CN111785392A - Population number early warning method and device, electronic equipment and computer readable medium - Google Patents
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Abstract
The disclosure relates to a population number early warning method and device, electronic equipment and a computer readable medium, and belongs to the technical field of statistics. The method comprises the following steps: acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of each monitoring time period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period; determining population inflow threshold values and population outflow threshold values of preset areas in the current monitoring time period according to population historical data; and acquiring the current population number of the preset area in the current monitoring time period, and if the current population number is larger than a population inflow threshold value or smaller than a population outflow threshold value, early warning the population number of the preset area. According to the method and the device, the population threshold value is dynamically calculated through the periodic population historical data, the threshold value change can be dynamically adjusted according to the continuously increased historical data, and the early warning is better carried out on the flowing condition of the personnel.
Description
Technical Field
The present disclosure relates to the field of statistical techniques, and in particular, to a population number early warning method, a population number early warning device, an electronic device, and a computer-readable medium.
Background
Due to the outbreak of new crown epidemic, monitoring of personnel flow in various places is very important for epidemic prevention and control. If the flow of people is too large, the risk of further spreading of the epidemic may be increased, resulting in serious consequences.
Along with the development and repetition of epidemic situations, if the population number in a certain area is only pre-warned through a fixed threshold value, the flexibility is poor, and the requirement of epidemic situation prevention and control is far away not met due to the fact that the self-adaptive capacity is unavailable.
In view of the above, there is a need in the art for a dynamic pre-warning method for population number to better manage the flow of people during an epidemic situation.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The purpose of the present disclosure is to provide a population number early warning method, a population number early warning device, an electronic device, and a computer readable medium, so that dynamic early warning can be performed on the flow condition of people during an epidemic situation at least to a certain extent, thereby improving prevention and control of an early warning area.
According to a first aspect of the present disclosure, there is provided a method for providing an early warning of population, comprising:
acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of corresponding monitoring time periods in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period;
determining population inflow threshold values and population outflow threshold values of the preset area in the current monitoring time period according to the population historical data;
and acquiring the current population number of the preset area in the current monitoring time period, and if the current population number is larger than the population inflow threshold value or smaller than the population outflow threshold value, early warning the population number of the preset area.
In an exemplary embodiment of the present disclosure, the method further comprises:
determining the signal coverage range of each communication base station in a preset range;
and determining a plurality of preset areas according to the signal coverage range of the communication base station.
In an exemplary embodiment of the present disclosure, the determining a plurality of the preset areas according to the signal coverage of the communication base station includes:
judging whether the signal coverage area of the communication base station is overlapped with the signal coverage area of the adjacent communication base station;
if the signal coverage range of the communication base station is not overlapped with the signal coverage range of the adjacent communication base station, taking the signal coverage range of each communication base station as a preset area corresponding to the communication base station;
and if the signal coverage range of the communication base station is overlapped with the signal coverage range of the adjacent communication base station, dividing the preset area corresponding to the two adjacent communication base stations according to a perpendicular bisector of a connecting line between the two communication base stations.
In an exemplary embodiment of the disclosure, the determining, according to the population history data, an inflow of population threshold and an outflow of population threshold of the preset area in a current monitoring time period includes:
determining a mean and a standard deviation of the historical monitoring period according to the population historical data;
determining a population fluctuation threshold value of the preset area in the current monitoring time period according to the standard deviation;
and determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to the mean value and the population fluctuation threshold value.
In an exemplary embodiment of the disclosure, the determining the mean and the standard deviation of the historical monitoring period according to the demographic historical data comprises:
determining the mean and standard deviation of Gaussian distribution according to the population historical data;
and taking the mean value and the standard deviation of the Gaussian distribution as the mean value and the standard deviation of the historical monitoring period.
In an exemplary embodiment of the disclosure, the determining the population fluctuation threshold of the preset area in the current monitoring time period according to the standard deviation includes:
determining a plurality of early warning grades and a plurality of early warning grade parameters corresponding to the early warning grades;
and determining a population fluctuation threshold value of the preset area corresponding to the early warning grade in the current monitoring time period according to the product of the standard deviation and the early warning grade parameter.
In an exemplary embodiment of the disclosure, the determining the population inflow threshold and the population outflow threshold of the preset area in the current monitoring time period according to the mean and the population fluctuation threshold includes:
obtaining a population inflow threshold value of the preset area in the current monitoring time period according to the sum of the mean value and the population fluctuation threshold value;
and obtaining the population outflow threshold value of the preset area in the current monitoring time period according to the difference between the mean value and the population fluctuation threshold value.
According to a second aspect of the present disclosure, there is provided an early warning device for population, comprising:
the historical data acquisition module is used for acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of corresponding monitoring time periods in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period;
the population threshold value determining module is used for determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to the population historical data;
and the population quantity early warning module is used for acquiring the current population quantity of the preset area in the current monitoring time period, and if the current population quantity is larger than the population inflow threshold value or smaller than the population outflow threshold value, early warning is carried out on the population quantity of the preset area.
According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any of the above-described population volume pre-warning methods via execution of the executable instructions.
According to a fourth aspect of the present disclosure, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the method of population size pre-warning as set forth in any one of the above.
The exemplary embodiments of the present disclosure may have the following advantageous effects:
in the method for early warning of population quantity according to the exemplary embodiment of the disclosure, on one hand, in consideration of the periodicity of personnel flow, the population threshold value of the monitoring time period is dynamically calculated by collecting population historical data of the corresponding monitoring time period in each monitoring period according to the continuously changing periodic population historical data, so that the early warning threshold value has dynamic and adaptive capabilities, and the threshold value change can be dynamically adjusted according to the continuously increasing historical data; on the other hand, by setting the population inflow threshold value and the population outflow threshold value in the monitoring time period, early warning can be carried out when the population quantity in the region is increased or reduced, so that the monitoring mechanism of the population quantity is more perfect, and the flow condition of the personnel in the epidemic situation period is better managed.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
FIG. 1 shows a flow diagram of a population volume pre-warning method in an example embodiment of the present disclosure;
fig. 2 schematically illustrates a schematic diagram of a signal coverage of a communication base station according to an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart for determining a preset region in an example embodiment of the present disclosure;
FIG. 4 schematically illustrates a schematic diagram of partitioning regions by a Voronoi diagram algorithm, according to one embodiment of the present disclosure;
FIG. 5 schematically illustrates a region partitioned by a Voronoi diagram algorithm according to one embodiment of the present disclosure;
FIG. 6 shows a flow diagram of calculating population thresholds according to an example embodiment of the present disclosure;
FIG. 7 schematically illustrates a schematic diagram of a Gaussian distribution, according to one embodiment of the present disclosure;
FIG. 8 illustrates a flow chart for determining a population fluctuation threshold in an example embodiment of the present disclosure;
FIG. 9 shows a block diagram of a population number pre-warning device of an example embodiment of the present disclosure;
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The example embodiment first provides a population number early warning method. Referring to fig. 1, the method for warning the population number may include the following steps:
step 110, acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of corresponding monitoring time periods in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period.
And S120, determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to population historical data.
And S130, acquiring the current population number of the preset area in the current monitoring time period, and if the current population number is larger than a population inflow threshold value or smaller than a population outflow threshold value, early warning the population number of the preset area.
The population quantity early warning method in the example embodiment can be applied to regional epidemic situation monitoring in new crown epidemic situations. Due to the outbreak of new crown epidemic situations, all places are very important for monitoring the personnel mobility, and along with the development and repetition of the epidemic situations, the control on population gathering conditions should change accordingly. For example, as the epidemic is relieved, the risk level may be reduced or relieved, and the control of people gathering may become relatively loose. For example, in a severe epidemic period, more than 50 people in a certain area may be called aggregation, but after the epidemic is relieved, more than 100 people may be called aggregation. Whether the aggregation is relatively dynamic or not, and therefore a dynamic early warning method of population is needed. Of course, it may also be applied in the monitoring of other events, for example, in the monitoring of the population of a region for some special festivals.
Because the popularity of the mobile phone in the current society is very high and almost approaches to 100%, the monitoring of the mobile phone user quantity can be approximately equivalent to the monitoring of the actual population. The data of the mobile equipment counted by the base station is used for monitoring or early warning epidemic situation personnel gathering by counting the number of users in a period of time in a signal coverage area of the communication base station.
In the method for early warning of population quantity according to the exemplary embodiment of the disclosure, on one hand, in consideration of the periodicity of personnel flow, the population threshold value of the monitoring time period is dynamically calculated by collecting population historical data of the corresponding monitoring time period in each monitoring period according to the continuously changing periodic population historical data, so that the early warning threshold value has dynamic and adaptive capabilities, and the threshold value change can be dynamically adjusted according to the continuously increasing historical data; on the other hand, by setting the population inflow threshold value and the population outflow threshold value in the monitoring time period, early warning can be carried out when the population quantity in the region is increased or reduced, so that the monitoring mechanism of the population quantity is more perfect, and the flow condition of the personnel in the epidemic situation period is better managed.
Next, the above steps of the present exemplary embodiment will be described in more detail with reference to fig. 2 to 8.
In step S110, a statistical data set of the number of mobile communication devices in the historical monitoring period in the preset area is obtained, and according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period, population historical data of the corresponding monitoring time period in each historical monitoring period is determined.
In this exemplary embodiment, the preset area refers to an early warning area within a certain preset range, and may be divided according to a certain preset dividing method, for example, in an actual application, the preset area may be divided according to a residential area, an office area, and the like, or may be divided according to a location of a communication base station and a signal coverage area, where each preset area includes at least one communication base station.
For regional crowd gathering early warning, a definite regional division is needed. The mobile communication device in this exemplary embodiment mainly refers to a mobile phone, and the signal coverage of the communication base station, that is, the range that the mobile phone can access, is the core basis for performing the area division. In order to ensure smooth conversation of the mobile equipment in the moving process, the communication base stations have signal overlapping areas between adjacent communication base stations, namely, one mobile phone is positioned in the intersection of signal coverage areas of two or more communication base stations, and simultaneous connection can be realized.
Based on the above, the preset area may be determined by the following method: determining the signal coverage range of each communication base station in a preset range; and determining a plurality of preset areas according to the signal coverage range of the communication base station.
In this exemplary embodiment, the division may be performed directly based on the signal coverage of the communication base station, that is, taking the position of the communication base station as the center and the signal coverage as the boundary, the enclosed area range is the preset area corresponding to the current base station. As shown in fig. 2, the preset areas corresponding to the communication base stations 201 and 202 are areas 203 and 204, respectively. By this way of partitioning, there may be a case where there is an intersection between a plurality of preset regions. In this case, the overlapping portion between the signal coverage areas of the respective communication base stations may be ignored, and only the area covered by the current signal may be determined.
In addition to this, the preset region may be divided based on a Voronoi Diagram algorithm (Voronoi Diagram) and a signal coverage. The voronoi diagram algorithm is a plane area division algorithm, wherein the voronoi diagram is composed of a group of continuous polygons formed by perpendicular bisectors of straight lines connecting two adjacent points. N points that are distinctive on the plane, the plane being divided according to a nearest neighbor principle, each point being associated with its nearest neighbor region. Through the voronoi diagram algorithm, the responsible area of each base station can be estimated. In this way, the influence of the signal overlap region between the base stations can be ignored.
As shown in fig. 3, the method for dividing the preset area based on the voronoi diagram algorithm and the signal coverage may specifically include the following steps:
and S310, judging whether the signal coverage area of the communication base station is overlapped with the signal coverage area of the adjacent communication base station.
When the area division is carried out through the Veno diagram algorithm, the target is to divide the area corresponding to the communication base station with the signal intersection. Therefore, it is first determined whether there is a portion where the signal coverage of the communication base station overlaps with the signal coverage of the adjacent communication base station.
Step s320, if the signal coverage area of the communication base station does not coincide with the signal coverage area of the adjacent communication base station, taking the signal coverage area of each communication base station as a preset area corresponding to the communication base station.
And if no signal intersection exists between two nearest adjacent communication base stations, namely no signal coverage is overlapped, dividing the communication base stations directly based on the signal coverage of the communication base stations, and taking the respective signal coverage of the communication base stations as corresponding preset areas.
And S330, if the signal coverage area of the communication base station is overlapped with the signal coverage area of the adjacent communication base station, dividing the preset area corresponding to the two adjacent communication base stations according to a perpendicular bisector of a connecting line between the two communication base stations.
And if the signal coverage range of the communication base station is overlapped with the signal coverage range of the adjacent communication base station, performing area division through a Voronoi diagram algorithm. As shown in fig. 4, adjacent communication base stations among the communication base stations 401, 402, 403, 404, 405, and 406 are connected, and a perpendicular bisector is made for each connecting line. Each area divided by a perpendicular bisector of a connecting line between the communication base stations is a preset area corresponding to each communication base station, as shown in fig. 5.
Generally, people in a city or a region travel or flow relatively regularly, and the total population is relatively stable. For example, many people may arrive at a company for work at 10 am, and this action may result in a decrease in the number of users in the residential area and an increase in the number of users in the office area. But the fluctuation is normal with respect to the history and falls within the range of stable fluctuation. Therefore, a periodic mechanism needs to be designed to take into account the normal flow of people that meet the regulations.
In the present exemplary embodiment, an appropriate monitoring period may be set in order to periodically monitor the flow condition of the person. Since the working day and the non-working day are obviously periodic, the periodic calculation can be carried out according to Monday, two, three, four, five, six and day by taking each week as a monitoring period. That is, the data of the first monitoring period is only compared with the data of the second monitoring period, so that the base station data fluctuation abnormity caused by periodic policy or work is compatible. The historical monitoring period refers to a monitoring period before the current monitoring period, and a proper time window length can be selected according to actual requirements, but at least the previous monitoring period of the current monitoring period needs to be included.
The corresponding monitoring time period in the monitoring period may be divided according to the statistical period of the communication base station, for example, the data statistical period of the communication base station is counted once per hour, and then the monitoring time period may be divided into hour levels, such as between 8-9 points. Alternatively, several hours may be combined into one cycle. Regardless of the division, such periodicity can be compatible with periodic changes in the base station statistical data due to the flow of persons that meet the regulations.
In this exemplary embodiment, the population history data with periodicity may be obtained by sliding a time window according to the statistical data of the historical time series of the communication base station, that is, the number of users counted by the communication base station in a time interval in the historical time. The population historical data comprises the population number in each monitoring period and the corresponding monitoring time period, the sliding time window comprises a plurality of monitoring periods, and the population historical data comprises a plurality of pieces of data.
For example, the current time period is 8-9 monday, and the number of users of the current communication base station is 80. If 8-9 monday points are used as the corresponding monitoring time periods in the monitoring period, historical user quantity data of all current base stations on monday points with the time of 8-9 monday points in a fixed time window range can be collected as population historical data corresponding to the monitoring time periods. Assuming that the length of the time window is 60 days, a total of 8 monday data at 8-9 points can be collected, and the obtained data set [80,82,88,83,82,89,90,85], for example, is population history data of the corresponding monitoring time period in each historical monitoring period.
In step S120, a population inflow threshold and a population outflow threshold of the preset area in the current monitoring time period are determined according to the population history data.
In this exemplary embodiment, the population inflow threshold refers to an upper threshold at which the number of population in a certain preset area increases, and the population outflow threshold refers to a lower threshold at which the number of population in a certain preset area decreases.
Regional people gathering is relative to historical data. In an area, if the number of current users is larger than the number of people in the historical period, the number of people is increased, and the situation can be defined as people flowing-in type aggregation. In one area, the number of current users is less than the number of population in the historical period, which indicates that the number of population is reduced; a decrease in the population in one area is indicative of an increase in the population in other areas, and this may be defined as a people-shedding aggregation. The two aggregation forms have very important reference significance for monitoring or early warning of personnel flow in an epidemic situation.
For example, in 5 days in the history of a certain area, the number of people in a certain time period is about 10, but the current time period becomes 20, which belongs to a people inflow type aggregation. Or, the historical population number of the same base station is about 100, and the current time period becomes 10, so that the other people outflow type aggregation is realized. Therefore, an increase or decrease in the number of people in the cycle range is a target of the warning in the present exemplary embodiment. The increase or decrease of users is fluctuation for epidemic situation monitoring, which indicates the flow of people and is an index with obvious reference significance.
As shown in fig. 6, the method for determining the population inflow threshold and the population outflow threshold of the preset area in the current monitoring time period according to the historical population data may specifically include the following steps:
and S610, determining the mean value and the standard deviation of the historical monitoring period according to the population historical data.
In the present exemplary embodiment, it is assumed that the historical data conforms to the gaussian distribution as shown in fig. 7, and therefore, the mean and standard deviation of the gaussian distribution may be determined from the population historical data and used as the mean and standard deviation of the historical monitoring period. The specific formula of the gaussian distribution shown in fig. 7 is as follows:
wherein, the variable x represents population data, μ represents a mean value of gaussian distribution, and σ represents a standard deviation of gaussian distribution, which can describe a dispersion degree of the gaussian distribution data, and the larger σ is, the more dispersed the data distribution is; the smaller σ, the more concentrated the data distribution. Therefore, σ is also called a shape parameter of gaussian distribution, and the larger σ is, the flatter the curve is, whereas the smaller σ is, the thinner and taller the curve is. The greater the distance of the data from the mean relative to σ, the more anomalous the data is.
Assuming that 8 pieces of historical population data corresponding to 8-9 points per monday for 8 monitoring periods have been collected [80,82,88,83,82,89,90,85], the following formula can be used:
the mean μ and standard deviation σ of the historical data were calculated. Wherein m represents the number of data in the population history data, i is an index variable, and x(i)Representing the ith data in the demographic history data.
And S620, determining a population fluctuation threshold value of the preset area in the current monitoring time period according to the standard deviation.
The population fluctuation threshold refers to a threshold where the population number fluctuates on a mean basis. As can be seen from fig. 7, the data of the gaussian distribution occupies most of the range (μ -n σ < ═ x < ═ μ + n σ), and belongs to normal data, whereas the data not in this range is abnormal data, the data on the left side of μ -n σ is data lower than normal values, and the data on the right side of μ + n σ is data higher than normal values. Therefore, the threshold calculation can be performed using this principle.
The population fluctuation threshold may be set to a single value, for example, the value of the parameter n may be set to 3, in which case the population fluctuation threshold is 3 σ. In addition, different population fluctuation thresholds may be classified according to different grades.
As shown in fig. 8, the method for determining the population fluctuation threshold of the multi-level early warning specifically includes the following steps:
and step S810, determining a plurality of early warning grades and a plurality of early warning grade parameters corresponding to the early warning grades.
And S820, determining a population fluctuation threshold value of the preset area corresponding to the early warning level in the current monitoring time period according to the product of the standard deviation and the early warning level parameter.
In the present exemplary embodiment, the population fluctuation threshold n σ of the early warning is calculated by setting the early warning level for the current specific early warning demand and selecting an appropriate n value. The plurality of n values correspond to the plurality of early warning levels, and the larger the n value is, the higher the early warning risk is, namely, the higher the aggregation degree of population is.
For example, n may be set to 3, 6, and 9, respectively, to define a level 1 warning, a level 2 warning, and a level 3 warning, respectively. The specific value of n needs to be defined according to the early warning sensitivity, for example, in the severe epidemic situation period, a higher early warning level can be set, for example, 3-level early warning, and n is set to 9; after the epidemic situation is relieved, a lower early warning level can be set, such as level 1 early warning, and n is set to be 3.
And S630, determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to the mean value and the population fluctuation threshold value.
In the embodiment, the population inflow threshold value of the preset area in the current monitoring time period is obtained according to the sum of the mean value and the population fluctuation threshold value; and obtaining the population outflow threshold value of the preset area in the current monitoring time period according to the difference between the mean value and the population fluctuation threshold value.
After determining the mean μ and population fluctuation threshold n σ of the historical data, the following formula may be followed:
μ-nσ<＝x<＝μ+nσ
population inflow and outflow thresholds are calculated.
μ + n σ is the population inflow threshold, i.e., the upper threshold for the increase in population size relative to historical data. If the population number exceeds the population inflow threshold, the population number of the current area is considered to be increased relative to the historical synchronization and exceeds the historical synchronization level.
μ -n σ (μ -n σ > ═ 0) is the population outflow threshold, i.e., the lower threshold for population reduction relative to historical data. If the population number is smaller than the population outflow threshold value, that is, the current regional personnel have flowed out, because the general population in the early warning range can be assumed to be a fixed value, the current regional population is reduced, and the population number in other regions is increased inevitably.
In summary, the people-in type gathering warning and the people-out type gathering warning can be adjusted or set according to actual conditions.
In step S130, the current population number of the preset area in the current monitoring time period is obtained, and if the current population number is greater than the population inflow threshold or less than the population outflow threshold, the population number of the preset area is pre-warned.
In this example embodiment, a suitable historical data sliding window may be selected according to the stability requirement of population number early warning, and the adaptive pre-warning threshold in the preset area of each communication base station may be dynamically calculated. The early warning grade can be divided according to the specific early warning grade requirement, and the value n is set. And by combining the region division method, the dynamic early warning of the population number of each preset region can be realized. And if the current population number is larger than the population inflow threshold value or smaller than the population outflow threshold value, the current population number in the preset area is shown to exceed the preset fluctuation range, and early warning is carried out on the population number in the preset area. If the current population number is within the range of the population outflow threshold value and the population inflow threshold value, the population number of the preset area does not need to be pre-warned, and only the data needs to be acquired and recorded, and the population historical data of each time period is updated in real time.
It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Further, the disclosure also provides a population number early warning device. Referring to fig. 9, the population number warning device may include a history data acquisition module 910, a population threshold determination module 920, and a population number warning module 930. Wherein:
the historical data acquiring module 910 may be configured to acquire a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determine population historical data of a corresponding monitoring time period in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period;
the population threshold determination module 920 may be configured to determine a population inflow threshold and a population outflow threshold of a preset area in a current monitoring time period according to population history data;
the population number early warning module 930 may be configured to obtain a current population number of the preset area in the current monitoring time period, and if the current population number is greater than a population inflow threshold or less than a population outflow threshold, early warning the population number of the preset area.
In some exemplary embodiments of the present disclosure, an early warning apparatus for population numbers provided by the present disclosure may further include a coverage area determination module and a preset area determination module. Wherein:
the coverage area determining module may be configured to determine a signal coverage area of each communication base station within a preset range;
the preset area determining module may be configured to determine a plurality of preset areas according to a signal coverage of the communication base station.
In some exemplary embodiments of the present disclosure, the preset region determining module may include a coincidence range judging unit, a first preset region determining unit, and a second preset region determining unit. Wherein:
the overlapping range judging unit may be configured to judge whether there is an overlap between the signal coverage of the communication base station and the signal coverage of the adjacent communication base station;
the first preset area determining unit may be configured to, if the signal coverage area of the communication base station does not coincide with the signal coverage area of the adjacent communication base station, use the signal coverage area of each communication base station as a preset area corresponding to the communication base station;
the second preset area determining unit may be configured to, if there is a coincidence between the signal coverage range of the communication base station and the signal coverage range of the adjacent communication base station, divide the preset area corresponding to the two adjacent communication base stations according to a perpendicular bisector of a connecting line between the two communication base stations.
In some exemplary embodiments of the present disclosure, the population threshold determination module 920 may include a distribution parameter determination unit, a fluctuation threshold determination unit, and a population threshold determination unit. Wherein:
the distribution parameter determining unit can be used for determining the mean value and the standard deviation of the historical monitoring period according to the population historical data;
the fluctuation threshold determination unit can be used for determining a population fluctuation threshold of the preset area in the current monitoring time period according to the standard deviation;
the population threshold determination unit can be used for determining a population inflow threshold and a population outflow threshold of the preset area in the current monitoring time period according to the mean value and the population fluctuation threshold.
In some exemplary embodiments of the present disclosure, the distribution parameter determination unit may include a gaussian parameter determination unit and a monitoring parameter determination unit. Wherein:
the Gaussian parameter determining unit can be used for determining the mean and standard deviation of Gaussian distribution according to population historical data;
the monitoring parameter determination unit may be configured to use the mean and standard deviation of the gaussian distribution as the mean and standard deviation of the historical monitoring period.
In some exemplary embodiments of the present disclosure, the fluctuation threshold determination unit may include an early warning level determination unit and a level fluctuation threshold determination unit. Wherein:
the early warning level determining unit can be used for determining a plurality of early warning levels and a plurality of early warning level parameters corresponding to the early warning levels;
the level fluctuation threshold determination unit may be configured to determine, according to a product of the standard deviation and the early warning level parameter, a population fluctuation threshold of the preset area corresponding to the early warning level in the current monitoring time period.
In some exemplary embodiments of the present disclosure, the population threshold determination unit may include an inflow threshold determination unit and an outflow threshold determination unit. Wherein:
the inflow threshold value determining unit may be configured to obtain a population inflow threshold value of the preset area in the current monitoring time period according to a sum of the mean value and the population fluctuation threshold value;
the outflow threshold determining unit may be configured to obtain a population outflow threshold of the preset area in the current monitoring time period according to a difference between the mean value and the population fluctuation threshold.
The specific details of each module/unit in the population number early warning device have been described in detail in the corresponding method embodiment section, and are not described herein again.
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device to implement an embodiment of the invention.
It should be noted that the computer system 1000 of the electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiment of the present invention.
As shown in fig. 10, the computer system 1000 includes a Central Processing Unit (CPU)1001 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for system operation are also stored. The CPU 1001, ROM 1002, and RAM 1003 are connected to each other via a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.
In particular, according to an embodiment of the present invention, the processes described below with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. When the computer program is executed by a Central Processing Unit (CPU)1001, various functions defined in the system of the present application are executed.
It should be noted that the computer readable media shown in the present disclosure may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method as described in the embodiments below.
It should be noted that although in the above detailed description several modules of the device for action execution are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module, in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method for providing an early warning of population, comprising:
acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of corresponding monitoring time periods in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period;
determining population inflow threshold values and population outflow threshold values of the preset area in the current monitoring time period according to the population historical data;
and acquiring the current population number of the preset area in the current monitoring time period, and if the current population number is larger than the population inflow threshold value or smaller than the population outflow threshold value, early warning the population number of the preset area.
2. The method for providing early warning of population numbers as recited in claim 1, further comprising:
determining the signal coverage range of each communication base station in a preset range;
and determining a plurality of preset areas according to the signal coverage range of the communication base station.
3. The method for warning about population quantity according to claim 2, wherein the determining a plurality of the preset areas according to the signal coverage of the communication base station comprises:
judging whether the signal coverage area of the communication base station is overlapped with the signal coverage area of the adjacent communication base station;
if the signal coverage range of the communication base station is not overlapped with the signal coverage range of the adjacent communication base station, taking the signal coverage range of each communication base station as a preset area corresponding to the communication base station;
and if the signal coverage range of the communication base station is overlapped with the signal coverage range of the adjacent communication base station, dividing the preset area corresponding to the two adjacent communication base stations according to a perpendicular bisector of a connecting line between the two communication base stations.
4. The method for warning about the population quantity according to claim 1, wherein the determining the population inflow threshold and the population outflow threshold of the preset area in the current monitoring time period according to the population history data comprises:
determining a mean and a standard deviation of the historical monitoring period according to the population historical data;
determining a population fluctuation threshold value of the preset area in the current monitoring time period according to the standard deviation;
and determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to the mean value and the population fluctuation threshold value.
5. The method for pre-warning population quantities according to claim 4, wherein the determining the mean and standard deviation of the historical monitoring periods according to the population history data comprises:
determining the mean and standard deviation of Gaussian distribution according to the population historical data;
and taking the mean value and the standard deviation of the Gaussian distribution as the mean value and the standard deviation of the historical monitoring period.
6. The method for warning about population quantity according to claim 4, wherein the step of determining the population fluctuation threshold of the preset area in the current monitoring time period according to the standard deviation comprises the following steps:
determining a plurality of early warning grades and a plurality of early warning grade parameters corresponding to the early warning grades;
and determining a population fluctuation threshold value of the preset area corresponding to the early warning grade in the current monitoring time period according to the product of the standard deviation and the early warning grade parameter.
7. The method for warning about the population quantity according to claim 4, wherein the determining the population inflow threshold and the population outflow threshold of the preset area in the current monitoring time period according to the mean value and the population fluctuation threshold comprises:
obtaining a population inflow threshold value of the preset area in the current monitoring time period according to the sum of the mean value and the population fluctuation threshold value;
and obtaining the population outflow threshold value of the preset area in the current monitoring time period according to the difference between the mean value and the population fluctuation threshold value.
8. An early warning device of population quantity, comprising:
the historical data acquisition module is used for acquiring a statistical data set of the number of mobile communication devices in a historical monitoring period in a preset area, and determining population historical data of corresponding monitoring time periods in each historical monitoring period according to the statistical data set, the preset monitoring period and the corresponding monitoring time period in each monitoring period;
the population threshold value determining module is used for determining a population inflow threshold value and a population outflow threshold value of the preset area in the current monitoring time period according to the population historical data;
and the population quantity early warning module is used for acquiring the current population quantity of the preset area in the current monitoring time period, and if the current population quantity is larger than the population inflow threshold value or smaller than the population outflow threshold value, early warning is carried out on the population quantity of the preset area.
9. An electronic device, comprising:
a processor; and
memory storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement a method of pre-warning of population size as recited in any of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out a method of pre-warning of population numbers according to any one of claims 1 to 7.
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