CN116882764A - Disaster risk management method based on region and historical data machine learning - Google Patents
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Abstract
The application relates to a disaster risk management method based on regional and historical data machine learning, which comprises the steps of determining disaster areas and placement points; determining an initial personnel set according to the disaster area and the placement points; and determining receiving personnel and evacuating personnel according to the historical passing route of each initial personnel in the initial personnel set and the historical passing times corresponding to the historical passing route, wherein the receiving personnel are personnel for receiving disaster-stricken personnel at the placement point, and the evacuating personnel are personnel for evacuating disaster-stricken personnel between the disaster-stricken area and the placement point. The application has the effect of improving the implementation efficiency of the evacuation disaster-stricken area.
Description
Technical Field
The application relates to the technical field of disaster risk assessment, in particular to a disaster risk management method based on region and historical data machine learning.
Background
At present, natural disasters such as debris flow, typhoons and floods are more, the damage is large, the range of the disaster is wide, and when the natural disasters occur, people can have great blindness in selecting escape routes due to the dynamic of disaster development and the panic mind of refugees in the catastrophe period. Therefore, how to select proper evacuation responsibility personnel and ensure safe and effective implementation of evacuation is also of great importance.
Disclosure of Invention
In order to improve the implementation efficiency of evacuating a disaster-stricken area, the application provides a disaster risk management method based on region and historical data machine learning. The method comprises the following steps:
determining disaster areas and placement points;
determining an initial personnel set according to the disaster area and the placement points;
and determining receiving personnel and evacuating personnel according to the historical passing route of each initial personnel in the initial personnel set and the historical passing times corresponding to the historical passing route, wherein the receiving personnel are personnel for receiving disaster-stricken personnel at the placement point, and the evacuating personnel are personnel for evacuating disaster-stricken personnel between the disaster-stricken area and the placement point.
According to the technical scheme, the positions of the disaster-stricken area and the placement point are determined firstly, then, the persons meeting the requirements are determined in distance according to the positions of the disaster-stricken area and the placement point, an initial person set is formed, and then, according to the historical passing route of each initial person in the initial person set and the passing times corresponding to the historical passing route, the evacuated persons more familiar with the disaster-stricken area and the receiving persons more familiar with the placement point are further determined, so that the purpose of selecting proper rescue persons is achieved, and the effect of improving the implementation efficiency of the evacuated disaster-stricken area is achieved.
In one possible implementation, determining an initial set of people from the disaster area and the placement point includes:
determining an initial personnel area according to a target point, a disaster area and a placement point, wherein the target point is the midpoint of a connecting line of the disaster area and the placement point;
and determining an initial personnel set according to the real-time positions of the personnel in the initial personnel area.
According to the technical scheme, the range of the initial personnel, namely the initial personnel area is defined according to the disaster-stricken area, the setting point and the midpoints of the disaster-stricken area and the setting point, then the initial personnel set is determined according to the real-time positions of the personnel in the initial personnel area, and a more proper personnel set is determined on the distance, so that the time for the personnel in the initial personnel set to reach the disaster-stricken area and/or the setting point can be reduced, and further the implementation efficiency of evacuating the disaster-stricken area can be improved.
In one possible implementation manner, determining the receiving person and the evacuating person according to the history traffic route of each initial person in the initial person set and the history traffic times corresponding to the history traffic route includes:
determining evacuation personnel according to the first passing times of each initial personnel in the initial personnel set between the disaster area and the placement point;
and determining the receiving personnel according to the second pass times of each initial personnel in the initial personnel set between the adjacent area and the placement point, wherein the adjacent area is an area bordered by the placement point and/or the disaster area.
According to the technical scheme, the first pass number of the initial personnel between the disaster affected area and the placement point is judged and selected to be more familiar with the pass condition of the disaster affected area and the placement point to serve as the evacuation personnel, the second pass number of the initial personnel between the adjacent area and the placement point is judged and selected to be more familiar with the placement point to serve as the receiving personnel, and the personnel more familiar with the local situation is selected to implement support, so that the implementation efficiency of the evacuation affected area and the placement efficiency of the placement point can be improved.
In one possible implementation, determining the evacuation personnel according to a first pass number of each initial personnel in the initial personnel set between the disaster area and the placement point includes:
when the first pass number is larger than a first pass number preset value, taking initial personnel corresponding to the first pass number larger than the first pass number preset value as evacuation personnel.
According to the technical scheme, the familiarity of initial personnel to other conditions such as passing between the disaster-stricken area and the placement point is measured by limiting the first preset value, and the proper evacuation personnel is determined, so that the evacuation efficiency of the evacuation disaster-stricken area is improved.
In one possible implementation, determining the receiving person according to the second pass number of each initial person in the initial person set between the adjacent area and the placement point includes:
and when the second pass number between the adjacent area and the placement point is larger than the second pass number preset value, taking an initial person corresponding to the second pass number larger than the second pass number preset value as a receiving person.
According to the technical scheme, the familiarity of initial personnel to other conditions such as passing between the placement point and the adjacent area is measured by limiting the preset value of the second times, and the proper receiving personnel are determined, so that the receiving and placement efficiency of the placement point is improved.
In one possible implementation, determining the disaster area includes:
determining a plurality of grid areas;
and determining disaster areas in the grid areas according to the rainwater amount, the drainage amount, the soil property data and the topography data in each grid area.
According to the technical scheme, the determination range of each grid area is reduced by dividing the grid area into a plurality of grid areas, and the accuracy of determining the disaster-stricken area can be improved.
In one possible implementation, determining a disaster area in a plurality of grid areas according to the amount of rain water, the amount of water discharged, the soil data, and the topography data in each grid area includes:
determining the actual water quantity of the grid area according to the rainwater quantity and the topography data;
determining the receivable rainwater according to the drainage and soil property data of the grid area;
determining a water quantity difference value of each grid area according to the actual water quantity and the receivable rainwater quantity;
and determining the grid area where the water quantity difference reaches the water quantity threshold as a disaster area.
According to the technical scheme, the accuracy of determining the receivable rainwater quantity in the grid area is improved in consideration of both theoretical drainage quantity and influence of land water seepage on the receivable rainwater quantity in the grid area, and the accuracy of determining the actual water quantity is improved in consideration of both the actual rainwater quantity in the grid area and the related water quantity flowing in other areas, so that the accuracy of judging the disaster area can be improved.
In one possible implementation, determining the actual water volume of the grid area according to the amount of rain water and the topography data includes:
calculating the associated water quantity of each grid area according to the topography data, wherein the associated water quantity is the rainwater quantity flowing into the grid area from other grid areas bordering the grid area;
and adding the associated water quantity and the rainwater quantity to obtain the actual water quantity.
According to the technical scheme, the amount of rainwater required to be discharged in the grid area can be accurately judged by considering the associated water amount flowing in from other grid areas bordering the grid area, and the accuracy of judging the disaster area is improved.
In one possible implementation, determining the placement point includes:
and determining at least one placement point according to the distance between the disaster-stricken area and the placement point, wherein the distance between the disaster-stricken area and the placement point is smaller than a preset distance value.
According to the technical scheme, the distance between the disaster-stricken area and the placement point is limited, so that the time for reaching the placement point can be ensured to a certain extent, the time spent from the disaster-stricken area to the placement point is shortened as much as possible, and the implementation efficiency of evacuating the disaster-stricken area is improved.
In one possible implementation, the method further includes:
and sending evacuation support information to the evacuees and the receiving personnel according to the disaster-stricken areas and the placement points, wherein the evacuation support information is used for providing the evacuees and the receiving personnel with the position information of the placement points and the disaster-stricken areas and the disaster conditions of the disaster-stricken areas.
In summary, the present application includes at least one of the following beneficial technical effects:
the method has the advantages that through acquiring the historical passing route of each initial person in the initial person set and the passing times corresponding to the historical passing route, the evacuated persons more familiar with the disaster area and the receiving persons more familiar with the placement points can be determined, the purpose of selecting proper rescue persons is achieved, and the effect of improving the implementation efficiency of the evacuated disaster area is achieved;
the method comprises the steps of defining an initial personnel area, determining an initial personnel set according to the real-time positions of personnel in the initial personnel area, determining a more proper personnel set in distance, reducing the time for the personnel in the initial personnel set to reach a disaster-affected area and/or a placement point, and further improving the implementation efficiency of evacuating the disaster-affected area;
the first pass number of the initial personnel between the disaster affected area and the placement point is judged and selected to be more familiar with the pass condition of the disaster affected area and the placement point to serve as the evacuation personnel, the second pass number of the initial personnel between the adjacent area and the placement point is judged and selected to be more familiar with the placement point to serve as the receiving personnel, and the personnel more familiar with the local situation is selected to implement support, so that the implementation efficiency of the evacuation affected area and the placement efficiency of the placement point can be improved.
Drawings
Fig. 1 is a flow chart of a disaster risk management method based on region and history data machine learning provided by the application.
Fig. 2 is a schematic structural diagram of a disaster risk management system based on region and history data machine learning according to the present application.
Fig. 3 is a schematic structural diagram of an electronic device provided by the present application.
In the figure, 200, a disaster risk management system based on region and history data machine learning; 201. a region determination module; 202. an initial personnel determination module; 203. a rescue personnel determining module; 301. a CPU; 302. a ROM; 303. a RAM; 304. an I/O interface; 305. an input section; 306. an output section; 307. a storage section; 308. a communication section; 309. a driver; 310. removable media.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
For most natural disasters, the prediction of the natural disasters can be further realized by monitoring some data, and then people in the disaster-affected area are timely notified to evacuate according to the prediction result, so that the loss caused by the natural disasters is reduced as much as possible. However, how to select proper evacuation responsible personnel and ensure the safe and effective evacuation of personnel in disaster areas to the greatest extent is a problem to be solved at present.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application provides a disaster risk management method based on region and history data machine learning, and the main flow of the method is described as follows.
As shown in fig. 1:
step S101: and determining disaster areas and placement points.
Specifically, a plurality of grid areas are first determined, the plurality of grid areas form a monitored area, and the division of the grid areas can be determined through administrative division, that is, each grid area can be a province, a city, a county, a town and the like, and can also be divided according to other indexes, for example, the monitored area is divided into a plurality of grid areas according to different rainfall, and then, for example, the monitored area is divided into a plurality of grid areas according to different topography. In the embodiment provided by the application, the monitored area refers to the largest geographical range which can be monitored, and the division of the monitored area into a plurality of grid areas is used for improving the accuracy of judging the disaster-affected area, if the monitored area is not divided into a plurality of grid areas, the disaster prediction is carried out on the whole large monitored area, and the accuracy of the prediction result is reduced. The manner in which the plurality of mesh regions are determined is not limited herein.
Further, disaster areas in the plurality of grid areas are determined according to the amount of rain water, the amount of water discharged, the soil data, and the topography data in each grid area. The amount of rainwater refers to the total amount of rainwater in each of the grid areas. The drainage amount refers to the amount of rainwater that can be received by the grid area through a river or other drainage channels. The soil data refers to the soil conditions of the grid region, and the water permeability of different soil is different. The geological data refer to the situation of the fluctuation and the danger of the surface morphology of the grid area, including the absolute height of the surface morphology and the steepness of the relative height difference or gradient.
It will be appreciated that for each grid area the amount of rainwater that needs to be borne comprises two parts, one part from the amount of rainfall falling in that grid area and the amount of rainwater that other grid areas flow into that grid area, i.e. the associated amount of water, so the actual amount of water for the grid area is determined from the amount of rainwater and the topography data. Firstly, calculating the associated water quantity of each grid area according to the topography data, wherein the associated water quantity is the rainwater quantity flowing into the grid area from other grid areas bordering the grid area; the actual water amount is calculated using the topography data because rainwater of other mesh areas flows into the mesh area only when the topography of the other mesh areas is higher than the topography of the mesh area, and rainwater of the other mesh areas does not flow into the mesh area when the topography of the other mesh areas is not higher than the topography of the mesh area. In one embodiment, a functional relationship or model between the amount of rainfall, the topography data, and the amount of rain that flows out may be established, such that the amount of rain that flows out or into other grid areas may be derived from the topography data. And adding the related water quantity and the rainwater quantity to obtain the actual water quantity.
Further, the manner of draining the amount of rainwater required for each grid area also includes two parts, one part is to receive, store or drain the amount of rainwater through a river or other drainage system built in the grid area, and the other part is to permeate the rainwater on the land in the grid area and absorb the amount of rainwater through the land and vegetation. Therefore, the amount of receivable rain water is determined based on the drainage amount of the mesh region and the soil property data. The drainage quantity of the built river channel or other drainage systems can be calculated by building data, the absorption condition of the soil to the rainwater needs to be estimated according to soil data, the water seepage of different soil is different, the amount of the rainwater which can be received by the soil with good water seepage is more, and the amount of the rainwater which can be received by the soil with poor water seepage is less.
Determining a water quantity difference value of each grid area, namely a difference value of the actual water quantity and the receivable rainwater quantity, according to the calculated actual water quantity and the receivable rainwater quantity, wherein the water quantity difference value is used for indicating whether the actual water quantity and the receivable rainwater quantity reach balance, and when the balance is reached, the received rainwater quantity and the discharged rainwater quantity of the grid area are balanced, so that rainwater accumulation is avoided, and flood is avoided; when the difference in water quantity reflects that the quantity of receivable rainwater is larger than the actual water quantity, rainwater accumulation is not caused. However, when the water quantity difference reflects that the receivable rainwater quantity is smaller than the actual water quantity, that is, the water quantity difference reaches a water quantity threshold value, the rainwater is accumulated, flood is easy to occur, and the grid area is determined to be a disaster-affected area.
After the disaster area is determined, the placement point is determined according to the disaster area, and the specific process is as follows:
and determining at least one placement point according to the distance between the disaster-stricken area and the placement point, wherein the distance between the disaster-stricken area and the placement point is smaller than a preset distance value.
It can be understood that by setting the distance preset value, that is, defining the distance between the placement point and the disaster area, the accessibility of the placement point can be ensured to a certain extent, if the placement point is located far from the disaster area, the possibility of accident on the road can be increased, and people in the disaster area can withdraw to the safe placement point to generate more resistance. Therefore, after the disaster area is determined, a circle is drawn around the disaster area with the preset distance value as a radius, and one or more placement points are determined within the range of the circle, and it is understood that the placement points are generally pre-built for avoiding when natural disasters occur, so the positions of the placement points are known in advance.
In a specific embodiment, one or more placement points may be selected from a plurality of placement points to complete the transfer of the personnel in the disaster area, or a plurality of placement points may be used simultaneously to complete the transfer of the personnel in the disaster area, and whether to screen the placement points again is determined according to actual situations or other requirements, which is not limited herein.
In a specific example, the placement of personnel in the disaster area is completed by screening suitable placement points according to the security score of each placement point, and the specific calculation process of the security score of each placement point is as follows, wherein the security scores comprise a route security score and a neighbor security score. The route safety score is obtained according to the number of grid areas and disaster situations, wherein the grid areas are passed by the route from the disaster area to the placement point. And for a certain passing route, the corresponding score of the disaster-stricken condition of the grid area passed by the passing route is called, then the ratio of the area or the length of the passing route falling into the grid area to the total area or the total length of the passing route is determined, the score and the ratio are multiplied to obtain the disaster-stricken score corresponding to the grid area, the disaster-stricken scores of all the grid areas passed by the passing route are added to obtain the total disaster-stricken score, then the corresponding dangerous lifting proportion is called according to the number of the passing grid areas, and the total disaster-stricken score and the dangerous lifting proportion are multiplied to obtain the route safety score. It will be appreciated that when a certain transit line is determined, the total disaster score is determined, but as the number of passing grid areas increases, the factors affecting the safety of the transit line increase, and the disaster condition of any passing grid area becomes serious, which results in an increase in the difficulty of passing the transit line.
And determining the safety score of the adjacent region according to disaster situation and relief data of a grid region bordering the placement point. And comparing the topography data of the placement points with the topography data of other grid areas around the placement points, and calculating the topography difference value of each grid area and the placement points. And determining the influence proportion of the disaster situation of different grid areas on the safety of the placement points according to the topography difference value. For example, a difference in average elevation of the placement point and each grid region in the periphery, that is, a topography difference, is calculated, and if the topography difference reflects that the elevation of the placement point is higher than the grid region, the influence specific gravity of the grid region is 0. If the topography difference reflects that the elevation of the placement point is not higher than the grid area, the specific gravity is determined to be affected according to the topography difference. For example, the grid area not higher than the elevation of the placement point has a first area, a second area and a third area, each area corresponds to a relief difference value, that is, the first area corresponds to the first relief difference value, the second area corresponds to the second relief difference value and the third area corresponds to the third relief difference value, then the influence specific gravity corresponding to the first area=the first relief difference value/(the first relief difference value+the second relief difference value+the third relief difference value), the influence specific gravity corresponding to the second area and the third area can be calculated by the same method, then the scores of disaster situations corresponding to the first area, the second area and the third area are obtained, and the adjacent area safety score of the placement point can be obtained by adding the products of the scores of disaster situations and the influence specific gravity of each area.
Step S102: and determining an initial personnel set according to the disaster area and the placement points.
Specifically, a circle is drawn by taking a target point as a circle center and the distance between the disaster affected area and the placement point as a radius, so as to form an initial personnel area, wherein the target point is the midpoint of a connecting line of the disaster affected area and the placement point. By the method, the initial personnel area is defined, and suitable personnel are found in the initial personnel area to assist in completing evacuation of personnel in the disaster area and personnel placement of each disaster area in the placement points.
And determining an initial personnel set according to the real-time positions of the personnel in the initial personnel area. The personnel in the initial personnel area can be ordinary residents, personnel with rescue experience, and public personnel in the initial personnel area. Whether the personnel in the initial personnel area are further limited is adjusted according to the actual situation. For example, when the disaster situation is serious, more people are needed to assist in completing the evacuation work from the disaster area to the placement point, and at this time, the people in the initial personnel area may not be limited, that is, the initial personnel set may be determined according to the positions of all the people in the initial personnel area; when the disaster situation is relatively light, people are not needed to assist in completing the evacuation work from the disaster area to the placement point, and then public staff in the initial staff area can be selected as an initial staff set.
Step S103: and determining the receiving personnel and the evacuating personnel according to the historical passing times corresponding to the historical passing routes of each initial personnel in the initial personnel set.
Specifically, the receiving personnel are people for receiving disaster-stricken personnel at the placement point, the evacuating personnel are people for evacuating disaster-stricken personnel between the disaster-stricken area and the placement point, the evacuating personnel comprise basic-level evacuating personnel and evacuating management personnel, and the receiving personnel comprise basic-level receiving personnel and receiving management personnel.
After the initial personnel set is determined, a passing route of the initial personnel in the initial personnel set passing through the disaster area and/or the placement point is obtained, and then the historical passing times of the passing route passing through the disaster area and the placement point are determined in the passing route and are recorded as first passing times. Setting a threshold range of evacuation personnel according to population density, disaster situation and area of a disaster area, and setting a first preset value when the number of initial personnel with the first pass number not being zero is greater than the threshold of the evacuation personnel, so that the number of the initial personnel with the first pass number greater than the first preset value is within the threshold range of the evacuation personnel.
According to the population density, the disaster situation and the area of the disaster area, the threshold range of the evacuee is set, and the corresponding relation among a plurality of groups of data can be established manually, so that the threshold range of the evacuee can be determined uniquely on the premise of knowing the population density, the disaster situation and the area of the area. The corresponding relation among the multiple groups of data can be obtained by model training of historical rescue data, wherein the historical rescue data comprises the area of a rescue area, population density, disaster damage condition and the number of rescue workers taking part in evacuation actions.
And determining all the evacuees according to the first preset value, and selecting one evacuation manager from all the evacuees to be responsible for overall management of all the evacuation actions. And selecting the evacuee corresponding to the maximum value of the first pass number from all evacuees as the evacuee manager. The larger the value of the first pass number is, the more familiar the pass condition of the disaster affected area and the placement point the corresponding evacuee can get, the more reasonable arrangement or adjustment of the evacuation action can be achieved, and the effect of improving the evacuation efficiency is achieved. The other evacuees than the evacuation manager are the base evacuees.
After the initial personnel set is determined, a passing route of the initial personnel in the initial personnel set passing through the adjacent area and the placement point is obtained, and then the historical passing times of each initial personnel, namely the second passing times, are determined in the passing route. The adjacent area is an area bordering the placement point and/or the disaster-stricken area. The second pass number indicates the number of passes through the placement point and passes through other places around the periphery, and the larger the second pass number is, the more the number of passes through the adjacent area is, and the more familiar the personnel condition and the route condition of the peripheral area are. And taking the initial personnel with the second pass times larger than the second pass times preset value as the receiving personnel of the placement point.
Then, a disaster receiving person is required to select from the receiving persons to receive the setting work of the disaster receiving person responsible for overall management of the setting point. The receiving personnel corresponding to the maximum value of the second pass number is used as receiving management personnel, the receiving management personnel has more knowledge of surrounding adjacent areas, the requirements of personnel in different areas can be better known, and poor communication caused by dialects and other problems can be avoided to a certain extent.
The disaster risk management method based on the region and the historical data machine learning further comprises the following steps:
and transmitting evacuation support information to the evacuee and the recipient according to the disaster area and the placement point, wherein the evacuation support information is used for providing the evacuee and the recipient with position information of the placement point and the disaster area and disaster conditions of the disaster area.
After the evacuation personnel and the receiving personnel are determined, evacuation support information is sent to all the evacuation personnel and the receiving personnel so as to inform the personnel that the personnel need to participate in corresponding support work, and then the positions of the placement points and the disaster areas are sent to the corresponding personnel so as to facilitate the personnel to achieve the appointed position for starting the support work. Meanwhile, the disaster situation is sent to the evacuee and the receiver, on one hand, the evacuee and the receiver are reminded of the disaster situation in the disaster area, the disaster situation in the process of reaching the designated position is noted, and the approximate rescue work can be known through the disaster situation. The method of transmitting the evacuation support information is not limited, and may be a short message, a telephone, a broadcast, or the like.
An embodiment of the present application provides a disaster risk management system 200 based on region and history data machine learning, referring to fig. 2, the disaster risk management system 200 based on region and history data machine learning includes:
the area determining module 201 is configured to determine a disaster area and a placement point;
an initial personnel determining module 202, configured to determine an initial personnel set according to the disaster area and the placement points;
the rescue personnel determining module 203 is configured to determine a receiving personnel and an evacuating personnel according to the historical traffic route of each initial personnel in the initial personnel set and the historical traffic times corresponding to the historical traffic route, where the receiving personnel are personnel receiving the disaster-stricken personnel at the location point, and the evacuating personnel are personnel evacuating the disaster-stricken personnel between the disaster-stricken area and the location point.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the described module, which is not described herein again.
The embodiment of the application discloses electronic equipment. Referring to fig. 3, the electronic apparatus includes a central processing unit (central processing unit, CPU) 301 that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage portion 307 into a random access memory (random access memory, RAM) 303. In the RAM 303, various programs and data required for the system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other by a bus. An input/output (I/O) interface 304 is also connected to the bus.
The following components are connected to the I/O interface 304: an input section 305 including a keyboard, a mouse, and the like; an output section 306 including a Cathode Ray Tube (CRT), a liquid crystal display (liquid crystal display, LCD), and the like, and a speaker, and the like; a storage portion 307 including a hard disk and the like; and a communication section 308 including a network interface card such as a local area network (local area network, LAN) card, a modem, or the like. The communication section 308 performs communication processing via a network such as the internet. A driver 309 is also connected to the I/O interface 304 as needed. A removable medium 310 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 309 as needed, so that a computer program read out therefrom is installed into the storage section 307 as needed.
In particular, the process described above with reference to flowchart fig. 1 may be implemented as a computer software program according to an embodiment of the application. For example, embodiments of the application include a computer program product comprising a computer program embodied on a machine-readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such embodiments, the computer program may be downloaded and installed from a network via the communication portion 308, and/or installed from the removable media 310. The above-described functions defined in the apparatus of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 301.
The computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any 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 (erasable programmable read only memory, EPROM), 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 context of this document, 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 the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. 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, radio Frequency (RF), and the like, or any suitable combination of the foregoing.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application is not limited to the specific combinations of the features described above, but also covers other embodiments which may be formed by any combination of the features described above or their equivalents without departing from the spirit of the application. Such as the above-mentioned features and the technical features having similar functions (but not limited to) applied for in the present application are replaced with each other.
Claims (10)
1. A disaster risk management method based on zone and history data machine learning, comprising:
determining disaster areas and placement points;
determining an initial personnel set according to the disaster affected area and the placement points;
and determining receiving personnel and evacuating personnel according to the historical passing route of each initial personnel in the initial personnel set and the historical passing times corresponding to the historical passing route, wherein the receiving personnel are personnel for receiving disaster-stricken personnel at the placement points, and the evacuating personnel are personnel for evacuating the disaster-stricken personnel between the disaster-stricken area and the placement points.
2. The method of disaster risk management based on compartment and history data machine learning according to claim 1, wherein said determining an initial set of people from said disaster affected area and said placement point comprises:
determining an initial personnel area according to a target point, the disaster affected area and the placement point, wherein the target point is the midpoint of a connecting line of the disaster affected area and the placement point;
and determining an initial personnel set according to the real-time positions of the personnel in the initial personnel area.
3. The disaster risk management method based on compartment and history data machine learning according to claim 1, wherein said determining a receiving person and an evacuating person according to the history traffic route of each of the initial persons in the initial person set and the history traffic number corresponding to the history traffic route comprises:
determining evacuation personnel according to the first pass times of each initial personnel in the initial personnel set between the disaster affected area and the placement point;
and determining the receiving personnel according to the second pass times of each initial personnel in the initial personnel set between the adjacent area and the placement point, wherein the adjacent area is an area bordered by the placement point and/or the disaster-stricken area.
4. The method for managing disaster risk based on compartment and history data machine learning according to claim 3, wherein said determining evacuation personnel based on the first pass number of each of said initial personnel in said initial personnel set between said disaster affected area and said placement point comprises:
when the first pass number is larger than a first pass number preset value, taking initial personnel corresponding to the first pass number larger than the first pass number preset value as evacuation personnel.
5. The method of disaster risk management based on compartment and history data machine learning according to claim 3, wherein said determining a receiving person according to a second pass number of each of said initial person sets between an adjacent area and said placement point comprises:
and when the second number of the passes between the adjacent area and the placement point is larger than a second number of times preset value, taking an initial person corresponding to the second number of passes larger than the second number of times preset value as a receiving person.
6. The method for managing disaster risk based on compartment and history data machine learning according to claim 1, wherein said determining a disaster area comprises:
determining a plurality of grid areas;
and determining disaster-affected areas in the grid areas according to the rainwater amount, the drainage amount, the soil data and the topography data in each grid area.
7. The method of disaster risk management based on compartment and history data machine learning according to claim 6, wherein said determining disaster affected areas in a plurality of grid areas according to the amount of rain water, the amount of water, the soil property data and the topography data in each of said grid areas comprises:
determining the actual water quantity of the grid area according to the rainwater quantity and the topography data;
determining a receivable amount of rain water according to the drainage amount and the soil property data of the grid area;
determining a water quantity difference value of each grid area according to the actual water quantity and the receivable rainwater quantity;
and determining the grid area in which the water quantity difference reaches the water quantity threshold as a disaster area.
8. The method for managing disaster risk based on compartment and history data machine learning according to claim 7, wherein said determining an actual water volume of a grid area based on said amount of rain water and said topography data comprises:
calculating the associated water quantity of each grid area according to the topography data, wherein the associated water quantity is the rainwater quantity flowing into the grid area from other grid areas bordering the grid area;
and adding the associated water quantity and the rainwater quantity to obtain the actual water quantity.
9. The method for managing disaster risk based on compartment and history data machine learning according to claim 1, wherein the determining the placement point comprises:
and determining at least one placement point according to the distance between the disaster affected area and the placement point, wherein the distance between the disaster affected area and the placement point is smaller than a distance preset value.
10. The method of disaster risk management based on compartment and history data machine learning of claim 1, further comprising:
and sending evacuation support information to the evacuee and the receiver according to the disaster area and the placement point, wherein the evacuation support information is used for providing the location information of the placement point and the disaster area and the disaster situation of the disaster area for the evacuee and the receiver.
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