CN115619064A - Rescue plan making method, device, equipment and storage medium - Google Patents
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Abstract
The invention provides a rescue plan making method, a rescue plan making device and a storage medium, wherein rescue space information in a preset time period is obtained, and longitude and latitude information summarized by the rescue space information is converted into rescue points in an ink card support coordinate system so as to accurately calculate distances; and generating different clusters through hierarchical clustering according to the distance position relationship of the rescue points to obtain the hierarchical relationship of the rescue points, and calculating the area surface of the rescue points, so that the area surface and the hierarchical relationship are aggregated to obtain a hierarchical grading result. Therefore, the multi-level rescue area generation method is provided, the area division can be carried out at each time interval and under the scale of different levels, reliable real-time reference is provided for the development of rescue tasks, and therefore rescue dispatch management can be conveniently carried out in the area dynamically divided in real time.
Description
Technical Field
The invention relates to the technical field of rescue planning, in particular to a rescue plan making method, a rescue plan making device, rescue plan making equipment and a storage medium.
Background
Currently, there are generally two rescue planning methods:
one method is to firstly acquire at least one rescue center coordinate, a hospital coordinate and a coordinate of an object to be rescued in a preset range, and then generate an optimal new rescue center coordinate according to the coordinates and the number of remaining beds in the hospital.
The other method is to directly plan an optimal rescue route by combining methods such as a GPSO algorithm, an LPSO algorithm, an MCPSO algorithm or an SIPSO algorithm and the like according to the coordinates of a rescue target and the coordinates of a hospital and a rescue center.
The two methods provide a layout method of emergency rescue stations and a designated strategy of a rescue plan in a rescue task, but in the actual situation, when a major disaster occurs, people needing rescue often present certain aggregation distribution, and rescue points are also often responsible for the rescue task of a certain area, but the methods do not provide a proper strategy on the division of the rescue area;
due to the dangerous situation, the rescue task is dynamically changed in real time, while the position of a new rescue center is often determined according to the existing historical data in the conventional algorithm, but the method is usually difficult to adapt to the dangerous situation data which is changed in real time, the distribution effect of the method on the rescue point and the rescue task is gradually weakened along with the time and the disaster change, and the method is deficient in real time.
In addition, the method mainly focuses on strategy designation of a small distance scale, such as path planning to a certain specific point to be rescued or the position of a certain newly added rescue point, lacks macroscopically analyzing and visualizing dangerous cases, and lacks clear unified guidance reference when encountering large-scale dangerous cases.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the rescue plan making method, the rescue plan making device, the rescue plan making equipment and the storage medium can divide a rescue area in real time and make a corresponding rescue plan, and provide reliable real-time reference for the development of a rescue task.
In a first aspect, the present invention provides a rescue plan making method, including the steps of:
acquiring distress spatial information at a preset time period, and converting longitude and latitude information in the distress spatial information into rescue points in an ink card holder coordinate system;
generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
calculating the area surface of each rescue point, and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partitioning result;
and obtaining different-level partitions from the result of the level partition, and making rescue plans of newly added rescue points, rescuers and goods for the different-level partitions through the rescue demands of the different-level partitions, the set rescue points and the distributed rescuers and goods and materials for rescue dispatch management.
In a second aspect, the present invention further provides a rescue plan making device, including:
the rescue information updating module is used for acquiring the help-seeking spatial information at a preset time period and converting longitude and latitude information in the help-seeking spatial information into a rescue point in an mercator coordinate system;
the hierarchical relation generating module is used for generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
the hierarchical partition generation module is used for calculating the area surface of each rescue point and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partition result;
and the rescue dispatch management module is used for obtaining different-level partitions from the result of the level partition, performing rescue dispatch management according to the rescue requirements of the different-level partitions, the set rescue points and the allocated rescue personnel and goods and making rescue plans of newly added rescue points, rescue personnel and goods for the different-level partitions.
In a third aspect, the present invention also provides an electronic device, including:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the rescue planning method as provided in the first aspect.
In a fourth aspect, the invention also provides a computer-readable storage medium, on which a computer program is stored, which computer program, when executed by a processor, implements the rescue planning method as provided in the first aspect.
The invention has the beneficial effects that: acquiring distress spatial information in a preset time period, and converting longitude and latitude information summarized by the distress spatial information into rescue points in a mercator coordinate system so as to accurately calculate the distance; and generating different clusters through hierarchical clustering according to the distance position relationship of the rescue points to obtain the hierarchical relationship of the rescue points, and calculating the area surface of the rescue points, thereby aggregating the area surface and the hierarchical relationship to obtain a hierarchical classification result. Therefore, the multi-level rescue area generation method is provided, the area division can be carried out at each time interval and under the scale of different levels, reliable real-time reference is provided for the development of rescue tasks, and therefore rescue dispatch management can be conveniently carried out in the area dynamically divided in real time.
Drawings
Fig. 1 is a flowchart of a rescue plan making method based on hierarchical zoning according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a rescue plan making device based on hierarchical zoning according to an embodiment of the invention;
FIG. 3 is a block diagram of an electronic device according to an embodiment of the invention;
FIG. 4 is a detailed flow chart of rescue planning according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a layered rescue area according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in greater detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a sub computer program, or the like.
Referring to fig. 1, an embodiment of the present invention provides a rescue plan making method, including:
acquiring distress spatial information in a preset time period, and converting longitude and latitude information in the distress spatial information into rescue points in an mercator coordinate system;
generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
calculating the area surface of each rescue point, and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partitioning result;
and obtaining different-level partitions from the result of the level partition, and making rescue plans of newly added rescue points, rescuers and goods for the different-level partitions through the rescue demands of the different-level partitions, the set rescue points and the distributed rescuers and goods and materials for rescue dispatch management.
From the above description, the beneficial effects of the present invention are: acquiring the distress spatial information at a preset time period, and converting longitude and latitude information summarized by the distress spatial information into a rescue point in an mercator coordinate system so as to accurately calculate the distance; and generating different clusters through hierarchical clustering according to the distance position relationship of the rescue points to obtain the hierarchical relationship of the rescue points, and calculating the area surface of the rescue points, so that the area surface and the hierarchical relationship are aggregated to obtain a hierarchical grading result. Therefore, the multi-level rescue area generation method is provided, the area division can be carried out at each time interval and under the scale of different levels, reliable real-time reference is provided for the development of rescue tasks, and therefore rescue dispatch management can be conveniently carried out in the area dynamically divided in real time.
Further, generating different clusters through hierarchical clustering according to the distance position relationship of the rescue points, and obtaining the hierarchical relationship of the rescue points comprises the following steps:
initializing each rescue point into a cluster, calculating the Euclidean distance between the farthest rescue points in each two clusters, fusing the two clusters into one cluster if the Euclidean distance is smaller than a preset distance, and obtaining the hierarchical relationship of the rescue points through the fusion between the clusters.
According to the description, when the Euclidean distance between the farthest rescue points in the two clusters is smaller than the preset distance, the two clusters are fused into one cluster, and the condition that the partitions are intersected in the same layer can be avoided.
Further, calculating a euclidean distance between the farthest rescue points in each two clusters, and if the euclidean distance is smaller than a preset distance, fusing the two clusters into one cluster, including:
merging two clusters which are not judged into one cluster according to the Euclidean distance:
wherein P and Q represent undiagnosed clusters, P i Coordinates representing the ith rescue point in the P cluster, q j The coordinates representing the jth rescue point in the Q cluster,
denotes p i And q is j And V represents a preset distance.
According to the description, the cluster judgment of all rescue points can be rapidly and comprehensively carried out by analyzing the cluster which is not judged.
Further, the calculating the area surface of each rescue point comprises the following steps:
and calculating the Thiessen polygon of each rescue point to obtain the area surface of each rescue point.
According to the description, the Thiessen polygon algorithm is used for the original rescue point data to obtain the surface information of the geographic space region of each rescue point, so that the subsequent surface aggregation is conveniently performed by using the Thiessen polygon.
Further, aggregating the hierarchical relationship of the rescue points and the area surface to obtain a hierarchical partitioning result further comprises:
and combining the hierarchical partition result with road network information, calculating the passing distance between every two rescue points in the same hierarchical partition, performing secondary clustering according to the passing distance, and if the passing distance exceeds a preset multiple of a preset distance, performing partition segmentation according to the distances between other rescue points and the two rescue points in the partition.
From the above description, it can be known that the coverage of the hierarchical partition can be finely adjusted by performing secondary clustering by combining the hierarchical partition result with the road network information, and the situation that the rescue plan is difficult to implement due to objective conditions such as natural landform and urban roads in each hierarchical partition is avoided.
Further, obtaining different-level partitions from the result of the level partition, and performing rescue dispatch management through rescue demands, set rescue points, allocated rescuers and goods and materials of the different-level partitions, wherein the step of making rescue plans of newly added rescue points, rescuers and goods and materials for the different-level partitions comprises the following steps:
judging whether set rescue points exist in each hierarchical partition, if so, incorporating the set rescue points into the corresponding partitions, otherwise, calculating the area mass center of the partitions, and adding the rescue points according to the coordinates of the area mass center;
and making a corresponding rescue plan of newly-added rescue personnel and materials for the rescue points according to the level of the partition.
According to the description, for the subarea without the rescue points, the rescue points are newly added at the centroid of the area, so that the subarea can be conveniently rescued.
Further, judging whether set rescue points exist in each hierarchy partition, if not, calculating the area mass center of the partition, adding a new rescue point according to the coordinate of the area mass center, and making a corresponding rescue plan of newly added rescue personnel and goods and materials for the rescue point according to the hierarchy where the partition is located comprises the following steps:
judging whether set rescue points exist in the subareas from large to small according to the grades of the subareas of each hierarchy, if not, newly adding rescue points at the area mass center of the subareas, and making a corresponding rescue plan of newly added rescue personnel and goods according to the total quantity of the rescue personnel and goods required by the subareas and the distributed rescue personnel and goods.
According to the description, the dispatching of the personnel and the goods in the newly-added rescue points is carried out according to the dispatching condition of each hierarchy partition, so that the flexibility of rescue dispatching is improved.
Referring to fig. 2, the present invention further provides a rescue plan making device, including:
the rescue information updating module is used for acquiring the help-seeking spatial information at a preset time period and converting longitude and latitude information in the help-seeking spatial information into a rescue point in an mercator coordinate system;
the hierarchical relation generating module is used for generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
the hierarchical partition generation module is used for calculating the area surface of each rescue point and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partition result;
and the rescue dispatch management module is used for obtaining different levels of partitions from the level partition result, performing rescue dispatch management according to the rescue requirements of the different levels of partitions, the set rescue points and the allocated rescuers and goods, and making rescue plans of newly added rescue points, rescuers and goods for the different levels of partitions.
Referring to fig. 3, the present invention further provides an electronic device, including:
one or more processors 301;
a storage device 302 for storing one or more programs;
when executed by the one or more processors 301, the one or more programs cause the one or more processors 301 to implement a rescue planning method as described above.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a rescue plan making method as described above.
The rescue plan making method, device, equipment and storage medium of the present invention are suitable for rescue planning, generation and hierarchy division of rescue areas and management of rescue dispatch under disaster conditions, and are described below by specific embodiments:
example one
Referring to fig. 1 and 4, a rescue plan making method includes the steps of:
s1, obtaining distress spatial information in a preset time period, and converting longitude and latitude information in the distress spatial information into rescue points in an mercator coordinate system.
Specifically, the distress spatial information in the time period t is obtained through the social media, wherein the distress spatial information comprises unresolved distress information and newly-added distress information, including longitude and latitude where the rescue point is located, rescue grades and other information, and the longitude and latitude information is converted into the rescue point in the mercator coordinate system, so that the distance can be accurately calculated.
And S2, generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points.
Specifically, referring to fig. 5, each rescue point is initialized to a cluster, the euclidean distance between the farthest rescue points in each two clusters is calculated, if the euclidean distance is smaller than a preset distance, the two clusters are fused into one cluster, and the hierarchical relationship of the rescue points is obtained through the fusion between the clusters.
In this embodiment, in different stages of the process from the beginning to the end of the disaster, the rescue requirement has a characteristic of dynamic change, and for convenience of management and control, it should be ensured that each level of partition has an approximate size in the whole rescue process, that is, it is ensured that the sizes of partitions in the same level are approximate under different data sparsity degrees. And generating different clusters according to the distance position relation of the rescue points by using a hierarchical clustering algorithm.
The specific process is as follows: and during initialization, each distress message is a cluster, whether the two clusters are fused into one cluster is judged by calculating the Euclidean distance between the farthest rescue points in the two clusters, and if the distance between the farthest rescue points in the two clusters is smaller than the preset distance V, the two clusters are divided into the same cluster.
Assuming that two clusters P and Q which are not judged exist under the current level, if the two clusters are met
Then, P and Q are merged into the same cluster, i.e.:
wherein
Is p i And q is j The distance between them. Therefore, different distress messages are divided into a plurality of different areas from bottom to top according to the geographic information of the distress messages, the distance of the distress messages in each area does not exceed the preset distance V, and the V is set according to the area information and is dynamically changed according to the size of an administrative area (for example, the cluster sizes of different layers are set according to the size of the administrative areas such as specific cities, districts, streets and the like). The hierarchical clustering algorithm ensures that the results generated by each cluster in the subsequent partitions under any hierarchy are satisfiedCondition for points p belonging to the same cluster i 、p j Satisfy the requirements of
For any point P in two clusters P and Q, P i All present in Q at point Q j Satisfy the requirements of
In each cluster, the distance between the farthest point is smaller than or equal to the current level set value V, and the distance between the points which must exist in the two clusters is larger than V, so that the distance between rescue points in the clusters is smaller than V, the distances between the clusters are larger than V, and the rescue points in the clusters have similar sizes. And large partitions between different hierarchies must contain small partitions, without the problem that one partition contains another partition in the same hierarchy, namely:
and S3, calculating the area surface of each rescue point, and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partition result.
S31, calculating the Thiessen polygon of each rescue point to obtain the area surface of each rescue point.
Specifically, a Thiessen polygon algorithm is used for the original rescue point data to obtain the geospatial area surface information of each rescue point.
And S32, aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partition result.
Specifically, according to the hierarchical relationship of the rescue points generated in the hierarchical clustering method, surface aggregation is carried out on the Thiessen polygons to obtain a hierarchical space partitioning result.
And S33, combining the hierarchical partition result with road network information, calculating the passing distance between every two rescue points in the same hierarchical partition, carrying out secondary clustering according to the passing distance, and carrying out partition segmentation according to the distances between other rescue points and the two rescue points in the partition if the passing distance exceeds a preset multiple of a preset distance.
Specifically, the spatial partition generated in the above steps may not be in accordance with the objective conditions of natural features, urban roads, and the like in the area, and thus may be difficult to implement. In order to avoid the problems, the algorithm finely adjusts the coverage range of the hierarchical community again, calculates the real passing distance between two pieces of help-seeking information by combining with the road network information, and performs clustering again according to the passing distance, and supposing that a rescue point p exists in the cluster A 1 、p 2 、p 3 、…、p n . Traversing any two points, traversing and calculating the passing distance between the two points in the cluster by using an A-x algorithm, and if the passing distance between the two points exceeds the preset distance
Doubling in practical application
If 1.5 is selected, the fact that the real passing distance between two points is large in obstruction is indicated, the two points are not suitable for being used as the same cluster, and the cluster is divided according to the passing distance from other points to the two points. The real passing time among the distress messages in each cluster can be ensured not to be too long, and the rescue efficiency is improved.
And S4, obtaining different-level partitions from the result of the level partition, and performing rescue dispatch management through rescue demands of the different-level partitions, set rescue points, allocated rescuers and goods and materials to make rescue plans of newly added rescue points, rescuers and goods and materials for the different-level partitions.
S41, judging whether set rescue points exist in each hierarchy partition, if so, incorporating the set rescue points into the corresponding partitions, otherwise, calculating the area mass center of the partitions, and adding the rescue points according to the coordinates of the area mass center.
Specifically, whether set rescue points exist in the subareas or not is judged from large to small according to the grades of the subareas of each hierarchy, and if not, the rescue points are newly added at the area mass center of the subareas.
And S42, making a corresponding rescue plan of newly added rescue personnel and materials for the rescue point according to the level of the partition.
And according to the total amount of the rescuers and the materials required by the subareas and the allocated rescuers and materials, making a corresponding rescue plan of the newly-added rescuers and the materials for the newly-added rescue point.
Specifically, a rescue point setting part determines whether rescue points need to be added or not based on the number and the level of existing rescue demands in the existing hierarchical partitions. If a certain area needs to be provided with a rescue point, the algorithm recommends the site selection of the new rescue point.
In the embodiment, under a larger distance scale, the existing rescue points are accommodated in the rescue area according to the area where the rescue points are located, so as to provide further material and personnel support; in addition, calculating the mass center of each rescue area with different levels given by the hierarchical partitioning result under a smaller distance scale, and recommending the mass center coordinate as a newly added rescue point coordinate if no existing rescue point exists in the area;
the specific process is as follows:
set the size grade of the rescue area as S i (I =1,2,3, \ 8230;, I), the total K generated at this level i A rescue area is marked as
(K =1,2,3, \ 8230;, K), no. a k The total amount of materials needed by each rescue area is R i,k The amount of existing material is r i,k The center of mass of which is C i,k 。
With S i-2 =500m，S i-1 =5000m，S i For example, =10000m, first calculate S i Center of mass C of each rescue point under grade i,k And central rescue points are arranged at each mass center, and the distribution quantity is (R) i,k -r i,k ) The rescue goods and materials. Then at S i-1 Under the graded region, calculating the required additional material amount Re in the region i-1,k Wherein Re i-1,k =R i-1,k -r i-1,k . The obtained result is compared with a preset threshold value
And (3) comparison:
if Re i-1,k If < 0, meaning that the rescue goods and materials in the area are relatively abundant, the rescue goods and materials are recommended to the S i Rescue area under grade
C in (1) i,k Rescue point supplement (-Re) i-1,k ) To support global rescue material distribution;
if 0 < Re i-1,k ＜
When the gap of the rescue goods and materials is small, the rescue goods and materials can be directly arranged from the upper-level area
Rescue point C in i,k Obtaining Re i-1,k The rescue goods and materials;
if it is
If the area has a rescue station, the area is located in the upper level area
Rescue point C i,k Middle call Re i-1,k The rescue materials are sent to the rescue station; if the rescue station is not owned, the current area is
At center of mass C i-1,k Setting a new rescue point and calling required materials;
if it is
Irrespective of the region
Whether there is a rescue point or not is all at the center of mass C i-1,k Generating a new rescue point and calling corresponding goods and materials;
in pair S i-1 All rescue zones under grade
After the rescue points and the rescue goods and materials are set, continuing to set the rescue points and the rescue goods and materials according to the process S i-2 And planning a new rescue point in the rescue area of the grade. Wherein, if
S in i-1 Rescue area under grade
Center of mass C i-1,k If the position is not provided with a rescue point, continuously searching the S where the position is located upwards i Rescue area under grade
As an alternative.
The method can continuously generate new optimal rescue point positions along with the reduction of the regional division scale, and set rescue points of different scales according to the size and the emergency degree of the region.
In the personnel and material distribution part, the rescue personnel distribution of the personnel to be transferred and the distribution and transportation of drinking water, food and medical materials are mainly considered. In the aspect of specific allocation, aiming at each rescue point/rescue center, firstly determining a polygonal area S under the minimum distance scale where the rescue point/rescue center is positioned 1 Sorting the first element according to the emergency degree and the second element according to the rescue distance, and assigning tasks; when no remaining points to be rescued exist in the area, determining the rescue area with larger distance scale where the points to be rescued exist, and further determining the matched rescue points as next task targets according to the sorting method until the matched rescue points are foundThe rescue task is completed.
The three parts form a process for making a rescue plan, and the algorithm process is periodically executed at a certain time interval t in the disaster relief period until the rescue task is completed, so that real-time rescue zoning and dispatch management in the rescue process are realized.
Thus, the present embodiment is driven by real-time rescue demand data. The method can be suitable for the requirements of rapidly judging the dangerous case grade of dynamic and complex dangerous case conditions, reasonably dividing disaster areas and the like under a large-range dangerous case. Compared with the prior scheme, the divided rescue area can be adaptively adjusted in real time along with the change of dangerous cases. The rescue personnel can grasp the disaster situation at the first time and select a proper rescue strategy. Also, the present embodiments provide a hierarchically partitioned rescue management framework. On the basis of acquiring real-time dangerous case data, a Thiessen polygon algorithm is adopted to divide a space region, and a hierarchical clustering method is used to aggregate the generated regions under different scales. Compared with the conventional rescue system, the rescue area under a larger scale in the scheme provides visual real-time disaster-suffered conditions for rescuers, and is beneficial to the overall control of the disaster conditions; the medium-sized rescue area can provide rescue task distribution guidance for the rescue center; the small rescue area is beneficial to exerting the rescue capacity of each rescue team to the maximum extent and providing the optimal rescue route planning for the rescue teams.
Example two
Referring to fig. 2, a rescue plan making device can execute the rescue plan making method provided by the first embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. The device can be implemented by software and/or hardware, and specifically comprises:
the rescue information updating module 201 is configured to acquire the spatial information for asking for help in a preset time period, and convert longitude and latitude information in the spatial information for asking for help into a rescue point in the mercator coordinate system.
The hierarchical relationship generation module 202 is configured to generate different clusters through hierarchical clustering according to the distance and position relationship of the rescue points, so as to obtain the hierarchical relationship of the rescue points; specifically, initializing each rescue point into a cluster, calculating the Euclidean distance between the farthest rescue points in each two clusters, fusing the two clusters into one cluster if the Euclidean distance is smaller than a preset distance, and obtaining the hierarchical relationship of the rescue points through the fusion between the clusters;
wherein, two clusters which are not judged are merged into one cluster according to the Euclidean distance:
wherein P and Q represent undiagnosed clusters, P i Coordinates representing the ith rescue point in the P cluster, q j The coordinates representing the jth rescue point in the Q cluster,
denotes p i And q is j And V represents a preset distance.
The hierarchical partition generation module 203 is configured to calculate a region surface of each rescue point, and aggregate the hierarchical relationship of the rescue points with the region surface to obtain a hierarchical partition result;
specifically, calculating a Thiessen polygon of each rescue point to obtain an area surface of each rescue point, and aggregating the hierarchical relationship of the rescue points and the area surface to obtain a hierarchical partitioning result; and combining the hierarchical partition result with road network information, calculating the passing distance between every two rescue points in the same hierarchical partition, performing secondary clustering according to the passing distance, and if the passing distance exceeds a preset multiple of the preset distance, performing partition segmentation according to the distance between other rescue points and the two rescue points in the partition.
The rescue dispatch management module 204 is used for obtaining different-level partitions from the hierarchical partition result, performing rescue dispatch management according to the rescue requirements of the different-level partitions, the set rescue points and the allocated rescuers and goods, and making rescue plans of newly added rescue points, rescuers and goods for the different-level partitions;
specifically, judging whether set rescue points exist in each hierarchy partition, if so, bringing the set rescue points into the corresponding partitions, otherwise, calculating the region mass center of the partitions, adding the rescue points according to the coordinates of the region mass center, and making corresponding rescue plans of newly added rescue workers and goods and materials for the rescue points according to the hierarchy where the partitions are located;
judging whether set rescue points exist in the subareas from large to small according to the grades of the subareas of each hierarchy, if not, newly adding rescue points at the area mass center of the subareas, and making a corresponding rescue plan of the newly added rescue personnel and materials for the newly added rescue points according to the total quantity of the rescue personnel and materials required by the subareas and the distributed rescue personnel and materials.
EXAMPLE III
Referring to fig. 3, an electronic device includes:
one or more processors 301;
a storage device 302 for storing one or more programs;
when the one or more programs are executed by the one or more processors 301, the one or more processors 301 implement the processes in the rescue plan making method embodiment described above, and can achieve the same technical effect, and in order to avoid repetition, the details are not described here again.
Example four
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the processes in the rescue plan making method embodiment described above, and can achieve the same technical effects, and in order to avoid repetition, details are not repeated here.
In summary, the rescue plan making method, the rescue plan making device, the rescue plan equipment and the storage medium provided by the invention provide a rescue area generation and rescue point matching method under multi-level and different distance scales. The method provides a solution for automatically dividing the rescue area under the large-range emergency condition, and meanwhile, the rescue area can be automatically divided under different distance scales. The invention also comprises a real-time rescue planning solution, and according to the information to be rescued in each time period, the rescue task points are divided into regions under different scales in real time, so that reliable real-time reference is provided for the development of the rescue tasks. Meanwhile, a layering and partitioning strategy which is easy to manage is provided, the partitioning under the large distance scale is convenient for rescue workers to control the dangerous case trend on the whole, and the partitioning under the small distance scale is beneficial to making and developing a specific rescue plan.
The above description is only an embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent modifications made by the present invention and the contents of the accompanying drawings, which are directly or indirectly applied to the related technical fields, are included in the scope of the present invention.
Claims (10)
1. A rescue plan making method is characterized by comprising the following steps:
acquiring distress spatial information at a preset time period, and converting longitude and latitude information in the distress spatial information into rescue points in an ink card holder coordinate system;
generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
calculating the area surface of each rescue point, and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partitioning result;
and obtaining different-level partitions from the result of the level partition, and making rescue plans of newly added rescue points, rescuers and goods for the different-level partitions through the rescue demands of the different-level partitions, the set rescue points and the distributed rescuers and goods and materials for rescue dispatch management.
2. The rescue plan making method according to claim 1, wherein different clusters are generated by hierarchical clustering according to the distance position relationship of the rescue points, and obtaining the hierarchical relationship of the rescue points comprises:
initializing each rescue point into a cluster, calculating the Euclidean distance between the farthest rescue points in each two clusters, if the Euclidean distance is smaller than a preset distance, fusing the two clusters into one cluster, and obtaining the hierarchical relation of the rescue points through the fusion between the clusters.
3. A rescue plan making method according to claim 2, wherein the euclidean distance between the farthest rescue points in each two clusters is calculated, and if the euclidean distance is smaller than a preset distance, the merging of the two clusters into one cluster comprises:
merging two clusters which are not judged into one cluster according to the Euclidean distance:
wherein P and Q represent undiagnosed clusters, P i Coordinates representing the ith rescue point in the P cluster, q j The coordinates representing the jth rescue point in the Q cluster,
denotes p i And q is j And V represents a preset distance.
4. A rescue plan making method according to claim 1, wherein the calculating the area surface of each rescue point comprises:
and calculating the Thiessen polygon of each rescue point to obtain the area surface of each rescue point.
5. The rescue plan making method according to claim 1, wherein the step of aggregating the hierarchical relationship of the rescue points and the area surface to obtain a hierarchical partitioning result further comprises:
and combining the hierarchical partition result with road network information, calculating the passing distance between every two rescue points in the same hierarchical partition, performing secondary clustering according to the passing distance, and if the passing distance exceeds a preset multiple of a preset distance, performing partition segmentation according to the distances between other rescue points and the two rescue points in the partition.
6. The method as claimed in claim 1, wherein the step of obtaining different levels of partitions from the result of the level partitioning, and performing rescue dispatch management according to the rescue demands, the set rescue points and the allocated rescuers and materials of the different levels of partitions, comprises the steps of:
judging whether set rescue points exist in each hierarchy partition, if so, bringing the set rescue points into the corresponding partitions, otherwise, calculating the area mass center of the partitions, and adding the rescue points according to the coordinates of the area mass center;
and making a corresponding rescue plan of newly-added rescue personnel and materials for the rescue points according to the level of the partition.
7. The method as claimed in claim 6, wherein the step of determining whether set rescue points exist in each hierarchy partition, if not, calculating the area centroid of the partition, adding a new rescue point according to the coordinates of the area centroid, and making a corresponding rescue plan for the new rescue personnel and materials according to the hierarchy of the partition comprises:
judging whether set rescue points exist in the subareas from large to small according to the grades of the subareas of each hierarchy, if not, newly adding rescue points at the area mass center of the subareas, and making a corresponding rescue plan of newly added rescue personnel and goods according to the total quantity of the rescue personnel and goods required by the subareas and the distributed rescue personnel and goods.
8. A rescue plan making device, comprising:
the rescue information updating module is used for acquiring the help-seeking spatial information at a preset time period and converting longitude and latitude information in the help-seeking spatial information into a rescue point in an mercator coordinate system;
the hierarchical relation generating module is used for generating different clusters through hierarchical clustering according to the distance position relation of the rescue points to obtain the hierarchical relation of the rescue points;
the hierarchical partition generation module is used for calculating the area surface of each rescue point and aggregating the hierarchical relation of the rescue points and the area surface to obtain a hierarchical partition result;
and the rescue dispatch management module is used for obtaining different levels of partitions from the level partition result, performing rescue dispatch management according to the rescue requirements of the different levels of partitions, the set rescue points and the allocated rescuers and goods, and making rescue plans of newly added rescue points, rescuers and goods for the different levels of partitions.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a rescue planning method as claimed in any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of a rescue planning method according to any one of claims 1-7.
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