Strong aftershock prediction method, device and electronic equipment

Abstract

The application provides a strong aftershock prediction method and device and electronic equipment, and relates to the technical field of earthquake prediction, and comprises the following steps: after obtaining the earthquake data of a target geographical area in a historical time period, the target geographical area is subjected to grid processing, the earthquake probability of a target grid area in a reference time period is calculated, and then the dangerous grid area in the target geographical area in a prediction time period is determined according to the earthquake probability of all grid areas in the reference time period. The application fills the gap that the occurrence position of strong aftershocks cannot be accurately predicted in the prior art, and thus can provide great technical support for post-earthquake disaster relief work.

Description

Technical Field

[0001] This invention relates to the technical field of earthquake prediction, and in particular to a method, apparatus, and electronic device for predicting strong aftershocks. Background Technology

[0002] The full release of earthquake energy takes time, and aftershocks generally follow the main shock. Strong aftershocks, in particular, can cause further damage or collapse of existing buildings, resulting in new casualties. Therefore, predicting strong aftershocks is a key concern for seismologists. Many scholars have conducted in-depth research on the magnitude and timing of strong aftershocks from moderate to strong earthquakes, but research on their locations is relatively limited. When the rupture zone of an aftershock is large, accurate prediction of its location would greatly assist post-earthquake relief efforts. Therefore, a method for predicting the location of strong aftershocks is urgently needed. Summary of the Invention

[0003] The purpose of this invention is to provide a method, device, and electronic device for predicting strong aftershocks, so as to fill the gap in the existing technology that cannot accurately predict the location of strong aftershocks, and thus provide great technical support for post-earthquake disaster relief work.

[0004] In a first aspect, the present invention provides a method for predicting strong aftershocks, comprising: acquiring seismic data of a target geographical area within a historical time period; wherein the seismic data includes: seismic information of strong earthquakes and seismic information of aftershocks; performing gridding processing on the target geographical area to obtain multiple grid areas; calculating the probability of earthquake occurrence of the target grid area within a reference time period based on the seismic data within the historical time period; wherein the target grid area represents any area among the multiple grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period; determining dangerous grid areas in the target geographical area within a prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period; wherein the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to the duration of the reference time period; the dangerous grid areas represent grid areas predicted to experience strong aftershocks.

[0005] In an optional implementation, calculating the probability of an earthquake occurring in the target grid area within a reference time period based on earthquake data within the historical time period includes: determining a complete magnitude lower limit for aftershocks based on earthquake data within the historical time period; constructing an earthquake time series for the target grid area based on the earthquake data and the complete magnitude lower limit; wherein the earthquake time series includes the number of earthquakes with magnitudes greater than the complete magnitude lower limit within each unit time; calculating the earthquake intensity function of the target grid area within a first time period and a second time period based on the earthquake time series of the target grid area, obtaining a first earthquake intensity function and a second earthquake intensity function for the target grid area; wherein the start time of the first time period is any moment in the changing time period, and the changing time period is related to the historical time period. The start times of the time intervals are the same, and the end times of the changing time intervals and the first time interval are both the start times of the reference time interval; the start time of the second time interval is the same as that of the first time interval, and the end time of the second time interval is the same as that of the reference time interval; the first seismic intensity function of the target grid region is standardized to obtain the first standardized seismic intensity function of the target grid region in the first time interval, and the second seismic intensity function of the target grid region is standardized to obtain the second standardized seismic intensity function of the target grid region in the second time interval; based on the first standardized seismic intensity function and the second standardized seismic intensity function, the probability of earthquake occurrence in the target grid region in the reference time interval is determined.

[0006] In an optional implementation, the first seismic intensity function of the target grid region is standardized, including: calculating the seismic intensity function of each grid region within the first time period to obtain the first seismic intensity function of each grid region; calculating the average value and standard deviation of the seismic intensity function of all grid regions within the first time period based on the first seismic intensity function of all grid regions; and standardizing the first seismic intensity function of the target grid region based on the average value and standard deviation of the seismic intensity function to obtain the first standardized seismic intensity function.

[0007] In an optional implementation, determining the probability of earthquake occurrence in the target grid area within the reference time period based on the first standardized seismic intensity function and the second standardized seismic intensity function includes: calculating the seismic intensity variation function of the target grid area within the reference time period based on the first standardized seismic intensity function and the second standardized seismic intensity function; traversing the variation time period and calculating the average seismic intensity variation of the target grid area within the reference time period based on the seismic intensity variation function; and determining the probability of earthquake occurrence in the target grid area within the reference time period based on the average seismic intensity variation.

[0008] In an optional implementation, determining the dangerous grid area in the target geographic area within the prediction time period based on the seismic probability of all grid areas within the reference time period includes: calculating the average seismic probability of the target geographic area within the reference time period based on the seismic probability of all grid areas within the reference time period; determining the probability gain of the target grid area within the reference time period based on the average seismic probability and the seismic probability of the target grid area within the reference time period; and determining the dangerous grid area based on the probability gain of all grid areas within the reference time period and a preset threshold.

[0009] In an optional implementation, determining the complete magnitude lower limit of aftershocks based on earthquake data within the historical time period includes: fitting the earthquake data within the historical time period using a GR relationship to obtain the complete magnitude lower limit of the aftershocks.

[0010] In an optional implementation, determining the probability of earthquake occurrence in the target grid area within the reference time period based on the average seismic intensity change includes: calculating the square of the average seismic intensity change in the target grid area within the reference time period to obtain the probability of earthquake occurrence in the target grid area within the reference time period.

[0011] Secondly, the present invention provides a strong aftershock prediction device, comprising: an acquisition module for acquiring seismic data of a target geographical area within a historical time period; wherein the seismic data includes seismic information of strong earthquakes and seismic information of aftershocks; a processing module for performing gridding processing on the target geographical area to obtain multiple grid areas; a calculation module for calculating the probability of earthquake occurrence of the target grid area within a reference time period based on the seismic data within the historical time period; wherein the target grid area represents any area among the multiple grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period; and a determination module for determining dangerous grid areas in the target geographical area within a prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period; wherein the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to the duration of the reference time period; and the dangerous grid areas represent grid areas predicted to experience strong aftershocks.

[0012] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the steps of the strong aftershock prediction method described in any of the foregoing embodiments.

[0013] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the strong aftershock prediction method described in any of the foregoing embodiments.

[0014] The present invention provides a method for predicting strong aftershocks, comprising: acquiring seismic data of a target geographical area within a historical time period; wherein the seismic data includes: seismic information of strong earthquakes and seismic information of aftershocks; performing gridding processing on the target geographical area to obtain multiple grid areas; calculating the probability of earthquake occurrence of the target grid area within a reference time period based on the seismic data within the historical time period; wherein the target grid area represents any area among the multiple grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period; determining the dangerous grid areas in the target geographical area within the prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period; wherein the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to the duration of the reference time period; the dangerous grid areas represent grid areas where strong aftershocks are predicted to occur.

[0015] The strong aftershock prediction method provided by this invention, after acquiring earthquake data of a target geographical area over a historical period, performs gridding processing on the target geographical area, calculates the probability of earthquake occurrence in the target grid area within a reference time period, and then determines the dangerous grid areas in the target geographical area within the prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period. This invention fills the gap in the existing technology that cannot accurately predict the location of strong aftershocks, thus providing significant technical support for post-earthquake disaster relief work. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 A flowchart of a strong aftershock prediction method provided in an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram illustrating multiple time periods in a strong aftershock prediction method provided in an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram illustrating multiple time periods in another strong aftershock prediction method provided in an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram illustrating an example of strong aftershock prediction provided by an embodiment of the present invention;

[0021] Figure 5 A functional block diagram of a strong aftershock prediction device provided in an embodiment of the present invention;

[0022] Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0025] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0026] Example 1

[0027] Figure 1 A flowchart of a strong aftershock prediction method provided in an embodiment of the present invention is shown below. Figure 1 As shown, the method specifically includes the following steps:

[0028] Step S102: Obtain earthquake data for the target geographic area within a historical time period.

[0029] Specifically, when performing strong aftershock prediction on a target geographical area, this invention requires the use of historical seismic data for that area. This seismic data includes information on both the strong earthquake and the aftershocks. The seismic information includes the time, location (i.e., latitude and longitude of the earthquake), and magnitude of the earthquake. Generally, the target geographical area represents the spatial distribution range of the aftershocks.

[0030] This invention is applicable to short-term aftershock prediction. The historical time period is generally 3 to 5 days. Accordingly, the earthquake data includes information on the strong earthquake after the initial earthquake and the earthquake information of aftershocks within the following 3 to 5 days. Based on the earthquake data within the aforementioned historical time period, the aftershock situation within the next 1 to 3 days (exemplary) can be predicted. In this invention, the duration of the prediction time period is shorter than the duration of the historical time period.

[0031] Step S104: Grid the target geographic area to obtain multiple grid areas.

[0032] In order to accurately predict the location of strong aftershocks, after determining the target geographical area, this embodiment of the invention needs to perform grid processing on the target geographical area to obtain multiple grid areas. Optionally, in order to improve the accuracy of the predicted aftershock location, the size of each grid is approximately 0.05° during grid processing.

[0033] Step S106: Calculate the probability of earthquake occurrence in the target grid area within the reference time period based on earthquake data within the historical time period.

[0034] After gridding, in order to assess the safety of each grid region, this embodiment of the invention uses seismic data from historical time periods to calculate the probability of an earthquake occurring in the target grid region within a reference time period. The probability of an earthquake occurring in the target grid region within the reference time period is related to the earthquake intensity in the target grid region within the reference time period. The target grid region represents any region among multiple grid regions; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period. That is, the reference time period belongs to the historical time period and is the last part of the historical time period. Figure 2 As shown, t0 is the start time of the historical time period, t1 is the start time of the reference time period, and t2 is the end time of both the reference time period and the historical time period.

[0035] Step S108: Determine the dangerous grid areas in the target geographic area within the prediction time period based on the seismic probability of all grid areas within the reference time period.

[0036] After calculating the probability of earthquake occurrence in each grid area within the target geographic region during the reference time period, the dangerous grid areas within the target geographic region during the prediction time period can be determined based on the probability of earthquake occurrence in each grid area. The start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to that of the reference time period. Dangerous grid areas represent grid areas where strong aftershocks are predicted to occur.

[0037] To improve the accuracy of strong aftershock prediction, this embodiment of the invention preferably sets the duration of the prediction time period to be equal to the duration of the reference time period, that is, Figure 2 In this context, t2-t1 = t3-t2. That is, assuming we need to determine the grid area in the target geographic region where a strong aftershock is highly probable within two days after the end of a historical time period, then this step should calculate the probability of an earthquake occurring in the target grid area within two days before the end of the historical time period.

[0038] For the screening of dangerous grid areas, users can set settings according to actual needs. For example, they can set a seismic probability threshold to determine that grid areas with a seismic probability exceeding the seismic probability threshold are dangerous grid areas. Alternatively, they can calculate other parameters that can be used to reflect the possibility of aftershocks based on the seismic probability to determine all dangerous grid areas.

[0039] The strong aftershock prediction method provided in this invention, after acquiring earthquake data of a target geographical area over a historical time period, performs gridding processing on the target geographical area, calculates the probability of earthquake occurrence in the target grid area within a reference time period, and then determines the dangerous grid areas in the target geographical area within the prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period. This invention fills the gap in the prior art's inability to accurately predict the location of strong aftershocks, thus providing significant technical support for post-earthquake disaster relief efforts.

[0040] In an optional implementation, step S106 above, which calculates the probability of earthquake occurrence in the target grid area within a reference time period based on earthquake data from historical time periods, specifically includes the following steps:

[0041] Step S1061: Determine the complete magnitude lower limit of aftershocks based on earthquake data within the historical time period.

[0042] Specifically, the complete magnitude (Mc) can be used to represent the completeness of an earthquake catalog. It means that in a certain area, all earthquakes of magnitude greater than that have been completely recorded by seismic stations and included in the earthquake catalog. The lower the complete magnitude, the fewer missing microearthquakes, and the more complete the earthquake catalog. Given that earthquake data from multiple aftershocks have been recorded within a historical period, these may include aftershocks of lower magnitude. Therefore, in order to improve the accuracy of predicting strong aftershocks within the prediction period, this embodiment of the invention needs to determine the lower limit of the complete magnitude for aftershocks.

[0043] Optionally, the complete magnitude lower limit of aftershocks can be determined based on earthquake data within a historical time period, including: fitting the earthquake data within the historical time period using the GR relationship to obtain the complete magnitude lower limit of aftershocks. After fitting the complete magnitude lower limit using the GR relationship, users can also appropriately increase the value of the lower limit as a new complete magnitude lower limit according to actual needs. That is, when filtering earthquake data, the selected magnitude lower limit is higher than the theoretical fitting result.

[0044] Step S1062: Based on the seismic data and complete lower magnitude limit, construct the seismic time series of the target grid area.

[0045] After determining the complete lower limit of aftershock magnitude, the earthquake time series N for the target grid region can be constructed based on the known earthquake data and the grid division results of the target geographic region. i (t), where the earthquake time series includes the number of earthquakes with magnitudes greater than the lower limit of the complete magnitude scale within each unit of time. In other words, if the earthquake time series is organized into a coordinate system, then the time series N... i The horizontal axis of (t) represents time, and the vertical axis represents the number of target earthquakes occurring per unit time. Target earthquakes are earthquakes whose magnitude is greater than the lower limit of the complete aftershock magnitude.

[0046] Step S1063: Calculate the seismic intensity function of the target grid region within the first time period and the second time period based on the seismic time series of the target grid region, and obtain the first seismic intensity function and the second seismic intensity function of the target grid region.

[0047] The first time period begins at any point within the variable time period, and its start time is the same as the historical time period. Both the end time of the variable time period and the end time of the first time period are the start time of the reference time period. The second time period begins at the same time as the first time period and ends at the same time as the reference time period. (Reference) Figure 3 The historical time period is (t0, t2), the reference time period is (t1, t2), the change time period is (t0, t1), and the first time period is (t... b The second time period is (t1), and the second time period is (t2). b ,t2),t0≤t b If ≤t1, the predicted time period is (t2,t3).

[0048] In this embodiment of the invention, after determining the seismic time series of the target grid region, the formula is used. Calculate the seismic intensity function of target grid region i within a specified time period. The specified time period in the above formula is: (t b The earthquake intensity function represents the earthquake intensity from t (t). b The average number of earthquakes with a magnitude greater than Mc (the complete magnitude lower limit of aftershocks) occurring in target grid region i within the time interval up to time t. In other words, the earthquake intensity function of the target grid region in the first time interval, i.e., the first earthquake intensity function, is: The seismic intensity function of the target grid region in the second time period, i.e., the second seismic intensity function, is:

[0049] Step S1064: Standardize the first seismic intensity function of the target grid region to obtain the first standardized seismic intensity function of the target grid region in the first time period; and standardize the second seismic intensity function of the target grid region to obtain the second standardized seismic intensity function of the target grid region in the second time period.

[0050] After obtaining the first and second seismic intensity functions for the target grid region, in order to compare the seismic intensity functions from different time periods, these seismic intensity functions need to have the same statistical properties. Therefore, the seismic intensity functions are standardized to obtain the first and second standardized seismic intensity functions. This standardization process can also be understood as a normalization process.

[0051] Step S1065: Based on the first and second standardized seismic intensity functions, determine the probability of earthquake occurrence in the target grid area within the reference time period.

[0052] pass Figure 3 It can be seen that the reference time period (t1, t2) is the same as the second time period (t). b ,t2) and the first time period (t b The time difference between the second and first standardized seismic intensity functions of the target grid area can reflect the seismic intensity of the target grid area within the reference time period to a certain extent. Furthermore, since seismic intensity is proportional to the probability of earthquake occurrence, the probability of earthquake occurrence in the target grid area within the reference time period can be determined based on the first and second standardized seismic intensity functions.

[0053] In an optional implementation, step S1064 above, which standardizes the first seismic intensity function of the target grid region, specifically includes the following steps:

[0054] Step S10641: Calculate the seismic intensity function of each grid region in the first time period to obtain the first seismic intensity function of each grid region.

[0055] Step S10642: Calculate the average value and standard deviation of the seismic intensity function for all grid regions within the first time period based on the first seismic intensity function for all grid regions.

[0056] Step S10643: Standardize the first seismic intensity function of the target grid area based on the average value and standard deviation of the seismic intensity function to obtain the first standardized seismic intensity function.

[0057] Specifically, to standardize the first seismic intensity function of the target grid area, it is necessary to calculate the average and standard deviation of the seismic intensity function within the first time period. Therefore, the seismic intensity function of each grid area within the target geographic area should first be calculated within the first time period. The formula used is as follows: The value of i ranges from 1 to I, where I represents the total number of grid areas within the target geographic area.

[0058] Next, the average seismic intensity function of all grid regions within the first time period is calculated based on the first seismic intensity function of all grid regions. and the standard deviation of the earthquake intensity function σ(t) b The mean and standard deviation are the definitions in conventional mathematics, and the algorithm will not be elaborated here.

[0059] After determining the average value and standard deviation of the seismic intensity function for the target grid region, this embodiment of the invention utilizes the formula... Calculate the target grid region i over a specified time period (t) b The earthquake intensity function within (t) is standardized as a seismic intensity function. Therefore, after obtaining... and σ(t) b After t1), use the formula The target grid region i can then be calculated in the first time period (t). b The first standardized seismic intensity function within t1) The method for standardizing the second seismic intensity function of the target grid region can be referred to steps S10641 to S10643 above, and will not be repeated here. The target grid region i in the second time period (t) b The second standardized seismic intensity function within t2) is:

[0060] In an optional implementation, step S1065 above, which determines the probability of earthquake occurrence in the target grid area within the reference time period based on the first and second standardized seismic intensity functions, specifically includes the following steps:

[0061] Step S10651: Calculate the seismic intensity variation function of the target grid area within the reference time period based on the first and second standardized seismic intensity functions.

[0062] Step S10652: Traverse the time period of change and calculate the average change in seismic intensity of the target grid area within the reference time period based on the seismic intensity change function.

[0063] As mentioned above, the difference between the second-standardized seismic intensity function and the first-standardized seismic intensity function of the target grid region can characterize the seismic intensity of the target grid region within a reference time period to a certain extent. However, after the selection of the start times of the first and second time periods, noise may affect the accuracy of the seismic intensity reflected by the second-standardized seismic intensity function and the first-standardized seismic intensity function. Therefore, in order to reduce the influence of random fluctuations (noise) in seismic activity, this embodiment of the invention traverses the changing time periods. That is, different times are selected as the start times of the second and first time periods within the changing time periods, and the difference between the second-standardized seismic intensity function and the first-standardized seismic intensity function is calculated. The average value of the multiple calculation results is then taken as the average seismic intensity change of the target grid region within the reference time period.

[0064] Specifically, the seismic intensity variation function of the target grid area within the reference time period is as follows: The average change in seismic intensity of the target grid area during the reference time period is: During the calculation, t b The system slides from time t0 to time t1 with a step size of Δt. Users can set the sliding step size according to their actual needs.

[0065] Step S10653: Determine the probability of earthquake occurrence in the target grid area within the reference time period based on the average earthquake intensity change.

[0066] In this embodiment of the invention, determining the probability of an earthquake occurring in a target grid area within a reference time period based on the average change in seismic intensity includes: calculating the square of the average change in seismic intensity of the target grid area within the reference time period to obtain the probability of an earthquake occurring in the target grid area within the reference time period. That is, the probability of an earthquake occurring in target grid area i within the reference time period.

[0067] In an optional implementation, step S108 above, which determines the hazardous grid areas in the target geographic area within the prediction time period based on the seismic probability of all grid areas within the reference time period, specifically includes the following steps:

[0068] Step S1081: Calculate the average seismic probability of the target geographic area within the reference time period based on the seismic probability of all grid areas within the reference time period.

[0069] Specifically, embodiments of the present invention utilize formulas To calculate the seismic probability of target grid region i within the reference time period (t1, t2), we can similarly calculate the seismic probability of all grid regions in the target geographic region within the reference time period by varying the value of i (1, I). Finally, we can solve for the average seismic probability of all grid regions in the target geographic region within the reference time period.

[0070] Step S1082: Based on the average seismic probability and the seismic probability of the target grid area within the reference time period, determine the probability gain of the target grid area within the reference time period.

[0071] In this embodiment of the invention, the probability of an earthquake occurring in the target grid region within the reference time period is subtracted from the average probability of earthquakes occurring in all grid regions within the reference time period. This subtracted probability is used as the probability gain for a strong earthquake occurring in target grid region i within the reference time period. In other words, the probability gain for target grid region i within the reference time period (t1, t2) is:

[0072] Step S1083: Determine the dangerous grid areas based on the probability gain of all grid areas within the reference time period and a preset threshold.

[0073] For the target grid region i, if ΔP i (t0,t1,t2)>P thr P thr If a preset threshold is set, then target grid area i is determined to be highly likely to experience a strong aftershock within the predicted time period, i.e., it is a dangerous grid area; otherwise, if P... i (t0,t1,t2)≤P thr If the probability of a strong aftershock occurring in target grid area i is low during the prediction time period, it is considered a safe grid area. Based on the above judgment method, combined with the probability gain of all grid areas within the reference time period and the preset threshold, all dangerous grid areas in the target geographical area during the prediction time period can be determined.

[0074] The inventors verified the method provided in the embodiments of this invention. On October 7, 2014, a Ms6.6 earthquake occurred in Jinggu, Yunnan. Based on the spatial distribution of aftershocks four days after the main shock, the study area was determined to be longitude 100.25 to 100.65°E and latitude 23.2 to 23.6°N. The study area was divided into grids with a scale of 0.05°. Time series of earthquakes were constructed for each grid. Based on the method provided in the embodiments of this invention, the probability of earthquake occurrence for each grid was calculated (the probability of earthquake occurrence here is the logarithmic value of the probability of earthquake occurrence described above). A threshold of -0.5 was used; areas above this threshold were considered locations where strong aftershocks were likely to occur in the next three days. Figure 4 The black squares in the image indicate that the rest of the area is a safe zone. The results show that the strong aftershocks of the MS6.6 earthquake in Jinggu, Yunnan on October 7, 2014 (the ML5.1 earthquake on October 11, 2014) were... Figure 4 The central pentagram occurs in the high-probability predicted region.

[0075] Example 2

[0076] This invention also provides a strong aftershock prediction device, which is mainly used to execute the strong aftershock prediction method provided in Embodiment 1 above. The following is a detailed description of the strong aftershock prediction device provided in this invention.

[0077] Figure 5 This is a functional block diagram of a strong aftershock prediction device provided in an embodiment of the present invention, such as... Figure 5 As shown, the device mainly includes: an acquisition module 10, a processing module 20, a calculation module 30, and a determination module 40, wherein:

[0078] The acquisition module 10 is used to acquire earthquake data of the target geographical area within a historical time period; the earthquake data includes: earthquake information of strong earthquakes and earthquake information of aftershocks.

[0079] The processing module 20 is used to perform gridding on the target geographic area to obtain multiple grid areas.

[0080] The calculation module 30 is used to calculate the probability of earthquake occurrence in a target grid area within a reference time period based on earthquake data within a historical time period; wherein, the target grid area represents any area among multiple grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period.

[0081] The determination module 40 is used to determine the dangerous grid areas in the target geographic area within the prediction time period based on the earthquake occurrence probability of all grid areas within the reference time period; wherein, the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to that of the reference time period; the dangerous grid areas represent the grid areas where strong aftershocks are predicted to occur.

[0082] The method executed by the strong aftershock prediction device provided in this invention, after acquiring earthquake data of the target geographical area within a historical time period, involves gridding the target geographical area, calculating the probability of earthquake occurrence in the target grid area within a reference time period, and then determining the dangerous grid areas in the target geographical area within the prediction time period based on the earthquake occurrence probabilities of all grid areas within the reference time period. This invention fills the gap in the prior art's inability to accurately predict the location of strong aftershocks, thereby providing significant technical support for post-earthquake disaster relief work.

[0083] Optionally, the computing module 30 includes:

[0084] The first determining unit is used to determine the complete lower limit of the magnitude of aftershocks based on earthquake data within a historical time period.

[0085] The building unit is used to construct the earthquake time series of the target grid area based on earthquake data and the complete lower magnitude limit; wherein the earthquake time series includes the number of earthquakes with a magnitude greater than the complete lower magnitude limit in each unit time.

[0086] The calculation unit is used to calculate the seismic intensity function of the target grid area within a first time period and a second time period based on the seismic time series of the target grid area, thereby obtaining the first seismic intensity function and the second seismic intensity function of the target grid area; wherein, the start time of the first time period is any moment in the changing time period, the starting time of the changing time period is the same as the start time of the historical time period, and the end time of the changing time period and the end time of the first time period are both the start time of the reference time period; the start time of the second time period is the same as the first time period, and the end time of the second time period is the same as the reference time period.

[0087] The standardization processing unit is used to standardize the first seismic intensity function of the target grid region to obtain the first standardized seismic intensity function of the target grid region in the first time period, and to standardize the second seismic intensity function of the target grid region to obtain the second standardized seismic intensity function of the target grid region in the second time period.

[0088] The second determining unit is used to determine the probability of earthquake occurrence in the target grid area within the reference time period based on the first and second standardized seismic intensity functions.

[0089] Optionally, the standardized processing unit is specifically used for:

[0090] Calculate the seismic intensity function for each grid region within the first time period to obtain the first seismic intensity function for each grid region.

[0091] Calculate the average and standard deviation of the seismic intensity function for all grid regions within the first time period based on the first seismic intensity function for all grid regions.

[0092] The first earthquake intensity function of the target grid region is standardized based on the average value and standard deviation of the earthquake intensity function to obtain the first standardized earthquake intensity function.

[0093] Optionally, the second determining unit includes: determining the probability of earthquake occurrence in the target grid area within a reference time period based on the first and second standardized seismic intensity functions, including:

[0094] The first calculation sub-unit is used to calculate the seismic intensity variation function of the target grid area within the reference time period based on the first and second standardized seismic intensity functions.

[0095] The second calculation sub-unit is used to traverse the time period and calculate the average change in seismic intensity of the target grid area within the reference time period based on the seismic intensity change function.

[0096] Define sub-cells to determine the probability of earthquake occurrence in the target grid area within a reference time period based on the average seismic intensity variation.

[0097] Module 40 is specifically used for:

[0098] The average earthquake probability of the target geographic area during the reference time period is calculated based on the earthquake probability of all grid areas during the reference time period.

[0099] Based on the average earthquake probability and the earthquake probability of the target grid area within the reference time period, the probability gain of the target grid area within the reference time period is determined.

[0100] Dangerous grid areas are determined based on the probability gain of all grid areas within a reference time period and a preset threshold.

[0101] Optionally, the first determining unit is specifically used to: obtain a complete lower limit of the magnitude of aftershocks by fitting earthquake data within a historical time period through the GR relationship.

[0102] Optionally, the sub-unit is specifically used to: calculate the square of the average seismic intensity change of the target grid area within the reference time period, and obtain the seismic probability of the target grid area within the reference time period.

[0103] Example 3

[0104] See Figure 6 This invention provides an electronic device, which includes a processor 60, a memory 61, a bus 62, and a communication interface 63. The processor 60, the communication interface 63, and the memory 61 are connected via the bus 62. The processor 60 is used to execute executable modules, such as computer programs, stored in the memory 61.

[0105] The memory 61 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 63 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0106] Bus 62 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0107] The memory 61 is used to store programs. After receiving an execution instruction, the processor 60 executes the program. The method executed by the apparatus defined by the process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 60 or implemented by the processor 60.

[0108] Processor 60 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 60 or by instructions in software form. Processor 60 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 61. Processor 60 reads the information in memory 61 and, in conjunction with its hardware, completes the steps of the above method.

[0109] The computer program product of the strong aftershock prediction method, device and electronic device provided in the embodiments of the present invention includes a computer-readable storage medium storing non-volatile program code executable by a processor. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0110] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0111] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0112] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0113] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0114] Furthermore, terms such as "horizontal," "vertical," and "sag" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0115] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting strong aftershocks, characterized in that, include: Obtain earthquake data for a target geographic area within a historical time period; wherein, the earthquake data includes: earthquake information of strong earthquakes and earthquake information of aftershocks; The target geographic area is gridded to obtain multiple grid areas; The probability of an earthquake occurring in a target grid area within a reference time period is calculated based on earthquake data within the historical time period; wherein, the target grid area represents any area among the plurality of grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period; Dangerous grid areas in the target geographic region are determined based on the earthquake probability of all grid areas within the reference time period; wherein, the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to that of the reference time period; the dangerous grid areas represent grid areas where strong aftershocks are predicted to occur. The calculation of the earthquake probability of the target grid area within the reference time period based on the earthquake data within the historical time period includes: The complete lower limit of the magnitude of aftershocks is determined based on earthquake data within the aforementioned historical time period; Based on the earthquake data and the complete lower magnitude limit, an earthquake time series of the target grid area is constructed; wherein, the earthquake time series includes: the number of earthquakes with a magnitude greater than the complete lower magnitude limit in each unit time; Based on the earthquake time series of the target grid area, the earthquake intensity function of the target grid area within a first time period and a second time period is calculated to obtain the first earthquake intensity function and the second earthquake intensity function of the target grid area; wherein, the start time of the first time period is any moment in the changing time period, the starting time of the changing time period is the same as the start time of the historical time period, and the end time of the changing time period and the end time of the first time period are both the start time of the reference time period; the start time of the second time period is the same as the start time of the first time period, and the end time of the second time period is the same as the end time of the reference time period; The first seismic intensity function of the target grid region is standardized to obtain the first standardized seismic intensity function of the target grid region in the first time period; and the second seismic intensity function of the target grid region is standardized to obtain the second standardized seismic intensity function of the target grid region in the second time period. Based on the first standardized seismic intensity function and the second standardized seismic intensity function, the probability of earthquake occurrence in the target grid area within the reference time period is determined.

2. The method for predicting strong aftershocks according to claim 1, characterized in that, The first seismic intensity function of the target grid region is standardized, including: Calculate the seismic intensity function of each grid region within the first time period to obtain the first seismic intensity function of each grid region; The average value and standard deviation of the seismic intensity function of all grid regions during the first time period are calculated based on the first seismic intensity function of all grid regions. The first earthquake intensity function of the target grid region is standardized based on the average value and standard deviation of the earthquake intensity function to obtain the first standardized earthquake intensity function.

3. The method for predicting strong aftershocks according to claim 1, characterized in that, Based on the first standardized seismic intensity function and the second standardized seismic intensity function, the probability of earthquake occurrence in the target grid area within the reference time period is determined, including: The seismic intensity variation function of the target grid region during the reference time period is calculated based on the first standardized seismic intensity function and the second standardized seismic intensity function. By iterating through the time periods, the average change in seismic intensity of the target grid area during the reference time period is calculated based on the seismic intensity change function. The probability of an earthquake occurring in the target grid area within the reference time period is determined based on the average change in earthquake intensity.

4. The method for predicting strong aftershocks according to claim 1, characterized in that, Based on the seismic occurrence probability of all grid areas within the reference time period, dangerous grid areas within the target geographic area are determined for the prediction time period, including: Calculate the average earthquake probability of the target geographic area within the reference time period based on the earthquake probability of all grid areas within the reference time period; Based on the average vibration probability and the vibration probability of the target grid area during the reference time period, the probability gain of the target grid area during the reference time period is determined. The dangerous grid area is determined based on the probability gain of all grid areas within the reference time period and a preset threshold.

5. The method for predicting strong aftershocks according to claim 1, characterized in that, Determining the complete magnitude lower limit of aftershocks based on earthquake data within the aforementioned historical time period includes: By fitting the earthquake data within the historical time period using the GR relationship, the complete lower limit of the magnitude of the aftershocks is obtained.

6. The method for predicting strong aftershocks according to claim 3, characterized in that, Determining the probability of earthquake occurrence in the target grid area within the reference time period based on the average seismic intensity change includes: The square of the average change in seismic intensity in the target grid area during the reference time period is calculated to obtain the probability of earthquake occurrence in the target grid area during the reference time period.

7. A strong aftershock prediction device, characterized in that, include: The acquisition module is used to acquire earthquake data of the target geographical area within a historical time period; wherein, the earthquake data includes: earthquake information of strong earthquakes and earthquake information of aftershocks; The processing module is used to perform gridding processing on the target geographic area to obtain multiple grid areas; The calculation module is used to calculate the probability of earthquake occurrence in a target grid area within a reference time period based on earthquake data within the historical time period; wherein, the target grid area represents any area among the plurality of grid areas; the reference time period is within the time range of the historical time period, and the end time of the reference time period is the same as the end time of the historical time period; The determination module is used to determine the dangerous grid areas in the target geographical area within the prediction time period based on the earthquake occurrence probability of all grid areas within the reference time period; wherein, the start time of the prediction time period is the end time of the reference time period, and the duration of the prediction time period is equal to that of the reference time period; the dangerous grid areas represent the grid areas predicted to experience strong aftershocks. The calculation module includes: The first determining unit is used to determine the complete lower limit of the magnitude of aftershocks based on the earthquake data within the historical time period. A construction unit is used to construct an earthquake time series of the target grid area based on the earthquake data and the complete lower magnitude limit; wherein, the earthquake time series includes: the number of earthquakes with a magnitude greater than the complete lower magnitude limit in each unit time; The calculation unit is used to calculate the seismic intensity function of the target grid area within a first time period and a second time period based on the seismic time series of the target grid area, thereby obtaining the first seismic intensity function and the second seismic intensity function of the target grid area; wherein, the start time of the first time period is any moment in the changing time period, the starting time of the changing time period is the same as the start time of the historical time period, and the end time of the changing time period and the end time of the first time period are both the start time of the reference time period; the start time of the second time period is the same as the start time of the first time period, and the end time of the second time period is the same as the end time of the reference time period; The standardization processing unit is used to standardize the first seismic intensity function of the target grid region to obtain the first standardized seismic intensity function of the target grid region in the first time period, and to standardize the second seismic intensity function of the target grid region to obtain the second standardized seismic intensity function of the target grid region in the second time period. The second determining unit is used to determine the probability of earthquake occurrence in the target grid area within the reference time period based on the first standardized seismic intensity function and the second standardized seismic intensity function.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the strong aftershock prediction method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the strong aftershock prediction method according to any one of claims 1 to 6.

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