此时该探针和u的距离组成的圆是u可能出现的位置,记做Candidateu,所以p能感知到u的概率是p的感知范围和圆的交集所占圆的比例,也即:When S senses u once, that is, a probe senses u before, the circle formed by the distance between the probe and u is the possible position of u, which is recorded as Candidate u , so the probability that p can sense u is the proportion of the circle occupied by the perceptual range of p and the intersection of the circle, that is:

Figure BDA0001611054870000033
Figure BDA0001611054870000033

当S感知到u两次时,此时两个探针对u的感知距离组成的两个圆的交点是u可能出现的位置,如果p的感知范围能够覆盖其中任一交点,则Probabilityp(u)=1,否则为0。When S senses u twice, the intersection of the two circles formed by the sensing distances of the two probes to u is where u may appear. If the sensing range of p can cover any of the intersections, then Probability p ( u)=1, otherwise 0.

Prob(u,state,S)代表S能将u的状态确定为state的概率,当S中新加入p的时候,则S∪{p}对u的状态确定的概率为:Prob(u, state, S) represents the probability that S can determine the state of u as state. When p is newly added to S, the probability that S∪{p} determines the state of u is:

Prob(u,state,S∪{p})=1-Probabilityp(u) (7)Prob(u,state,S∪{p})=1-Probability p (u) (7)

Prob(u,Next(state),S∪{p})=Probabilityp(u) (8)Prob(u,Next(state),S∪{p})=Probability p (u) (8)

也即当p能感知到u时,u的状态发生转移,否则保持不变。That is, when p can perceive u, the state of u is transferred, otherwise it remains unchanged.

在每一轮的迭代过程中,计算所有候选探针的Bonus(p),然后选择最优的位置,通过将候选探针p的位置设置为接口的参数,请求该接口,并保存接口返回的距离结果。根据p在当前时刻的感知结果,更新每个用户的被感知状态,更新已感知的城市范围。In each round of iteration, the Bonus(p) of all candidate probes is calculated, and then the optimal position is selected. By setting the position of the candidate probe p as a parameter of the interface, request the interface, and save the returned value of the interface. distance result. According to the perception result of p at the current moment, update the perceived state of each user, and update the perceived city range.

3)迭代停止条件检查步骤3) Iterative stop condition check step

用于判断是否已经达到感知城市中所有用户的目标,是否停止迭代选取探针。为了保证能够达到感知城市中所有用户位置的目标,可以通过检查两个条件是否满足,即:已选择的探针集合S的感知范围是否覆盖整个城市;已感知到的用户是否都可以被三角定位,也即是否都被至少3个探针感知到。由于接口是返回距离探针位置最近的n个用户的距离值,且假设探针距离第n个用户为Disn,则每个探针在已经感知到距离为Disn-δ的范围内所有的用户,则当S内所有探针的Disn-δ的范围组成的并集覆盖整个城市时,整个城市内所有用户就至少被一个探针感知到。其中δ是一个固定的较小值,其大小和移动应用提供的距离精度有关,例如当距离精度为10米时,δ可以设为20米。而第二个条件的满足,就保证整个城市内所有用户都被感知到且能够被三角定位确定具体位置。It is used to judge whether the goal of sensing all users in the city has been reached, and whether to stop iteratively selecting probes. In order to ensure that the goal of sensing the locations of all users in the city can be achieved, it is possible to check whether two conditions are met, namely: whether the sensing range of the selected probe set S covers the entire city; whether all sensed users can be triangulated. , that is, whether they are all sensed by at least 3 probes. Since the interface returns the distance value of the n users closest to the probe position, and it is assumed that the probe's distance from the nth user is Dis n , then each probe has sensed all the distances within the range of Dis n -δ users, when the union of the ranges of Dis n- δ of all probes in S covers the whole city, all users in the whole city are perceived by at least one probe. Where δ is a fixed small value, and its size is related to the distance accuracy provided by the mobile application. For example, when the distance accuracy is 10 meters, δ can be set to 20 meters. The satisfaction of the second condition ensures that all users in the entire city are perceived and can be triangulated to determine the specific location.

4)三角定位步骤4) Triangulation steps

用于将距离值进行三角定位来确定每个用户的具体位置。将探针收集到的距离信息综合,每个用户至少有与之相关的3个探针以及距离值,将每个探针位置和对应的距离信息画圆,3个圆的交点或者相交区域的中心位置就是用户的具体位置。Used to triangulate distance values to determine the exact location of each user. Synthesize the distance information collected by the probes, each user has at least 3 probes and distance values related to it, draw a circle for the position of each probe and the corresponding distance information, and the intersection of the three circles or the intersection area. The central location is the specific location of the user.

一种基于移动社交网络的城市人群时空动态感知系统,其特征在于,包括:A spatiotemporal dynamic perception system for urban crowds based on a mobile social network, comprising:

候选感知位置获取单元,用于将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;The candidate perceptual position acquisition unit is used to discretize the urban area into grids with a side length of a certain value, and the center position of each grid is used as the candidate perceptual position set;

感知位置选择单元,在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;The sensing position selection unit, in the candidate sensing position set, selects the position that can generate the maximum sensing benefit in the current state as the sensing position, and performs sensing at the sensing position to obtain the distance information of the user;

定位单元,利用在感知不同位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。The positioning unit determines the specific position of each user through triangulation by using the distance information of the user obtained by sensing different positions.

与现有技术相比,本发明具有如下的优点:Compared with the prior art, the present invention has the following advantages:

1.每次都是选取感知收益最大的探针进行感知,所以仅需较少的探针数量就能感知到整个城市中用户的具体位置,也即能更少地请求应用服务器;1. Each time, the probe with the greatest perception benefit is selected for sensing, so only a small number of probes can sense the specific location of the user in the entire city, that is, fewer application servers can be requested;

2.具有良好的扩展性,能更好地扩展到其他的城市。2. It has good scalability and can be better extended to other cities.

附图说明Description of drawings

图1是本方法的流程图。Figure 1 is a flow chart of the present method.

图2是本方法在某城市的运行示例图。Figure 2 is an example diagram of the operation of the method in a certain city.

图3是本方法中用到的三角定位的示例图。Figure 3 is an example diagram of triangulation used in the method.

具体实施方法Specific implementation method

实施例一:Example 1:

图1是本实施例的感知方法的流程图。假设任务要感知某城市的城市用户的时空动态特征,方法使用者找到某移动社交网络软件的接口,使用者可以利用本方法感知该社交网络用户的时空动态特征。FIG. 1 is a flowchart of the sensing method of this embodiment. Assuming that the task is to perceive the spatiotemporal dynamic characteristics of urban users in a certain city, the method user finds the interface of a mobile social network software, and the user can use this method to perceive the spatiotemporal dynamic characteristics of the social network users.

本实施例的感知方法,包括:The sensing method of this embodiment includes:

初始化步骤,将该城市区域离散化为100米*100米的格子,并将格子的中心位置作为候选的探针位置。将用户的历史记录中的位置映射到这些格子中,统计每个用户在每个格子出现的次数,通过式(1)计算每个用户出现在每个格子中的概率。In the initialization step, the urban area is discretized into a 100m*100m grid, and the center position of the grid is used as a candidate probe position. Map the location in the user's history record to these grids, count the number of times each user appears in each grid, and calculate the probability of each user appearing in each grid by formula (1).

感知位置选取步骤,每一轮根据式(2)计算出每个候选探针的感知收益,并选择感知收益最大的探针。如图2所示,是在某城市选择探针并进行感知的过程的示例,每一个圆代表一个探针的感知范围,每一个点代表一个用户的位置,图中“1”所示的黑色的点代表还没有被感知到的用户,“2”所示的深灰色的点代表被一个或者两个探针感知到的用户,而“3”所示的浅灰色的点代表被至少三个探针感知到的用户。在选取的开始阶段中,感知范围因素在感知收益中起到更大的作用,而在用户分布较少的区域感知范围越大,所以开始阶段选取的探针都是在用户分布稀疏的区域。后续的选择也是选择感知范围和之前探针感知范围重叠不多的探针。直到所有的用户都能被至少三个探针感知到时停止。In the perceptual position selection step, each round calculates the perceptual gain of each candidate probe according to formula (2), and selects the probe with the largest perceptual gain. As shown in Figure 2, it is an example of the process of selecting probes and sensing in a city. Each circle represents the sensing range of a probe, and each point represents the location of a user. The black color indicated by "1" in the figure The dots represent users who have not been sensed yet, the dark gray dots indicated by "2" represent users who are sensed by one or two probes, and the light gray dots indicated by "3" represent users who have been sensed by at least three probes. The user perceived by the probe. In the initial stage of selection, the perception range factor plays a greater role in the perceived benefit, and the perception range is larger in the area with less user distribution, so the probes selected in the initial stage are all in the area where the user distribution is sparse. The subsequent selection is also to select the probe whose sensing range does not overlap with the sensing range of the previous probe. Stop until all users are sensed by at least three probes.

迭代停止条件检查步骤,在图2的最后一张图,所有探针的感知范围的并集覆盖了整个城市,并且所有用户都是“3”所示的浅灰色的,也即所有用户至少被3个探针感知到,迭代过程停止。The iterative stop condition checking step, in the last graph of Figure 2, the union of the sensing ranges of all probes covers the entire city, and all users are light gray as indicated by "3", that is, all users are at least 3 probes sense that the iterative process stops.

三角定位步骤,图3是一个用户的三角定位的过程,将和一个用户相关的三个圆求交点,交点就是用户的具体位置。Triangulation step, Figure 3 shows the process of triangulation of a user. The intersection of three circles related to a user is obtained, and the intersection is the specific position of the user.

对本发明的实验验证:Experimental verification of the present invention:

实验一选取某城市中252平方公里的范围,设置格子大小为100米*100米,并分别在连续5天的7点,12点以及21点进行数据感知,得到了在不同时间段内本发明的方法以及现有方法(基于单个用户的感知方法来感知整个城市用户的时空动态)感知城市范围内用户时空动态所需感知次数的平均值,如表1所示:Experiment 1 selects the area of 252 square kilometers in a city, sets the grid size to 100 meters * 100 meters, and conducts data perception at 7 o'clock, 12 o'clock and 21 o'clock for 5 consecutive days, and obtains the invention in different time periods. The method and the existing method (based on the perception method of a single user to perceive the spatiotemporal dynamics of users in the whole city), the average number of perception times required to sense the spatiotemporal dynamics of users within the city, as shown in Table 1:

表1.实验一的结果Table 1. Results of Experiment One

Figure BDA0001611054870000051
Figure BDA0001611054870000051

结果表明,本发明的方法要比现有技术能减少24.4%-26.9%的感知次数,性能优于现有技术。The results show that the method of the present invention can reduce the number of perceptions by 24.4%-26.9% compared with the prior art, and the performance is better than that of the prior art.

实验二的设置与实验一相同,通过模拟的方法将城市中用户的数量进行增加。本实验比较了两种方法在不同用户数量下的延展性。实验结果如表2所示。The setting of Experiment 2 is the same as Experiment 1, and the number of users in the city is increased by means of simulation. This experiment compares the scalability of the two methods under different numbers of users. The experimental results are shown in Table 2.

表2.实验二的结果Table 2. Results of experiment two

Figure BDA0001611054870000061
Figure BDA0001611054870000061

结果表明,本发明的方法比现有技术能减少19.4%-25.%的感知次数,性能优于现有技术。并且,随着用户数量增加,本发明方法的感知次数在线性增加,说明延展性比较好,适用于不同人口数量的城市。The results show that the method of the present invention can reduce the number of perceptions by 19.4%-25.% compared with the prior art, and the performance is better than that of the prior art. Moreover, as the number of users increases, the number of perceptions of the method of the present invention increases linearly, indicating that the ductility is relatively good, and it is suitable for cities with different populations.

实施例二:Embodiment 2:

本实施例针对另外一种返回数据类型不同的社交网络应用,通过变形感知收益函数来进行拓展。这种类型的社交网络不会返回用户间的距离的精确值,而是返回以用户为中心,一个固定值为半径的圆形范围内其他用户的列表。针对此类社交网络应用,可以将感知收益和用户被确定的范围进行联系,可定义Utility函数如下:In this embodiment, another social network application that returns different types of data is expanded through the deformation perception benefit function. This type of social network does not return an exact value of the distance between users, but returns a list of other users within a circle with a fixed radius centered on the user. For such social network applications, the perceived benefit can be linked to the user's determined range, and the utility function can be defined as follows:

Figure BDA0001611054870000062
Figure BDA0001611054870000062

其中Areau为用户u被探针集合S确定的范围的面积,其初始值为

Figure BDA0001611054870000063
定义如下:where Area u is the area of the range determined by the probe set S for user u, and its initial value is
Figure BDA0001611054870000063
Defined as follows:

Figure BDA0001611054870000064
Figure BDA0001611054870000064

其中Disk(p)为探针p的感知范围,其是以探针p的位置为中心,固定值为半径的圆。Among them, Disk(p) is the sensing range of probe p, which is a circle whose center is the position of probe p and whose fixed value is the radius.

实施例三:Embodiment three:

本实施例提供一种基于移动社交网络的城市人群时空动态感知系统,其包括:This embodiment provides a mobile social network-based spatiotemporal dynamic perception system for urban crowds, which includes:

候选感知位置获取单元,用于将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;The candidate perceptual position acquisition unit is used to discretize the urban area into grids with a side length of a certain value, and the center position of each grid is used as the candidate perceptual position set;

感知位置选择单元,在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;The sensing position selection unit, in the candidate sensing position set, selects the position that can generate the maximum sensing benefit in the current state as the sensing position, and performs sensing at the sensing position to obtain the distance information of the user;

定位单元,利用在不同感知位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。The positioning unit determines the specific position of each user through triangulation by using the distance information of the user obtained at different sensing positions.

以上实施例为本发明方法进行感知的一般过程,仅仅是对本发明的精神作举例说明。本发明所属技术领域的技术人员可以对所描述的具体实施例做各种各样的修改或补充或采用类似的方式替代,但并不会偏离本发明的精神或者超越所附权利要求书所定义的范围。The above embodiment is a general process of perception by the method of the present invention, and is only an example to illustrate the spirit of the present invention. Those skilled in the art to which the present invention pertains can make various modifications or additions to the described specific embodiments or substitute in similar manners, but will not deviate from the spirit of the present invention or go beyond the definitions of the appended claims range.

Claims (10)

1.一种基于移动社交网络的城市人群时空动态感知方法,其特征在于,包括以下步骤:1. a kind of urban crowd dynamic perception method based on mobile social network, is characterized in that, comprises the following steps: 1)将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;1) Discretize the urban area into grids with a side length of a certain value, and use the center position of each grid as a set of candidate perception positions; 2)在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;所述感知收益是一个探针对定位所有用户的位置带来的帮助,在一个感知位置进行感知称为放一个探针;将用户的历史位置数据映射到相应的格子中,并计算每个用户出现在每个格子中的概率;当探针集合S还未感知到用户u时,根据用户u出现在每个格子中的概率估算探针p能感知到u的概率;2) In the candidate sensing position set, select the position that can generate the maximum sensing benefit in the current state as the sensing position, and perform sensing at the sensing position to obtain the distance information of the user; the sensing benefit is a probe to locate all users. Bringing the help, sensing at a sensing location is called placing a probe; mapping the user's historical location data to the corresponding grid, and calculating the probability of each user appearing in each grid; when the probe set S When the user u has not yet been perceived, the probability that the probe p can perceive u is estimated according to the probability that the user u appears in each grid; 3)利用在不同感知位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。3) Using the distance information of users obtained at different sensing positions, the specific position of each user is determined by triangulation. 2.如权利要求1所述的方法,其特征在于,步骤1)将用户的历史位置数据映射到相应的格子中,并采用以下公式计算每个用户出现在每个格子中的概率:2. method as claimed in claim 1, is characterized in that, step 1) the historical position data of user is mapped in corresponding grid, and adopts following formula to calculate the probability that each user appears in each grid:
Figure FDA0002581811410000011
Figure FDA0002581811410000011
其中λu,c为用户u在格子c中出现的次数。where λ u,c is the number of times the user u appears in the grid c.
3.如权利要求1所述的方法,其特征在于,步骤2)采用迭代过程选择感知位置,在每一轮的迭代过程中选择当前状态下能够产生最大感知收益的位置进行感知,并通过检查迭代停止条件来判断是否停止迭代;所述迭代停止条件包括:已选择的探针集合的感知范围是否覆盖整个城市;已感知到的用户是否都能够被三角定位。3. method as claimed in claim 1 is characterized in that, step 2) adopts iterative process to select perceptual position, in the iterative process of each round, selects the position that can produce maximum perceptual benefit under current state to perceive, and by checking. The iteration stop condition is used to judge whether to stop the iteration; the iteration stop condition includes: whether the sensing range of the selected probe set covers the whole city; whether all the sensed users can be triangulated. 4.如权利要求3所述的方法,其特征在于,所述感知收益定义为:4. The method of claim 3, wherein the perceived benefit is defined as: Bonus(p,S)=Utility(S∪{p})-Utility(S)Bonus(p,S)=Utility(S∪{p})-Utility(S)
Figure FDA0002581811410000012
Figure FDA0002581811410000012
其中,Bonus(p,S)是加入探针p能带来的感知收益,也即感知能力Utility的差,S是已选择的探针集合;
Figure FDA0002581811410000013
是城市的总面积,Area(S)是已经选择的探针的感知范围的并集;Prob(S,u,state)是S能把用户u定位到状态state的概率,用户有三个状态:只被一个探针感知到,被两个探针感知到,以及被三个探针感知到。
Among them, Bonus(p,S) is the perceptual benefit that can be brought by adding probe p, that is, the difference in perception ability, and S is the selected probe set;
Figure FDA0002581811410000013
is the total area of the city, Area(S) is the union of the sensing ranges of the selected probes; Prob(S, u, state) is the probability that S can locate the user u to the state state, and the user has three states: only Sensed by one probe, sensed by two probes, and sensed by three probes.
5.如权利要求4所述的方法,其特征在于,当探针p能感知到用户u,且u还未被完全定位时,通过估算p能感知u的概率Probabilityp(u),来计算Prob(p,u,state)。5. The method of claim 4, wherein when the probe p can perceive the user u, and u has not been completely located, the probability p (u) that p can perceive u is calculated by estimating the probability p (u) Prob(p,u,state). 6.如权利要求5所述的方法,其特征在于,当探针集合S还未感知到u时,Probabilityp(u)根据历史数据即u出现在每个格子中的概率进行估算,计算公式为:6. The method of claim 5, wherein when the probe set S has not yet sensed u, Probability p (u) is estimated according to historical data, that is, the probability that u appears in each grid, and the calculation formula for:
Figure FDA0002581811410000021
Figure FDA0002581811410000021
其中Cp是p的感知范围,Probability(u,c)代表u出现在格子c中的概率;where C p is the perceptual range of p, and Probability(u, c) represents the probability of u appearing in grid c; 当S感知到u一次,即有一个探针感知到u时,该探针和u的距离组成的圆是u可能出现的位置,记做Candidateu,Probabilityp(u)采用下式计算:When S senses u once, that is, when a probe senses u, the circle formed by the distance between the probe and u is the possible position of u, denoted as Candidate u , and Probability p (u) is calculated by the following formula:
Figure FDA0002581811410000022
Figure FDA0002581811410000022
当S感知到u两次时,两个探针对u的感知距离组成的两个圆的交点是u可能出现的位置,如果p的感知范围能够覆盖其中任一交点,则Probabilityp(u)=1,否则为0。When S senses u twice, the intersection of the two circles formed by the sensing distances of the two probes to u is where u may appear. If the sensing range of p can cover any of the intersections, then Probability p (u) =1, otherwise 0.
7.如权利要求4所述的方法,其特征在于,在每一轮的迭代过程中,计算所有候选探针的感知收益,然后选择最优的位置;将候选探针p的位置设置为接口的参数,请求该接口并保存接口返回的距离结果;根据p在当前时刻的感知结果,更新每个用户的被感知状态,并更新已感知的城市范围。7. The method according to claim 4, characterized in that, in the iterative process of each round, the perceptual gains of all candidate probes are calculated, and then the optimal position is selected; the position of the candidate probe p is set as the interface parameter, request this interface and save the distance result returned by the interface; according to the perception result of p at the current moment, update the perceived state of each user, and update the perceived city range. 8.如权利要求1所述的方法,其特征在于,步骤3)利用每个用户的与之相关的3个探针位置以及距离值,将每个探针位置和对应的距离信息画圆,3个圆的交点或者相交区域的中心位置即为用户的具体位置。8. method as claimed in claim 1, is characterized in that, step 3) utilizes 3 probe positions and distance value relevant to it of each user, draws a circle with each probe position and corresponding distance information, The intersection of the three circles or the center position of the intersection area is the specific position of the user. 9.如权利要求1所述的方法,其特征在于,将感知收益和用户被确定的范围相联系,以获得以用户为中心,一个固定值为半径的圆形范围内其他用户的列表,定义Utility函数如下:9. The method of claim 1, wherein the perceived benefit is associated with the determined range of the user to obtain a list of other users within a circular range with a fixed value centered on the user, defining The Utility function is as follows:
Figure FDA0002581811410000023
Figure FDA0002581811410000023
其中Areau为用户u被探针集合S确定的范围的面积,其初始值为
Figure FDA0002581811410000024
定义如下:
where Area u is the area of the range determined by the probe set S for user u, and its initial value is
Figure FDA0002581811410000024
Defined as follows:
Figure FDA0002581811410000025
Figure FDA0002581811410000025
其中Disk(p)为探针p的感知范围,其是以探针p的位置为中心,固定值为半径的圆。Among them, Disk(p) is the sensing range of probe p, which is a circle whose center is the position of probe p and whose fixed value is the radius.
10.一种采用权利要求1~9中任一权利要求所述方法的基于移动社交网络的城市人群时空动态感知系统,其特征在于,包括:10 . A spatiotemporal dynamic perception system for urban crowds based on a mobile social network using the method according to any one of claims 1 to 9 , wherein: 10 . 候选感知位置获取单元,用于将城市区域离散化成边长为一定值的格子,将各格子的中心位置作为候选感知位置集合;The candidate perceptual position acquisition unit is used to discretize the urban area into grids with a side length of a certain value, and the center position of each grid is used as the candidate perceptual position set; 感知位置选择单元,在候选感知位置集合中,选择当前状态下能够产生最大感知收益的位置作为感知位置,在感知位置进行感知以获取用户的距离信息;The sensing position selection unit, in the candidate sensing position set, selects the position that can generate the maximum sensing benefit in the current state as the sensing position, and performs sensing at the sensing position to obtain the distance information of the user; 定位单元,利用在不同感知位置获得的用户的距离信息,通过三角定位来确定每个用户的具体位置。The positioning unit determines the specific position of each user through triangulation by using the distance information of the user obtained at different sensing positions.
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