CN111429698A - Geological disaster early warning system - Google Patents
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- CN111429698A CN111429698A CN202010215151.4A CN202010215151A CN111429698A CN 111429698 A CN111429698 A CN 111429698A CN 202010215151 A CN202010215151 A CN 202010215151A CN 111429698 A CN111429698 A CN 111429698A
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Abstract
The invention belongs to the technical field of geological disaster early warning, and discloses a geological disaster early warning system, which comprises: the system comprises a vibration detection module, a geothermal detection module, a mobile monitoring module, a ground subsidence detection module, a main control module, a geological structure identification module, a disaster model construction module, a judgment module, an early warning module and a display module. According to the invention, through the geological structure recognition module, the proper size parameters can be selected according to different conditions of different areas of the image, so that the geological structure recognition precision is improved; meanwhile, the three-dimensional geological disaster model and the disaster area geological model constructed by the disaster model construction module are constructed based on the interpolated drilling data, so that the occurrence state of the geological disaster in the space can be reflected more truly; the three-dimensional model is connected with the database, and geological disaster information can be edited and inquired.
Description
Technical Field
The invention belongs to the technical field of geological disaster early warning, and particularly relates to a geological disaster early warning system.
Background
The geological disaster refers to a rock-soil body movement event which is caused by natural or artificial action and most of the two actions in a synergistic manner and can relatively strongly damage human lives and properties and living environment on the earth surface layer. The geological disaster has dual nature of natural evolution and man-made induction in cause, which is not only a component of the natural disaster, but also belongs to the category of the man-made disaster. In a certain sense, geological disasters are a problem with social attributes and become important factors restricting the development of socio-economic and people's living. Therefore, the prevention and control of geological disasters not only means prevention, avoidance and engineering management, but also means the effort of improving the quality of human beings on the basis of high-level social consciousness, and the geological environment is consciously protected by restricting public behaviors through formulating public policies or government laws, so that the aim of avoiding or reducing the geological disasters is fulfilled. However, the existing geological disaster early warning system has poor identification precision on geological structures; meanwhile, disaster information cannot be displayed in detail on the geological model.
In summary, the problems of the prior art are as follows: the existing geological disaster early warning system has poor geological structure recognition precision; meanwhile, disaster information cannot be displayed in detail on the geological model.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a geological disaster early warning system.
The invention is realized in this way, a geological disaster early warning system includes:
the system comprises a vibration detection module, a geothermal detection module, a mobile monitoring module, a ground subsidence detection module, a main control module, a geological structure identification module, a disaster model construction module, a judgment module, an early warning module and a display module;
the vibration detection module is connected with the main control module and used for detecting geological vibration data through the vibration sensor;
the geothermal detection module is connected with the main control module and used for detecting geothermal data through a geothermal detector;
the mobile monitoring module is connected with the main control module and used for detecting geological movement data through the mobile detector;
the ground subsidence detection module is connected with the main control module and used for detecting geological subsidence data through the ground subsidence detector;
the main control module is connected with the vibration detection module, the geothermal detection module, the movement monitoring module, the ground subsidence detection module, the geological structure identification module, the disaster model construction module, the judgment module, the early warning module and the display module and is used for controlling the normal work of each module through the main controller;
the geological structure recognition module is connected with the main control module and used for recognizing the geological structure through a recognition program;
the disaster model building module is connected with the main control module and used for building a geological disaster model through a modeling program;
the judging module is connected with the main control module and is used for judging the degree of the geological disaster through a judging program;
the early warning module is connected with the main control module and is used for carrying out alarm notification according to the judgment result through an early warning program;
and the display module is connected with the main control module and used for displaying the detected vibration, geothermal heat, movement and subsidence data, the identification result, the model and the judgment result through the display.
Further, the geological structure identification module identification method comprises the following steps:
(1) segmenting a noise region of an image of geological structure information into Y regions by an extraction program, wherein Y is an even number, the regions are rectangular regions or square regions, and the area size values of the regions
Wherein i, j are the middle point pixel values of the region, and Z is an odd value;
(2) calculating the average variation function R (0) of the average variation function R (theta) of each region in the horizontal direction and the average variation function R (90) of each region in the vertical direction, and calculating the relative sizes of the average variation function values of the region in the horizontal direction and the vertical direction according to the R (0) and the R (90) of the region η;
(3) judging whether the property of the area is a smooth area, an edge area or a composite area according to the η value, and judging whether the area belongs to a horizontal area or a vertical area according to the direction of an edge when the area is judged to be the edge area;
(4) according to the property of the region, the wavelet transformation with the same or different sizes is carried out on the region in the horizontal direction and the vertical direction.
Further, if the region is a smooth region, wavelet transformation of the first scale is performed in the horizontal and vertical directions, respectively, and a maximum point α of the wavelet transformation in the horizontal direction and a maximum point β of the wavelet transformation in the vertical direction are found.
Further, specifically, the step (4) is that if the region is a vertical region, performing wavelet transform of a first scale in the vertical direction, performing wavelet transform of a second scale in the horizontal direction, and finding a maximum point α of the wavelet transform of the horizontal direction and a maximum point β of the wavelet transform of the vertical direction, where the first size is smaller than the second size.
Further, the disaster model construction module construction method comprises the following steps:
1) collecting and sorting the related data of the geological disaster information model through a modeling program, and carrying out digital processing on the related data;
2) constructing a three-dimensional geological disaster model; constructing a geological disaster information database based on the data after digital processing;
3) and associating the three-dimensional geological disaster model with a geological disaster information database to establish the three-dimensional geological disaster information model.
Further, the building of the three-dimensional geological disaster model comprises:
constructing the surface of a geological disaster body: performing three-dimensional visualization analysis and image dynamic analysis processing on the obtained geological image data, and extracting the surface range and shape information of a geological disaster body; delineating the extracted orthographic image of the geological disaster body, converting the delineated range into coordinate data of points, generating a boundary line and a surface of the geological disaster body based on the converted coordinate data, and superposing the generated boundary line and the surface of the geological disaster body to the established three-dimensional terrain environment model;
drilling interpolation: inserting virtual drill holes among the existing drill holes according to the existing drill hole data, and then combining a kriging method in an ArcGIS statistical method to perform interpolation processing on the drill hole data;
modeling a geological disaster body: and (3) extracting the drilling data in a layering manner, constructing a stratum TIN model of the area where the geological disaster is located and surface and bottom TIN models of the geological disaster body, determining the unfavorable geological range of each layer, and filling the stratum attribute between the layers.
Further, the building of the three-dimensional terrain environment model comprises: vectorizing the topographic map, storing contour line files and elevation point files containing elevation value information in a database as data sources for constructing a digital elevation model, and creating a three-dimensional topographic environment model.
Further, the main control module comprises:
the data acquisition unit is used for acquiring geological monitoring data acquired by the vibration detection module, the geothermal detection module, the mobile monitoring module and the ground subsidence detection module;
and the statistical unit is used for acquiring analysis configuration information of the geological monitoring data, analyzing the geological monitoring data to acquire analysis data, preprocessing the analysis data to acquire audit data, and counting the audit data in unit time to acquire the statistical data.
Further, the judging module comprises:
the classification analysis unit is used for analyzing the geological monitoring data through a classification algorithm, predicting the probability of geological disasters in a certain area, and analyzing and predicting the cause of the geological disasters through comparison data;
the cluster analysis unit is used for carrying out cluster analysis on various influence factors of the disaster through a cluster algorithm to distinguish the group characteristics of the disaster;
the association rule analysis unit is used for analyzing association rules between the rule of geological disaster occurrence in a certain area and the rainfall records through an association rule mining algorithm;
the regression analysis unit is used for analyzing the cause of the geological disaster through a general regression algorithm mainly based on linear regression;
the vector similarity analysis unit is used for mining and comparing the incidence relation of the two groups of data through a vector similarity algorithm and mining the incidence relation between the rainfall variation rule and the geological disaster occurrence rule;
and the time sequence analysis unit is used for predicting the occurrence possibility of the future geological disaster based on the change rule discovered by the geological disaster historical data by using a general time sequence analysis algorithm mainly based on an autoregressive moving average model.
Further, the early warning module combines geological data processed by the main control module with geographic information to generate disaster early warning data, and when the disaster early warning data exceeds an alert value, the monitoring platform sends the early warning information to an area corresponding to the disaster early warning data exceeding the alert value through a wireless signal;
the monitoring platform removes the geographic information areas which exceed the warning value and are lower than the warning value and smaller than the threshold value from the disaster early warning data to generate rescue evacuation data;
when a rescue route is generated, selecting a rescue target, and generating the rescue route by using the rescue evacuation data as a constraint condition and adopting a genetic algorithm;
and when an evacuation route is generated, generating an evacuation destination according to the disaster early warning data, and generating the evacuation route by taking the rescue evacuation data as a constraint condition and adopting a genetic algorithm.
The invention has the advantages and positive effects that: according to the invention, through the geological structure recognition module, the proper size parameters can be selected according to different conditions of different areas of the image, so that the geological structure recognition precision is improved; meanwhile, the three-dimensional geological disaster model and the disaster area geological model constructed by the disaster model construction module are constructed based on the interpolated drilling data, so that the occurrence state of the geological disaster in the space can be reflected more truly; the three-dimensional model is connected with the database, and geological disaster information can be edited and inquired.
Drawings
Fig. 1 is a block diagram of a geological disaster warning system according to an embodiment of the present invention.
In the figure: 1. a vibration detection module; 2. a geothermal detection module; 3. a mobile monitoring module; 4. a ground subsidence detection module; 5. a main control module; 6. a geological structure identification module; 7. a disaster model building module; 8. a judgment module; 9. an early warning module; 10. and a display module.
Fig. 2 is a flowchart of a geologic structure identification module identification method according to an embodiment of the present invention.
Fig. 3 is a flowchart of a disaster model building module building method according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a main control module according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a determining module according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a geological disaster early warning system provided by the embodiment of the present invention includes: the system comprises a vibration detection module 1, a geothermal detection module 2, a mobile monitoring module 3, a ground subsidence detection module 4, a main control module 5, a geological structure identification module 6, a disaster model construction module 7, a judgment module 8, an early warning module 9 and a display module 10.
The vibration detection module 1 is connected with the main control module 5 and used for detecting geological vibration data through a vibration sensor;
the geothermal detection module 2 is connected with the main control module 5 and used for detecting geothermal data through a geothermal detector;
the mobile monitoring module 3 is connected with the main control module 5 and used for detecting geological movement data through the mobile detector;
the ground subsidence detection module 4 is connected with the main control module 5 and used for detecting geological subsidence data through the ground subsidence detector;
the main control module 5 is connected with the vibration detection module 1, the geothermal detection module 2, the mobile monitoring module 3, the subsidence detection module 4, the geological structure identification module 6, the disaster model construction module 7, the judgment module 8, the early warning module 9 and the display module 10, and is used for controlling the normal work of each module through the main controller;
the geological structure recognition module 6 is connected with the main control module 5 and used for recognizing the geological structure through a recognition program;
the disaster model building module 7 is connected with the main control module 5 and used for building a geological disaster model through a modeling program;
the judging module 8 is connected with the main control module 5 and used for judging the degree of the geological disaster through a judging program;
the early warning module 9 is connected with the main control module 5 and is used for carrying out alarm notification according to the judgment result through an early warning program;
and the display module 10 is connected with the main control module 5 and used for displaying the detected vibration, geothermal heat, movement and subsidence data, the identification result, the model and the judgment result through a display.
As shown in fig. 2, the identification method of the geological structure identification module 6 provided by the embodiment of the present invention is as follows:
s101, dividing a noise region of the image of the geological structure information into Y regions through an extraction program, wherein Y is an even number, the regions are rectangular regions or square regions, and the area size values of the regions
Where i, j are the middle point pixel values of the region and Z is an odd value.
S102, calculating the average variation function R (0 degree) of the average variation function R (theta) of each area in the horizontal direction and the average variation function R (90 degrees) of each area in the vertical direction, and calculating the variable η of the relative sizes of the average variation function values of the area in the horizontal direction and the vertical direction according to the R (0 degree) and the R (90 degrees) of the area.
S103, judging whether the property of the area is a smooth area, an edge area or a composite area according to the η value, and judging whether the area belongs to a horizontal area or a vertical area according to the direction of the edge when the area is judged to be the edge area.
And S104, performing wavelet transformation on the region in the horizontal direction and the vertical direction in the same or different sizes according to the property of the region.
If the region provided by the embodiment of the present invention is a smooth region, wavelet transform of the first scale is performed in the horizontal direction and the vertical direction, and a maximum point α of wavelet transform in the horizontal direction and a maximum point β of wavelet transform in the vertical direction are found.
The step (4) provided in the embodiment of the present invention is specifically that, if the region is a vertical region, performing wavelet transform of a first scale in the vertical direction, performing wavelet transform of a second scale in the horizontal direction, and finding a maximum point α of the wavelet transform in the horizontal direction and a maximum point β of the wavelet transform in the vertical direction, where the first size is smaller than the second size.
As shown in fig. 3, a method for constructing the disaster model construction module 7 according to the embodiment of the present invention is as follows:
s201, collecting and arranging the related data of the geological disaster information model through a modeling program, and carrying out digital processing on the related data.
S202, constructing a three-dimensional geological disaster model; and constructing a geological disaster information database based on the data after the digital processing.
And S203, associating the three-dimensional geological disaster model with a geological disaster information database, and establishing the three-dimensional geological disaster information model.
The method for constructing the three-dimensional geological disaster model provided by the embodiment of the invention comprises the following steps:
constructing the surface of a geological disaster body: performing three-dimensional visualization analysis and image dynamic analysis processing on the obtained geological image data, and extracting the surface range and shape information of a geological disaster body; delineating the extracted orthographic image of the geological disaster body, converting the delineated range into coordinate data of points, generating a boundary line and a surface of the geological disaster body based on the converted coordinate data, and superposing the generated boundary line and the surface of the geological disaster body to the established three-dimensional terrain environment model;
drilling interpolation: inserting virtual drill holes among the existing drill holes according to the existing drill hole data, and then combining a kriging method in an ArcGIS statistical method to perform interpolation processing on the drill hole data;
modeling a geological disaster body: and (3) extracting the drilling data in a layering manner, constructing a stratum TIN model of the area where the geological disaster is located and surface and bottom TIN models of the geological disaster body, determining the unfavorable geological range of each layer, and filling the stratum attribute between the layers.
The invention provides a method for constructing a three-dimensional terrain environment model, which comprises the following steps: vectorizing the topographic map, storing contour line files and elevation point files containing elevation value information in a database as data sources for constructing a digital elevation model, and creating a three-dimensional topographic environment model.
As shown in fig. 4, the main control module 5 in the embodiment of the present invention includes:
and the data acquisition unit 51 is used for acquiring geological monitoring data acquired by the vibration detection module, the geothermal detection module, the mobile monitoring module and the ground subsidence detection module.
The statistical unit 52 is configured to obtain analysis configuration information of the geological monitoring data, analyze the geological monitoring data to obtain analysis data, preprocess the analysis data to obtain audit data, and count the audit data in unit time to obtain the statistical data.
As shown in fig. 5, the determining module 8 in the embodiment of the present invention includes:
and the classification analysis unit 81 is used for analyzing the geological monitoring data through a classification algorithm, predicting the probability of geological disasters in a certain area, and analyzing and predicting the cause of the geological disasters through comparison data.
And the cluster analysis unit 82 is used for carrying out cluster analysis on various influence factors of the disaster through a clustering algorithm to distinguish the group characteristics of the disaster.
And the association rule analysis unit 83 is configured to analyze an association rule between a rule of a certain area where a geological disaster occurs and a rainfall record through an association rule mining algorithm.
And a regression analysis unit 84 for analyzing the cause of the geological disaster by a general regression algorithm mainly based on linear regression.
And the vector similarity analysis unit 85 is used for mining and comparing the association relationship of the two groups of data through a vector similarity algorithm, and mining the association relationship between the rainfall variation rule and the geological disaster occurrence rule.
And the time series analysis unit 86 is used for predicting the occurrence possibility of the future geological disaster based on the change rule found by the geological disaster historical data by using a general time series analysis algorithm mainly based on an autoregressive moving average model.
The early warning module in the embodiment of the invention combines geological data processed by the main control module with the geographic information to generate disaster early warning data, and when the disaster early warning data exceeds an alert value, the monitoring platform sends the early warning information to an area corresponding to the disaster early warning data exceeding the alert value through a wireless signal.
And the monitoring platform removes the geographic information areas which exceed the warning value and are lower than the warning value and less than the threshold value from the disaster early warning data to generate rescue and evacuation data.
When a rescue route is generated, a rescue target is selected, and the rescue evacuation data is used as a constraint condition to generate the rescue route by adopting a genetic algorithm.
And when an evacuation route is generated, generating an evacuation destination according to the disaster early warning data, and generating the evacuation route by taking the rescue evacuation data as a constraint condition and adopting a genetic algorithm.
When the embodiment of the invention works, firstly, the geological vibration data is detected by the vibration detection module 1 by using the vibration sensor; detecting geothermal data by a geothermal detector through a geothermal detection module 2; detecting geological movement data by a movement detector through a movement monitoring module 3; detecting geological collapse data by a ground collapse detector through a ground collapse detection module 4; secondly, the main control module 5 identifies the geological structure by using an identification program through a geological structure identification module 6; a geological disaster model is built by a disaster model building module 7 by utilizing a modeling program; judging the degree of geological disaster by a judging module 8 by using a judging program; then, the early warning module 9 utilizes an early warning program to perform alarm notification according to the judgment result; finally, the display module 10 is used for displaying the detected vibration, geothermy, movement and subsidence data, the identification result, the model and the judgment result.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. The geological disaster early warning system is characterized by comprising:
the system comprises a vibration detection module, a geothermal detection module, a mobile monitoring module, a ground subsidence detection module, a main control module, a geological structure identification module, a disaster model construction module, a judgment module, an early warning module and a display module;
the vibration detection module is connected with the main control module and used for detecting geological vibration data through the vibration sensor;
the geothermal detection module is connected with the main control module and used for detecting geothermal data through a geothermal detector;
the mobile monitoring module is connected with the main control module and used for detecting geological movement data through the mobile detector;
the ground subsidence detection module is connected with the main control module and used for detecting geological subsidence data through the ground subsidence detector;
the main control module is connected with the vibration detection module, the geothermal detection module, the movement monitoring module, the ground subsidence detection module, the geological structure identification module, the disaster model construction module, the judgment module, the early warning module and the display module and is used for controlling the normal work of each module through the main controller;
the geological structure recognition module is connected with the main control module and used for recognizing the geological structure through a recognition program;
the disaster model building module is connected with the main control module and used for building a geological disaster model through a modeling program;
the judging module is connected with the main control module and is used for judging the degree of the geological disaster through a judging program;
the early warning module is connected with the main control module and is used for carrying out alarm notification according to the judgment result through an early warning program;
and the display module is connected with the main control module and used for displaying the detected vibration, geothermal heat, movement and subsidence data, the identification result, the model and the judgment result through the display.
2. The geological disaster early warning system as claimed in claim 1, wherein the identification method of the geological structure identification module is as follows:
(1) segmenting a noise region of an image of geological structure information into Y regions by an extraction program, wherein Y is an even number, the regions are rectangular regions or square regions, and the area size values of the regions
Wherein i, j are the middle point pixel values of the region, and Z is an odd value;
(2) calculating the average variation function R (0) of the average variation function R (theta) of each region in the horizontal direction and the average variation function R (90) of each region in the vertical direction, and calculating the relative sizes of the average variation function values of the region in the horizontal direction and the vertical direction according to the R (0) and the R (90) of the region η;
(3) judging whether the property of the area is a smooth area, an edge area or a composite area according to the η value, and judging whether the area belongs to a horizontal area or a vertical area according to the direction of an edge when the area is judged to be the edge area;
(4) according to the property of the region, the wavelet transformation with the same or different sizes is carried out on the region in the horizontal direction and the vertical direction.
3. The geological disaster early warning system as claimed in claim 2, wherein if the region is a smooth region, the wavelet transform of the first scale is performed in the horizontal and vertical directions, respectively, and the maximum point α of the wavelet transform in the horizontal direction and the maximum point β of the wavelet transform in the vertical direction are found.
4. A geological disaster early warning system as claimed in claim 2, wherein said (4) is specifically configured to perform a wavelet transform of a first scale in a vertical direction if the region is a vertical region, perform a wavelet transform of a second scale in a horizontal direction, and find a maximum point α of the wavelet transform of the horizontal direction and a maximum point β of the wavelet transform of the vertical direction, wherein the first size is smaller than the second size.
5. The geological disaster early warning system as claimed in claim 1, wherein the disaster model building module is constructed by the following method:
1) collecting and sorting the related data of the geological disaster information model through a modeling program, and carrying out digital processing on the related data;
2) constructing a three-dimensional geological disaster model; constructing a geological disaster information database based on the data after digital processing;
3) and associating the three-dimensional geological disaster model with a geological disaster information database to establish the three-dimensional geological disaster information model.
6. The geological disaster early warning system as claimed in claim 5, wherein said constructing a three-dimensional geological disaster model comprises:
constructing the surface of a geological disaster body: performing three-dimensional visualization analysis and image dynamic analysis processing on the obtained geological image data, and extracting the surface range and shape information of a geological disaster body; delineating the extracted orthographic image of the geological disaster body, converting the delineated range into coordinate data of points, generating a boundary line and a surface of the geological disaster body based on the converted coordinate data, and superposing the generated boundary line and the surface of the geological disaster body to the established three-dimensional terrain environment model;
drilling interpolation: inserting virtual drill holes among the existing drill holes according to the existing drill hole data, and then combining a kriging method in an ArcGIS statistical method to perform interpolation processing on the drill hole data;
modeling a geological disaster body: and (3) extracting the drilling data in a layering manner, constructing a stratum TIN model of the area where the geological disaster is located and surface and bottom TIN models of the geological disaster body, determining the unfavorable geological range of each layer, and filling the stratum attribute between the layers.
7. The geological disaster early warning system as recited in claim 6 wherein said constructing a three-dimensional terrain environment model comprises: vectorizing the topographic map, storing contour line files and elevation point files containing elevation value information in a database as data sources for constructing a digital elevation model, and creating a three-dimensional topographic environment model.
8. The geological disaster early warning system as claimed in claim 1, wherein said master control module comprises:
the data acquisition unit is used for acquiring geological monitoring data acquired by the vibration detection module, the geothermal detection module, the mobile monitoring module and the ground subsidence detection module;
and the statistical unit is used for acquiring analysis configuration information of the geological monitoring data, analyzing the geological monitoring data to acquire analysis data, preprocessing the analysis data to acquire audit data, and counting the audit data in unit time to acquire the statistical data.
9. The geological disaster early warning system as claimed in claim 1, wherein said judging module comprises:
the classification analysis unit is used for analyzing the geological monitoring data through a classification algorithm, predicting the probability of geological disasters in a certain area, and analyzing and predicting the cause of the geological disasters through comparison data;
the cluster analysis unit is used for carrying out cluster analysis on various influence factors of the disaster through a cluster algorithm to distinguish the group characteristics of the disaster;
the association rule analysis unit is used for analyzing association rules between the rule of geological disaster occurrence in a certain area and the rainfall records through an association rule mining algorithm;
the regression analysis unit is used for analyzing the cause of the geological disaster through a general regression algorithm mainly based on linear regression;
the vector similarity analysis unit is used for mining and comparing the incidence relation of the two groups of data through a vector similarity algorithm and mining the incidence relation between the rainfall variation rule and the geological disaster occurrence rule;
and the time sequence analysis unit is used for predicting the occurrence possibility of the future geological disaster based on the change rule discovered by the geological disaster historical data by using a general time sequence analysis algorithm mainly based on an autoregressive moving average model.
10. The geological disaster early warning system as claimed in claim 1, wherein the early warning module combines geological data processed by the main control module with geographic information to generate disaster early warning data, and when the disaster early warning data exceeds a warning value, the monitoring platform sends the early warning information to an area corresponding to the disaster early warning data exceeding the warning value through a wireless signal;
the monitoring platform removes the geographic information areas which exceed the warning value and are lower than the warning value and smaller than the threshold value from the disaster early warning data to generate rescue evacuation data;
when a rescue route is generated, selecting a rescue target, and generating the rescue route by using the rescue evacuation data as a constraint condition and adopting a genetic algorithm;
and when an evacuation route is generated, generating an evacuation destination according to the disaster early warning data, and generating the evacuation route by taking the rescue evacuation data as a constraint condition and adopting a genetic algorithm.
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| CN112685519A (en) * | 2020-12-09 | 2021-04-20 | 深圳市易智博网络科技有限公司 | Geological disaster-based underground rock stratum plane analysis method |
| CN113012398A (en) * | 2021-02-20 | 2021-06-22 | 中煤航测遥感集团有限公司 | Geological disaster monitoring and early warning method and device, computer equipment and storage medium |
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