A method and system for calculating sea area seismic activity parameters

Abstract

The present application provides a method and system for calculating marine seismic activity parameters, which are applicable to the technical field of data processing. The method includes: obtaining seismic event information and geological structure information; generating seismic statistical region information according to the seismic event information, geological structure information, preset neighborhood radius information, and preset number of regional position points information; calculating seismic activity parameters according to the seismic statistical region information, preset weight coefficient matrix, preset bias matrix, preset spatial mapping function, and preset mapping iteration number threshold. By analyzing and calculating the seismic event information and geological structure information, the present application divides seismic statistical regions, and then maps the data of multiple seismic statistical regions into a high-dimensional space for in-depth feature extraction and prediction calculation, so as to further calculate the seismic activity parameters through the prediction calculation results, ensuring the accuracy and effectiveness of calculating the seismic activity parameters.

Description

Technical Field

[0001] This application belongs to the technical field of data processing, and particularly relates to a method and system for calculating sea area seismic activity parameters. Background Art

[0002] China has a vast sea area, where both intraplate earthquakes and plate-boundary earthquakes exist, and seismic activities are frequent. With the development of the national economic construction, the types and quantities of construction projects in the sea area and coastal areas are increasing. Once an earthquake occurs, it will cause huge losses to the coastal areas, sea areas, and construction project areas in the coastal areas. Therefore, it is necessary to conduct sea area seismic analysis work and make preparations and protection before the occurrence of sea area seismic disasters. In the sea area seismic analysis work, the calculation of seismic activity parameters is crucial. The calculated activity parameters can predict indicators such as the risk of seismic activities, thereby providing reliable data support for prevention and post-disaster reconstruction work.

[0003] In the prior art, it is usually dependent on experts to manually judge the seismic statistical area, and then use the analytic hierarchy process or the least squares method to fit the data of the land seismic statistical area, so as to use the obtained fitting result as the seismic activity parameter for subsequent seismic activity analysis work.

[0004] However, in the prior art, large errors are easily generated when processing high-dimensional and complex seismic data, which cannot ensure the accuracy and reliability of seismic activity analysis calculations. Moreover, the existing seismic zoning maps only cover land areas, lacking seismic zoning for sea areas and models suitable for sea area seismic activity analysis. The seismic activity parameters of sea areas cannot be calculated through the existing models, so the seismic activity situation of sea areas cannot be analyzed. Therefore, when a seismic disaster occurs in a sea area, the timeliness of pre-disaster prevention and post-disaster reconstruction cannot be guaranteed, resulting in huge economic losses in the coastal areas. Summary of the Invention

[0005] In view of this, the embodiments of this application provide a method and system for calculating sea area seismic activity parameters, aiming to solve the problems in the prior art that there are large errors in the calculation of sea area seismic activity parameters, the accuracy and reliability of the calculation results are low, and thus they cannot be used for effective analysis of sea area seismic activities.

[0006] The first aspect of the embodiments of this application provides a method for calculating sea area seismic activity parameters, including:

[0007] Obtain seismic event information and geological structure information;

[0008] Generate seismic statistical area information according to the seismic event information, geological structure information, preset neighborhood radius information, and preset number of regional position points information;

[0009] Calculate seismic activity parameters according to the seismic statistical region information, a preset weight coefficient matrix, a preset bias matrix, a preset spatial mapping function, and a preset mapping iteration count threshold.

[0010] The second aspect of the embodiments of the present application provides a system for calculating seismic activity parameters in a sea area, including:

[0011] An information acquisition module, configured to acquire seismic event information and geological structure information;

[0012] A seismic statistical region information generation module, configured to generate seismic statistical region information according to the seismic event information, geological structure information, a preset neighborhood radius information, and a preset number of regional position points information; and

[0013] A seismic activity parameter calculation module for calculating seismic activity parameters according to the seismic statistical region information, a preset weight coefficient matrix, a preset bias matrix, a preset spatial mapping function, and a preset mapping iteration count threshold.

[0014] The third aspect of the embodiments of the present application provides a terminal device, where the terminal device includes a memory and a processor, and a computer program that can run on the processor is stored on the memory. When the processor executes the computer program, the steps of the method for calculating seismic activity parameters in the sea area as described in the first aspect above are implemented.

[0015] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium, including: storing a computer program, and when the computer program is executed by a processor, the steps of the method for calculating seismic activity parameters in the sea area as described in the first aspect above are implemented.

[0016] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: By analyzing and calculating the complex and huge seismic event information and geological structure information, dividing the seismic statistical region through data feature analysis of multiple pieces of information to reduce data complexity, and then mapping the data of multiple seismic statistical regions into a high-dimensional space for in-depth feature extraction and prediction calculation, accurately capturing the complex relationships of seismic influencing factors between regions, further calculating the seismic activity parameters through the prediction calculation results, enabling the calculated seismic activity parameters to adapt to different seismic activity patterns, ensuring the accuracy and effectiveness of calculating seismic activity parameters, thereby improving the accuracy and reliability of analyzing and calculating the seismic activity in the sea area, and providing scientific and effective data support for the planning and construction of marine facilities and coastal cities. Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the first embodiment of the present application;

[0019] Figure 2 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the second embodiment of the present application;

[0020] Figure 3 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the third embodiment of the present application;

[0021] Figure 4 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the fourth embodiment of the present application;

[0022] Figure 5 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the fifth embodiment of the present application;

[0023] Figure 6 It is a schematic flowchart of the implementation of the method for calculating the marine seismic activity parameters provided in the sixth embodiment of the present application;

[0024] Figure 7 It is a schematic structural diagram of the system for calculating the marine seismic activity parameters provided in the embodiments of the present application;

[0025] Figure 8 It is a schematic diagram of the terminal device provided in the embodiments of the present application. Detailed implementation manners

[0026] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, systems, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0027] To illustrate the technical solutions described in the present application, the following will be described through specific embodiments.

[0028] Figure 1The following is a flowchart showing the implementation of the method for calculating marine seismic activity parameters provided in the first embodiment of the present application:

[0029] Step S101: Obtain seismic event information and geological structure information.

[0030] In this embodiment, the seismic event information may be information such as the epicenter location, magnitude, and occurrence time of an earthquake, which can reflect the spatial distribution, intensity, and time law of the earthquake occurrence. It can be obtained through seismic data institutions such as the Global Seismic Network Center and the China Earthquake Networks Center; the geological structure information may include information such as the location, length, strike, activity nature, and activity rate of faults, which can be obtained through on-site survey data of geological survey departments or relevant research literature, or can be determined by geological staff using methods such as geological mapping or geophysical exploration and then input into a computer to complete the acquisition.

[0031] Step S102: Generate seismic statistical region information according to the seismic event information, geological structure information, preset neighborhood radius information, and preset number of regional location points information.

[0032] In this embodiment, the preset neighborhood radius information and the preset number of regional location points information can be set manually and can be calculation parameters when dividing and processing seismic statistical regions according to seismic event information and geological structure information. The range of each seismic statistical region can be determined through the neighborhood radius information and the number of regional location points information, or each seismic statistical region can be obtained through clustering calculation. The seismic statistical region can be used to further calculate and divide potential source regions.

[0033] Step S103: Calculate seismic activity parameters according to the seismic statistical region information, preset weight coefficient matrix, preset bias matrix, preset spatial mapping function, and preset mapping iteration number threshold.

[0034] In this embodiment, the preset weight coefficient matrix, the preset bias matrix, the preset spatial mapping function, and the preset mapping iteration number threshold can be set manually. Among them, the preset spatial mapping function can be designed based on the exponential function or the hyperbolic tangent function. First, each seismic statistical region can be weighted and summed through the weight coefficient matrix, and then the result of the weighted sum is summed with the bias matrix. Then, the sum result is used as the independent variable of the spatial mapping function, and the calculated function value is used as an intermediate variable. Then, the intermediate variable is recalculated through the weight coefficient matrix and the bias matrix, and the calculation result is used as the independent variable of the spatial mapping function for transformation calculation, so as to achieve iterative calculation. The number of iterations can be determined by the mapping iteration number threshold. The seismic activity parameters can be the magnitude-frequency characterization parameter and the earthquake occurrence rate characterization parameter. Among them, the magnitude-frequency characterization parameter of the seismic event can be the magnitude-frequency characterization parameter in the Gutenberg-Richter law, which is used to describe the logarithmic-linear relationship between the number of earthquakes with a specific magnitude and the magnitude. The earthquake occurrence rate characterization parameter can be used to represent the annual occurrence rate of earthquakes with a magnitude greater than or equal to a specific earthquake magnitude.

[0035] The method for calculating the seismic activity parameters of the sea area provided by the embodiment of the present application analyzes and calculates the complex and huge seismic event information and geological structure information, divides the seismic statistical regions by analyzing the data characteristics of multiple pieces of information, reduces the data complexity, and then maps the data of multiple seismic statistical regions into a high-dimensional space for deep feature extraction and prediction calculation, accurately captures the complex relationships of seismic influencing factors between regions, further calculates the seismic activity parameters through the prediction calculation results, enables the calculated seismic activity parameters to adapt to different seismic activity patterns, ensures the accuracy and effectiveness of calculating the seismic activity parameters, and thus improves the accuracy and reliability of analyzing and calculating the seismic activity of the sea area, providing scientific and effective data support for the planning and construction of marine facilities and coastal cities.

[0036] Figure 2 The flowchart of the method for calculating the seismic activity parameters of the sea area provided by the second embodiment of the present application is shown. The difference from the first embodiment above is that:

[0037] The seismic event information includes magnitude information and epicenter location information;

[0038] The step S102 specifically includes:

[0039] Step S201, perform normalization processing on the magnitude information to obtain magnitude characterization information.

[0040] In this embodiment, it can be understood that in seismic research work, the seismic magnitude information collected usually has different magnitude measurement standards and magnitude differences, and needs to be normalized to unify the dimensions of various magnitude information, so that magnitude data from different sources and of different types are comparable, ensuring the effectiveness of subsequent calculations. The normalization method can be linear normalization or Z-score normalization. The result after normalization is the magnitude characterization information.

[0041] Step S202: Calculate the logical space distance of each of the magnitude characterization information to obtain the magnitude logical distance.

[0042] In this embodiment, the logical space distance can be the Euclidean distance. By calculating the Euclidean distance between each magnitude characterization information, the magnitude logical distance is obtained.

[0043] Step S203: Calculate the logical space distance of each of the epicenter location information to obtain the location logical distance.

[0044] In this embodiment, the logical space distance can be the Euclidean distance. By calculating the Euclidean distance between each epicenter location information, the location logical distance is obtained.

[0045] Step S204: Calculate the logical space distance of each of the geological structure information to obtain the geological structure logical distance.

[0046] In this embodiment, the logical space distance can be the Euclidean distance. By calculating the Euclidean distance between each geological structure information, the geological structure logical distance is obtained.

[0047] Step S205: Calculate the comprehensive earthquake information distance according to the magnitude logical distance, location logical distance, geological structure logical distance and a preset weight coefficient.

[0048] In this embodiment, the preset weight coefficient can be set manually. The weighted sum of the magnitude logical distance, location logical distance, and geological structure logical distance can be calculated by the preset weight coefficient, and the calculation result is the comprehensive earthquake information distance.

[0049] Step S206: Generate a plurality of earthquake characterization information points according to the magnitude characterization information, epicenter location information, geological structure information, and comprehensive earthquake information distance.

[0050] In this embodiment, the magnitude characterization information, epicenter location information, geological structure information, and the comprehensive distance of seismic information can be used as the elements of a matrix. Multiple seismic characterization information matrices are generated through multiple sets of magnitude characterization information, epicenter location information, geological structure information, and the comprehensive distance of seismic information, and these multiple matrices are stored in a single logical storage space as multiple seismic characterization information points. One seismic characterization information point represents a matrix generated by the magnitude characterization information, epicenter location information, geological structure information, and the comprehensive distance of seismic information.

[0051] Step S207: Determine whether the comprehensive distance of the seismic information is less than or equal to the preset neighborhood radius information; if so, generate the neighborhood set information of each seismic characterization information point according to the seismic characterization information point corresponding to the comprehensive distance of the seismic information; if not, do not process the seismic characterization information point corresponding to the comprehensive distance of the seismic information and do not generate the neighborhood set information.

[0052] In this embodiment, one of the seismic characterization information points can be randomly selected as the point of the main domain first. When the comprehensive distance of the seismic information is less than or equal to the preset neighborhood radius information, it indicates that the adjacent distance between the two seismic characterization information points corresponding to the comprehensive distance of the seismic information is relatively close. If one of the seismic characterization information points is used as the point of the main domain, then the other seismic characterization information point is used as the neighborhood point. Thus, all the points whose comprehensive distance of the seismic information from the point of the main domain is less than or equal to the preset neighborhood radius information are counted to obtain all the neighborhood points, and then the neighborhood set information of each seismic characterization information point is generated according to all the neighborhood points. When the comprehensive distance of the seismic information is greater than the preset neighborhood radius information, it indicates that the adjacent distance between the two seismic characterization information points corresponding to the comprehensive distance of the seismic information is relatively far, so this seismic characterization information point is not used as the neighborhood point, and thus the seismic characterization information point corresponding to the comprehensive distance of the seismic information is not processed and the neighborhood set information is not generated.

[0053] Step S208: Generate seismic statistical region information according to the neighborhood set information and the preset number information of regional location points.

[0054] In this embodiment, the preset number information of regional location points can be set manually and is used to restrict the range of each seismic statistical region information. Each seismic statistical region information can be divided according to the number information of regional location points by counting the seismic characterization information points in each neighborhood set information.

[0055] The method for calculating marine seismic activity parameters provided by the embodiments of the present application calculates a comprehensive logical distance by integrating seismic magnitude information and geological structure information, which is used to more comprehensively reflect the similarity and relevance between each seismic point, helps to effectively extract the characteristics between each seismic data in the subsequent calculation process, and quickly locates the areas with frequent seismic activities by statistically analyzing the number of neighborhood points, thereby increasing the accuracy and effectiveness of the division of the seismic statistical area, improving the accuracy and robustness of the calculation of marine seismic activity parameters, and providing more comprehensive information for the analysis of marine seismic activities.

[0056] Figure 3 The flowchart of the implementation of the method for calculating marine seismic activity parameters provided by the third embodiment of the present application is shown. The difference from the second embodiment above is that the step S208 specifically includes:

[0057] Step S301: Count the number of information points in each of the neighborhood set information to obtain the neighborhood set point quantity information.

[0058] In this embodiment, count the number of seismic characterization information points in each neighborhood set information, and this number is the neighborhood set point quantity information.

[0059] Step S302: Determine whether the neighborhood set point quantity information is greater than or equal to a preset regional location point quantity information; if so, go to step S303; if not, go to step S304.

[0060] In this embodiment, the preset regional location point quantity information can be set artificially. When the neighborhood set point quantity information is greater than or equal to the preset regional location point quantity information, it indicates that the seismic characterization information points in the neighborhood set corresponding to the points in this main domain are strongly correlated with each other, and the points in this main domain have frequent seismic activities. It is necessary to use the seismic characterization information points in this neighborhood set as core points, and multiple core points form core point information. When the neighborhood set point quantity information is less than the preset regional location point quantity information, it indicates that the seismic points corresponding to this neighborhood set are weakly correlated with each other. When the neighborhood set point quantity information is equal to zero, it means that the points in the main domain corresponding to this neighborhood set have little reference significance for seismic activity analysis, and it is necessary to discard the points in this main domain; when the neighborhood set point quantity information is not equal to zero, use the seismic characterization information points in this neighborhood set as boundary points, and multiple boundary points form boundary point information.

[0061] Step S303: Use the seismic characterization information points corresponding to the neighborhood set point quantity information as core point information.

[0062] In this embodiment, when the number information of neighborhood set points is greater than or equal to the preset number information of regional position points, it indicates that the seismic characterization information points in the neighborhood set corresponding to the points in the main domain are strongly correlated with each other, and the seismic activity of the points in the main domain is frequent. It is necessary to use the seismic characterization information points in the neighborhood set as core points, and multiple core points constitute core point information.

[0063] Step S304, determine whether the number information of neighborhood set points is not zero; if so, proceed to step S305; if not, discard the seismic characterization information points corresponding to the neighborhood set number information.

[0064] In this embodiment, when the number information of neighborhood set points is less than the preset number information of regional position points, it indicates that the correlation between the seismic points corresponding to the neighborhood set is weak. When the number information of neighborhood set points is equal to zero, it means that the points in the main domain corresponding to the neighborhood set have little reference significance for seismic activity analysis, and it is necessary to discard the points in the main domain.

[0065] Step S305, use the seismic characterization information points corresponding to the number information of neighborhood set points as boundary point information.

[0066] In this embodiment, when the number information of neighborhood set points is not zero, the seismic characterization information points in the neighborhood set are used as boundary points, and multiple boundary points form boundary point information.

[0067] Step S306, generate a seismic statistical region information characterization set according to the core point information, boundary point information, and neighborhood set information.

[0068] In this embodiment, it can be started from any core point in the core point information, determine the neighborhood set of the core point, and then use a recursive method to spread the core points through the neighborhood set until all core points are assigned to the neighborhood set and cannot be spread anymore. The finally generated neighborhood set information is used as each seismic statistical region information characterization set.

[0069] Step S307, generate seismic statistical region information according to the seismic statistical region information characterization set.

[0070] In this embodiment, it can be understood that the seismic statistical region information characterization set contains multiple matrix elements. Extract the values of the matrix elements, and regenerate multiple matrices according to the extracted values. The multiple matrices are the seismic statistical region information, and the seismic statistical region information includes the seismic event information and geological structure information of each seismic statistical region.

[0071] The method for calculating sea area seismic activity parameters provided by the embodiments of the present application divides sets based on the density of seismic data points, can adaptively identify seismic statistical regions of different shapes and sizes, and effectively filters out redundant data such as accidentally occurring small earthquakes or data measurement errors by determining core point information and boundary point information, thereby increasing the accuracy and reliability of the division of seismic statistical regions and providing effective data support for the calculation of seismic activity parameters.

[0072] Figure 4 The implementation flowchart of the method for calculating sea area seismic activity parameters provided by the fourth embodiment of the present application is shown. The difference from the first embodiment above is that the step S103 specifically includes:

[0073] Step S401, generating a seismic statistical parameter matrix according to the seismic statistical region information.

[0074] In this embodiment, it may be to extract each value in multiple seismic statistical region information to generate one-dimensional data, set the dimension of the matrix, and convert the one-dimensional array into multiple seismic statistical parameter matrices according to the dimension of the matrix.

[0075] Step S402, calculating a seismic activity characterization variable matrix according to the seismic statistical parameter matrix, a preset weight coefficient matrix, and a preset bias matrix.

[0076] In this embodiment, it may be to first perform weighted summation on the seismic statistical parameter matrix through the weight coefficient matrix, and then add the result of the weighted summation to the bias matrix, and the addition result is used as the seismic activity characterization variable matrix.

[0077] Step S403, using the seismic activity characterization variable matrix as the independent variable of a preset space mapping function to generate a seismic activity characterization space mapping variable matrix.

[0078] In this embodiment, using the seismic activity characterization variable matrix as the independent variable of a preset space mapping function, the calculated function value is used as the seismic activity characterization space mapping variable matrix.

[0079] Step S404, calculating seismic activity parameters according to the seismic activity characterization space mapping variable matrix and a preset mapping iteration number threshold.

[0080] In this embodiment, it may be to calculate the seismic activity characterization space mapping variable matrix through the weight coefficient matrix and the bias matrix again, and then use the calculation result as the independent variable of the space mapping function to calculate the function value, thereby realizing one iteration. The number of iterations can be determined by the mapping iteration number threshold, and the result obtained after multiple iterative calculations is output as the seismic activity parameter.

[0081] The method for calculating the seismic activity parameters provided by the embodiment of the present application performs a non-linear spatial mapping transformation on the seismic statistical region data through a preset spatial mapping function, and performs an offset transformation on the seismic statistical region data in the non-linear space through a preset bias function, fully extracting and transforming the non-linear features in the seismic statistical region, increasing the spatial distance between each non-linear feature, so that various complex features in the seismic statistical region data are extracted and analyzed, avoiding the loss of effective feature information, and improving the accuracy of calculating the seismic activity parameters of the sea area.

[0082] Figure 5 The flowchart of implementing the method for calculating the seismic activity parameters provided by the fifth embodiment of the present application is shown. The difference from the fourth embodiment above is that the step S404 specifically includes:

[0083] Step S501, count the generation times of the seismic activity characterization spatial mapping variable matrix to obtain the mapping iteration times.

[0084] In this embodiment, every time the seismic activity characterization spatial mapping variable matrix is generated, it means that the spatial mapping transformation has been performed once. Therefore, the mapping iteration times can be calculated by counting the generation times of the seismic activity characterization spatial mapping variable matrix to determine whether to terminate the calculation of the spatial mapping transformation.

[0085] Step S502, determine whether the mapping iteration times are less than the preset mapping iteration times threshold; if so, enter step S503; if not, enter step S504.

[0086] In this embodiment, the preset mapping iteration times threshold can be set artificially. When the mapping iteration times are less than the preset mapping iteration times threshold, it means that the feature extraction and analysis of the seismic statistical region data are still not sufficient, and iterative calculation needs to be continued to ensure that the seismic statistical region data is deeply feature-extracted and analyzed; when the mapping iteration times are greater than or equal to the preset mapping iteration times threshold, it means that the feature extraction and analysis of the seismic statistical region data are sufficient enough, and there is no need to continue the iterative calculation. The seismic statistical region data has been deeply feature-extracted and analyzed and can be used to output the calculation results.

[0087] Step S503, take the seismic activity characterization spatial mapping variable matrix as the seismic statistical parameter matrix and return it to step S402.

[0088] In this embodiment, when the mapping iteration times are less than the preset mapping iteration times threshold, it means that the feature extraction and analysis of the seismic statistical region data are still not sufficient, and iterative calculation needs to be continued to ensure that the seismic statistical region data is deeply feature-extracted and analyzed.

[0089] Step S504: Extract the magnitude characterization information and the earthquake occurrence frequency information from the earthquake activity characterization spatial mapping variable matrix.

[0090] In this embodiment, when the mapping iteration count is greater than or equal to the preset mapping iteration count threshold, it indicates that the feature extraction and analysis of the earthquake statistical region data are sufficient, and there is no need to continue the iterative calculation. The earthquake statistical region data has undergone in-depth feature extraction and analysis and can be used to output the calculation results. At this time, it is necessary to extract the magnitude characterization information and the earthquake occurrence frequency information from the earthquake activity characterization spatial mapping variable matrix for subsequent calculation of earthquake activity parameters.

[0091] Step S505: Calculate the earthquake activity parameters based on the magnitude characterization information and the earthquake occurrence frequency information.

[0092] In this embodiment, the earthquake activity parameters can be the magnitude-frequency characterization parameters and the earthquake occurrence rate, which are used to quantitatively describe the earthquake activity characteristics. Based on the Gutenberg-Richter law, the magnitude characterization information can be fitted by the analytic hierarchy process or the least squares method, and the fitting result is output as the magnitude-frequency characterization parameter. Multiple magnitudes can be divided into different magnitude intervals, and then the earthquake occurrence frequencies in each magnitude interval are statistically counted, and the earthquake occurrence rates in each magnitude interval are calculated.

[0093] The method for calculating the earthquake activity parameters in the embodiments of the present application fully extracts and analyzes the data features by mapping the earthquake statistical region information into a non-linear space, fully captures the complex non-linear relationships among multiple factors such as magnitude, time, and space in the earthquake statistical region information, so as to more accurately fit the correlations between the magnitude-frequency and the earthquake occurrence rate and various influencing factors, adapt to the geological condition differences and earthquake activity characteristic differences of different earthquake statistical regions, make the calculation results more in line with the actual earthquake activity laws, and ensure the accuracy and comprehensiveness of the calculation of the earthquake activity parameters in the sea area.

[0094] Figure 6 The flowchart showing the implementation of the method for calculating the earthquake activity parameters in the sixth embodiment of the present application is different from that of the first embodiment above in that:

[0095] The earthquake activity parameters include the magnitude-frequency characterization parameters and the earthquake occurrence rate characterization parameters;

[0096] After the step S103, it further includes:

[0097] Step S601: Obtain the distribution information of potential earthquake source marine facilities, the population distribution information of potential earthquake source regions, and the surrounding environment information of potential earthquake sources.

[0098] In this embodiment, the distribution information of potential seismic source marine facilities may be information such as the geographical locations, quantities, types, scales, functions, etc. of offshore drilling platforms, submarine cables, marine observation stations, port terminals, offshore wind farms, etc. The population distribution information of the potential seismic source area may be the quantity, density, and spatial distribution characteristics of the population in the seismic statistical area and its surrounding areas, and may include the population distribution in urban and rural areas, the distribution of different age groups and occupational groups, etc. The surrounding environment information of the potential seismic source may be the characteristics of the natural environment and ecosystem surrounding the seismic statistical area. The natural environment may include topographical features (such as mountains, plains, coastlines, etc.), geological structures, meteorological conditions, etc.; the ecosystem may include marine ecosystems (such as coral reefs, fishing grounds, etc.), terrestrial ecosystems (such as forests, wetlands, etc.). The above information can be obtained by retrieving on the Internet. Among them, the potential seismic source area can be obtained by further dividing the seismic statistical area.

[0099] Step S602: Calculate the seismic risk coefficient information according to the magnitude-frequency characterization parameter, earthquake incidence characterization parameter, distribution information of potential seismic source marine facilities, population distribution information of the potential seismic source area, and surrounding environment information of the potential seismic source.

[0100] In this embodiment, it may be to perform quantization processing on various types of information collected. For example, assign corresponding values and weights to different types and importance levels of marine facilities; convert the population distribution information into quantization indicators such as population density; score the ecological vulnerability, terrain impact, etc. in the surrounding environment information. To eliminate the magnitude differences between different data, it is necessary to perform standardization processing on the quantized data, such as using the Min-Max normalization or Z-score normalization method. After the normalization processing, a comprehensive influence factor of magnitude-frequency and earthquake incidence, a distribution influence factor of marine facilities, a population distribution influence factor, and a surrounding environment influence factor are obtained. The seismic risk coefficient can be obtained by summing the comprehensive influence factor of magnitude-frequency and earthquake incidence, the distribution influence factor of marine facilities, the population distribution influence factor, and the surrounding environment influence factor.

[0101] Step S603: Determine the seismic risk response level information according to the seismic risk coefficient information and the preset risk coefficient calibration interval.

[0102] In this embodiment, the preset risk coefficient calibration interval can be set manually, or it can be set by referring to specific earthquake magnitude classification criteria, with different risk coefficient calibration intervals, and each interval corresponding to a specific earthquake risk response level, such as low risk, medium risk, high risk, and extremely high risk. It can be to compare the calculated earthquake risk coefficient with the preset calibration intervals one by one. If the earthquake risk coefficient is within the interval corresponding to low risk, then it is determined that the earthquake risk response level for this time is the low risk level; when the risk coefficient falls within the medium risk interval, the response level is the medium risk; if it is within the high risk interval, the response level is the high risk.

[0103] Step S604, generate multiple earthquake emergency rescue information according to the earthquake risk response level information, the preset earthquake risk level information, and the preset emergency response information.

[0104] In this embodiment, it can be to match the earthquake risk response level with the preset earthquake risk level. If the low risk level is matched, the corresponding rescue information can be extracted from the preset emergency response information. The earthquake emergency rescue information can include the deployment of a small number of rescue personnel, the reserve of basic materials, etc.; for the medium risk level, more resources can be invested, and the earthquake emergency rescue information can include information such as adding rescue teams and replenishing materials; when in the high risk or extremely high risk level, the emergency response information can be more comprehensive and with greater intensity, and the earthquake emergency rescue information can cover large-scale personnel rescue, the input of professional equipment, medical support, etc.

[0105] The method for calculating the sea area earthquake activity parameters provided by the embodiments of the present application comprehensively considers the distribution of potential source marine facilities, the distribution of regional population, and the surrounding environment information to calculate the risk coefficient, comprehensively and accurately quantifies the impact of sea area earthquakes on marine facilities, personnel, and the surrounding environment, and quickly and accurately generates multiple emergency rescue information adapted to the current earthquake risk situation according to the accurate risk coefficient, making the rescue strategy more targeted, providing a solid guarantee for the efficient implementation of rescue operations after sea area earthquakes, and comprehensively improving the ability to respond to sea area earthquake disasters.

[0106] Corresponding to the method in the above embodiment, Figure 7 The structural block diagram of the sea area earthquake activity parameter calculation system provided by the embodiments of the present application is shown. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown. Figure 7 The exemplary sea area earthquake activity parameter calculation system can be the execution body of the sea area earthquake activity parameter calculation method provided in the foregoing Embodiment 1.

[0107] Refer to Figure 7 , the sea area earthquake activity parameter calculation system includes:

[0108] An information acquisition module 710, configured to acquire earthquake event information and geological structure information;

[0109] An earthquake statistical area information generation module 720, configured to generate earthquake statistical area information according to the earthquake event information, geological structure information, preset neighborhood radius information, and preset number of area location points information; and

[0110] A sea area earthquake activity parameter calculation module 730, configured to calculate earthquake activity parameters according to the earthquake statistical area information, preset weight coefficient matrix, preset bias matrix, preset spatial mapping function, and preset mapping iteration number threshold.

[0111] For the processes of the modules in the sea area earthquake activity parameter calculation system provided by the embodiments of the present application to implement their respective functions, reference may be specifically made to the description of the foregoing Figure 1 Example 1 shown, which will not be elaborated here.

[0112] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0113] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0114] It should also be understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0115] As used in the specification of the present application and the appended claims, the term "if" may be interpreted as "when", "once", "in response to determining", or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" depending on the context.

[0116] In addition, in the description of the specification and the appended claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and should not be construed as indicating or implying relative importance. It should also be understood that although the terms "first", "second", etc. are used in the text in some embodiments of the present application to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first table can be named the second table, and similarly, the second table can be named the first table without departing from the scope of the various described embodiments. The first table and the second table are both tables, but they are not the same table.

[0117] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that a specific feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.

[0118] The method for calculating the marine seismic activity parameters provided by the embodiments of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc. The embodiments of the present application do not impose any restrictions on the specific types of terminal devices.

[0119] For example, the terminal device may be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device, or other processing devices connected to a wireless modem, a vehicle-mounted device, a vehicle-to-everything (V2X) terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a set top box (STB), a customer premise equipment (CPE), and / or other devices for communicating on a wireless system, as well as next-generation communication systems, such as a mobile terminal in a 5G network or a mobile terminal in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0120] By way of example and not limitation, when the terminal device is a wearable device, the wearable device may also be a general term for devices that are intelligently designed for daily wear using wearable technology and developed into wearable devices, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is either directly worn on the body or integrated into the user's clothing or accessories. A wearable device is not just a hardware device, but also realizes powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable intelligent devices include those with full functions and large sizes that can achieve complete or partial functions without relying on a smartphone, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to cooperate with other devices such as smartphones, such as various smart bracelets and smart jewelry for monitoring physical signs.

[0121] Figure 8 It is a schematic structural diagram of a terminal device provided by an embodiment of the present application. As Figure 8 shown, the terminal device 8 of this embodiment includes: at least one processor 80 ( Figure 8 only one is shown in the figure), and a memory 81. A computer program 82 that can run on the processor 80 is stored in the memory 81. When the processor 80 executes the computer program 82, the steps in the embodiments of the above-mentioned various methods for calculating seismic activity parameters in each sea area are implemented, such as Figure 1 the steps S101 to S103 shown in the figure. Alternatively, when the processor 80 executes the computer program 82, the functions of each module / unit in the above-mentioned system embodiments are implemented, such as Figure 7The functions of the modules 710 to 730 shown.

[0122] The terminal device 8 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art can understand that Figure 8 merely examples of the terminal device 8, which do not constitute a limitation on the terminal device 8, may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the terminal device may further include an input and sending device, a network access device, a bus, etc.

[0123] The so-called processor 80 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0124] In some embodiments, the memory 81 may be an internal storage unit of the terminal device 8, such as the hard disk or memory of the terminal device 8. The memory 81 may also be an external storage device of the terminal device 8, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 8. Further, the memory 81 may also include both the internal storage unit and the external storage device of the terminal device 8. The memory 81 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 81 may also be used to temporarily store data that has been sent or will be sent.

[0125] In addition, in each embodiment of the present application, the functional units may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0126] An embodiment of the present application further provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, the terminal device implements the steps in any of the above method embodiments.

[0127] An embodiment of the present application further provides a computer-readable storage medium storing a computer program, which when executed by a processor can implement the steps in each of the above method embodiments.

[0128] An embodiment of the present application provides a computer program product, which when running on a terminal device enables the terminal device to execute and implement the steps in each of the above method embodiments.

[0129] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above method embodiments of the present application can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps in each of the above method embodiments. Among them, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0130] In the above embodiments, the descriptions of the various embodiments have their own focuses. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0131] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0132] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0133] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for calculating sea area seismicity parameters, characterized in that: include: Obtain information on earthquake events and geological structures; Generate earthquake statistical regional information based on the earthquake event information, geological structure information, preset neighborhood radius information and preset regional location point quantity information; Calculating seismic activity parameters according to the earthquake statistical area information, a preset weight coefficient matrix, a preset bias matrix, a preset spatial mapping function, and a preset mapping iteration number threshold; The earthquake event information includes magnitude information and epicenter location information; The step of generating earthquake statistical regional information according to the earthquake event information, geological structure information, preset neighborhood radius information and preset regional location point quantity information specifically includes: Normalizing the magnitude information to obtain magnitude representation information; Calculate the logical spatial distance of each magnitude characterization information to obtain the magnitude logical distance; Calculate the logical spatial distance of each epicenter location information to obtain the location logical distance; Calculating the logical spatial distance of each of the geological structure information to obtain the geological structure logical distance; Calculate the comprehensive distance of earthquake information according to the magnitude logical distance, location logical distance, geological structure logical distance and preset weight coefficient; Generate multiple earthquake characterization information points according to the magnitude characterization information, epicenter location information, geological structure information and earthquake information comprehensive distance; When the earthquake information comprehensive distance is less than or equal to the preset neighborhood radius information, generating neighborhood set information of each earthquake characterization information point according to the earthquake characterization information point corresponding to the earthquake information comprehensive distance; Generate earthquake statistical area information according to the neighborhood set information and preset regional location point quantity information; The step of calculating the seismicity parameter according to the earthquake statistical area information, the preset weight coefficient matrix, the preset bias matrix, the preset spatial mapping function and the preset mapping iteration number threshold specifically includes: Generate an earthquake statistical parameter matrix according to the earthquake statistical area information; Calculating a seismicity characterization variable matrix according to the seismic statistical parameter matrix, a preset weight coefficient matrix, and a preset bias matrix; Using the seismicity characterization variable matrix as an independent variable of a preset spatial mapping function to generate a seismicity characterization spatial mapping variable matrix; The seismicity parameter is calculated according to the seismicity characterization space mapping variable matrix and a preset mapping iteration number threshold.

2. The method for calculating sea area seismic activity parameters according to claim 1, characterized in that: The step of generating earthquake statistical regional information according to the neighborhood set information and the preset regional location point quantity information specifically includes: Counting the number of information points in each of the neighborhood set information to obtain neighborhood set point quantity information; Determine whether the number of neighborhood set points is greater than or equal to the preset number of regional location points; If yes, the earthquake characterization information point corresponding to the neighborhood set point quantity information is used as the core point information; If not, when the number of neighborhood set points is not zero, the earthquake characterization information point corresponding to the number of neighborhood set points is used as the boundary point information; Generate a seismic statistical regional information representation set according to the core point information, boundary point information and neighborhood set information; The seismic statistical area information is generated according to the seismic statistical area information representation set.

3. The method for calculating sea area seismic activity parameters according to claim 1, characterized in that: The step of calculating the seismicity parameter according to the seismicity characterization space mapping variable matrix and a preset mapping iteration number threshold specifically includes: Counting the number of times the seismic activity characterization space mapping variable matrix is ​​generated to obtain the number of mapping iterations; Determining whether the mapping iteration number is less than a preset mapping iteration number threshold; If yes, the seismic activity characterization space mapping variable matrix is ​​used as the seismic statistical parameter matrix, and the process returns to the step of calculating the seismic activity characterization variable matrix according to the seismic statistical parameter matrix, the preset weight coefficient matrix and the preset bias matrix; If not, extracting the magnitude characterization information and earthquake occurrence number information of the seismic activity characterization space mapping variable matrix; The seismic activity parameters are calculated based on the magnitude characterization information and the earthquake occurrence frequency information.

4. The method for calculating sea area seismic activity parameters according to claim 1, characterized in that: The seismic activity parameters include magnitude frequency characterization parameters and earthquake occurrence rate characterization parameters.

5. The method for calculating sea area seismic activity parameters according to claim 4, characterized in that: After the step of calculating the seismicity parameters according to the earthquake statistical area information, the preset weight coefficient matrix, the preset bias matrix, the preset spatial mapping function and the preset mapping iteration number threshold, the method further includes: Obtain information on the distribution of marine facilities at potential earthquake sources, population distribution in potential earthquake source areas, and the surrounding environment of potential earthquake sources; Calculate earthquake risk coefficient information based on the magnitude frequency characterization parameters, earthquake occurrence rate characterization parameters, potential earthquake source marine facility distribution information, potential earthquake source regional population distribution information, and potential earthquake source surrounding environment information; Determining earthquake risk response level information according to the earthquake risk factor information and a preset risk factor calibration interval; A plurality of earthquake emergency rescue information are generated according to the earthquake risk response level information, the preset earthquake risk level information and the preset emergency response information.

6. A system for calculating parameters of marine seismic activity, characterized in that: include: An information acquisition module is used to obtain earthquake event information and geological structure information; An earthquake statistical area information generation module, used to generate earthquake statistical area information according to the earthquake event information, geological structure information, preset neighborhood radius information and preset area location point quantity information; as well as A sea area seismicity parameter calculation module, used to calculate seismicity parameters according to the seismic statistical area information, a preset weight coefficient matrix, a preset bias matrix, a preset spatial mapping function and a preset mapping iteration number threshold; The earthquake event information includes magnitude information and epicenter location information; The step of generating earthquake statistical regional information according to the earthquake event information, geological structure information, preset neighborhood radius information and preset regional location point quantity information specifically includes: Normalizing the magnitude information to obtain magnitude representation information; Calculate the logical spatial distance of each magnitude characterization information to obtain the magnitude logical distance; Calculate the logical spatial distance of each epicenter location information to obtain the location logical distance; Calculating the logical spatial distance of each of the geological structure information to obtain the geological structure logical distance; Calculate the comprehensive distance of earthquake information according to the magnitude logical distance, location logical distance, geological structure logical distance and preset weight coefficient; Generate multiple earthquake characterization information points according to the magnitude characterization information, epicenter location information, geological structure information and earthquake information comprehensive distance; When the earthquake information comprehensive distance is less than or equal to the preset neighborhood radius information, generating neighborhood set information of each earthquake characterization information point according to the earthquake characterization information point corresponding to the earthquake information comprehensive distance; Generate earthquake statistical regional information based on the neighborhood set information and the preset regional location point quantity information; The step of calculating the seismicity parameter according to the earthquake statistical area information, the preset weight coefficient matrix, the preset bias matrix, the preset spatial mapping function and the preset mapping iteration number threshold specifically includes: Generate an earthquake statistical parameter matrix according to the earthquake statistical area information; Calculating a seismicity characterization variable matrix according to the seismic statistical parameter matrix, a preset weight coefficient matrix, and a preset bias matrix; Using the seismicity characterization variable matrix as an independent variable of a preset spatial mapping function to generate a seismicity characterization spatial mapping variable matrix; The seismicity parameter is calculated according to the seismicity characterization space mapping variable matrix and a preset mapping iteration number threshold.

7. A terminal device, characterized in that: The terminal device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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