Earthquake event identification method and device based on earthquake early warning

Abstract

The present invention relates to the technical field of earthquake early warning, and in particular to a method and device for distinguishing earthquake events based on earthquake early warning, which improve the effectiveness and practicality of the earthquake early warning system and reduce the losses caused by earthquakes. The method is used to evaluate the impact of earthquake events monitored by the earthquake early warning system, and the method comprises: obtaining real-time earthquake data information detected by the earthquake early warning system in real time; extracting factor features of the real-time earthquake data information to obtain earthquake characteristic vectors, which include earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level; inputting the earthquake characteristic vectors into a pre-constructed earthquake impact range analysis model to obtain an earthquake impact range feature portrait; the earthquake impact range feature portrait consists of multiple annular areas and a central circle area, the multiple annular areas and the central circle area all take the epicenter position as the center, and the multiple annular areas and the central circle area are sequentially nested.

Description

Technical Field

[0001] The present invention relates to the technical field of earthquake early warning, and in particular to a method and device for distinguishing earthquake events based on earthquake early warning. Background Art

[0002] Earthquake is a common natural disaster that has caused huge loss of life and property to human society. With the development of science and technology, the earthquake early warning system has become one of the important means to reduce the impact of earthquake disasters. The earthquake early warning system can quickly provide warning information within a few seconds to tens of seconds after the earthquake occurs, so that people have time to take countermeasures and thus reduce the damage caused by the earthquake.

[0003] Although the existing earthquake early warning system can predict the occurrence of earthquakes to a certain extent, it still has shortcomings in accurately assessing the scope of earthquake impact. The existing earthquake impact assessment methods can often only provide large-scale earthquake impact predictions and lack detailed assessments of local areas, which may lead to unreasonable allocation of rescue resources. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an earthquake event identification method and device based on earthquake early warning, which improves the effectiveness and practicality of the earthquake early warning system and reduces the losses caused by earthquakes.

[0005] In a first aspect, the present invention provides a method for distinguishing earthquake events based on earthquake early warning, the method being used to perform impact assessment on earthquake events monitored by an earthquake early warning system, the method comprising:

[0006] Obtain real-time data information of earthquakes detected by the earthquake early warning system;

[0007] Extracting the key features of real-time earthquake data information to obtain earthquake characteristic vectors, which include earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level;

[0008] Inputting the earthquake characteristic vector into a pre-constructed earthquake influence range analysis model to obtain a characteristic image of the earthquake influence range; the characteristic image of the earthquake influence range is composed of a plurality of annular areas and a central circle area, the plurality of annular areas and the central circle area are all centered on the epicenter, the plurality of annular areas and the central circle area are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into a plurality of end-to-end connected fan-shaped cells, each fan-shaped cell is marked with a corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency;

[0009] Obtaining an earthquake impact assessment feature set and a historical earthquake feature vector for each fan-shaped cell, the earthquake impact assessment feature set including a quantified value of geological structure, a building seismic resistance level, and a population density; the historical earthquake feature vector including a historical number of earthquakes and a historical earthquake level feature value;

[0010] For each fan-shaped cell, the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell are used as inputs to the pre-built earthquake impact assessment model to obtain the earthquake event impact feature index;

[0011] The earthquake event impact characteristic index of each fan-shaped cell is input into the earthquake impact range characteristic image for marking, and the earthquake impact range characteristic circular matrix is ​​obtained;

[0012] The characteristic circular matrix of earthquake impact range is input into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and earthquake early warning and rescue strategies are formulated preferentially for the areas corresponding to each cell in the earthquake hazard unit set.

[0013] Furthermore, the mathematical calculation formula of the earthquake impact assessment model is: in, Represents the characteristic index of earthquake event impact, Indicates The weight of the feature, Indicates The value of the feature, n represents the number of features involved in calculating the earthquake event impact feature index. Further, the structure of the earthquake impact assessment model includes:

[0014] Input layer: used to receive the historical earthquake feature vectors, real-time earthquake levels, and earthquake impact assessment feature sets of each fan-shaped cell;

[0015] Feature extraction layer: extracts high-level features of input data through several neural network layers;

[0016] Fusion layer: used to fuse features from different sources;

[0017] Evaluation layer: performs in-depth analysis and calculation based on fusion features;

[0018] Output layer: used to output the earthquake event impact characteristic index and provide the earthquake impact score of each fan-shaped cell.

[0019] Furthermore, the method for acquiring real-time earthquake data information includes:

[0020] When an earthquake occurs, the seismograph will immediately capture the signal of the seismic wave and quickly transmit this raw data to the data center;

[0021] After the data arrives at the data center, it undergoes preprocessing operations, including noise filtering, signal enhancement, and waveform correction;

[0022] The pre-processed data is sent to the real-time data analysis system to quickly analyze the seismic wave signal and determine the real-time earthquake data information;

[0023] The real-time earthquake data information is packaged into a standardized format and transmitted to the earthquake early warning system.

[0024] Furthermore, the method for obtaining the seismic characteristic vector includes:

[0025] Preprocess the data obtained in real time from the earthquake early warning system, including noise filtering to remove background noise and interference signals in the data;

[0026] Perform Fourier transform and wavelet transform on the seismic waveform to extract waveform characteristic parameters;

[0027] Directly measure the maximum amplitude and main frequency components of seismic waves through the sensors of the seismograph;

[0028] Determine the epicenter location by inverting the travel time of seismic waves;

[0029] Estimate earthquake magnitude based on seismic wave amplitude, frequency and waveform parameters;

[0030] The extracted characteristic parameters are combined into a seismic characteristic vector.

[0031] Furthermore, the method for constructing the earthquake impact range analysis model includes:

[0032] Collect historical earthquake data;

[0033] Select a machine learning model as the basic architecture of the earthquake impact range analysis model. The machine learning model includes a convolutional neural network and a recurrent neural network.

[0034] Use historical data to train models and evaluate model performance through techniques such as cross-validation;

[0035] Adjust model parameters based on verification results to optimize model performance;

[0036] Deploy the earthquake impact range analysis model into the system.

[0037] Furthermore, the earthquake early warning and rescue strategy includes:

[0038] Based on the earthquake hazard unit cluster, emergency warning information is immediately issued to residents in these units through radio, television, mobile phone text messages and social media;

[0039] Determine the priority rescue areas according to the priority ranking in the earthquake hazard unit set;

[0040] Deploy relief supplies based on the needs assessment of each unit in the circular matrix of earthquake impact range characteristics;

[0041] Organize search and rescue teams, carry search and rescue equipment and medical equipment, and enter key areas of earthquake hazard units to conduct search and rescue work;

[0042] After the rescue work is completed, post-disaster resettlement work is carried out, including building temporary shelters, distributing daily necessities and providing psychological support;

[0043] Initiate post-disaster reconstruction planning and assess and repair damaged buildings;

[0044] Establish smooth information communication channels;

[0045] Collect and analyze data and information during the rescue process to provide experience and reference for future earthquake early warning and rescue work.

[0046] On the other hand, the present application also provides an earthquake event identification device based on earthquake early warning, the device comprising:

[0047] The earthquake real-time data acquisition module acquires the real-time earthquake data information detected by the earthquake early warning system in real time;

[0048] The earthquake characteristic vector extraction module extracts the key features of the real-time earthquake data information to obtain the earthquake characteristic vector, which includes earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level;

[0049] An earthquake impact range analysis module inputs an earthquake characteristic vector into a pre-built earthquake impact range analysis model to obtain a characteristic image of the earthquake impact range; the earthquake impact range characteristic image is composed of a plurality of annular areas and a central circle area, the plurality of annular areas and the central circle area are all centered on the epicenter, the plurality of annular areas and the central circle area are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into a plurality of end-to-end connected fan-shaped cells, each fan-shaped cell is marked with a corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency;

[0050] A feature collection module is used to obtain a set of earthquake impact assessment features and a historical earthquake feature vector for each fan-shaped cell, wherein the set of earthquake impact assessment features includes a quantified value of geological structure, a building seismic resistance level, and a population density; and the historical earthquake feature vector includes a number of historical earthquakes and a historical earthquake level feature value;

[0051] The earthquake impact assessment module, for each sector cell, takes the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell as input into the pre-built earthquake impact assessment model to obtain the earthquake event impact feature index;

[0052] The feature marking module inputs the earthquake event impact feature index of each fan-shaped cell into the earthquake impact range feature image for marking, and obtains the earthquake impact range feature circular matrix;

[0053] The hazard unit extraction and response strategy formulation module inputs the circular matrix of earthquake impact range characteristics into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and prioritizes earthquake early warning and rescue strategy formulation for the areas corresponding to each cell in the earthquake hazard unit set.

[0054] In a third aspect, the present application provides an electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program, when executed by the processor, implements the steps of any one of the above methods.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps in any one of the above-mentioned methods when executed by a processor.

[0056] Compared with the prior art, the present invention has the following advantages: by subdividing the earthquake impact range to form multiple annular areas and fan-shaped cells, and determining the specific impact degree of each cell based on factors such as earthquake waveform, amplitude and frequency, it is possible to provide a more detailed earthquake impact assessment than traditional large-scale predictions;

[0057] This method not only takes into account real-time earthquake data, but also combines static information such as the quantitative value of geological structure, the seismic resistance level of buildings, and population density, as well as dynamic information such as the number of historical earthquakes and the characteristic values ​​of historical earthquake levels, which can more comprehensively evaluate the impact of earthquakes on specific areas;

[0058] Since this method can obtain earthquake data in real time and process it quickly, it can provide early warning information within a short time after an earthquake occurs, giving people more time to take countermeasures;

[0059] By identifying the earthquake hazard unit cluster, early warnings can be issued to the most severely affected areas first, and corresponding rescue strategies can be formulated, which helps to optimize the allocation of rescue resources and ensure that limited resources can be used in the most critical places;

[0060] The generated circular matrix of earthquake impact range characteristics can intuitively show the extent of earthquake impact, which helps decision makers quickly understand which areas need urgent attention, thereby speeding up emergency response;

[0061] The use of pre-built earthquake impact assessment models and earthquake hazard unit extraction models can make scientific judgments based on data, avoid the bias that may be caused by subjective judgment, and enhance the reliability and accuracy of decision-making; this method can continuously adjust model parameters according to changes in actual conditions and add new influencing factors, making it have good adaptability and scalability to cope with different earthquake scenarios;

[0062] In summary, this earthquake event identification method based on earthquake early warning has greatly improved the effectiveness and practicality of the earthquake early warning system and reduced the losses caused by earthquakes through multi-dimensional and multi-level data analysis and model application. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is a flow chart of the present invention;

[0064] Figure 2 It is a structural diagram of an earthquake event identification device based on earthquake early warning. DETAILED DESCRIPTION

[0065] In the description of the present application, those skilled in the art should know that the present application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, the present application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), a combination of hardware and software. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable storage media, and the computer-readable storage medium contains computer program code.

[0066] The above-mentioned computer-readable storage medium can adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device, or device.

[0067] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws.

[0068] The present application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0069] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in the flowchart and / or block diagram.

[0070] These computer-readable program instructions can also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the flowchart and / or block diagram.

[0071] Computer-readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus can provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0072] The present application is described below in conjunction with the drawings in the present application.

[0073] Embodiment 1: Figure 1 As shown, the earthquake event identification method based on earthquake early warning of the present invention specifically includes the following steps:

[0074] S1. Real-time acquisition of earthquake data information detected by the earthquake early warning system;

[0075] The data of the earthquake early warning system comes from earthquake monitoring stations distributed in various places. The earthquake monitoring stations are spread across earthquake-active areas and potential earthquake risk areas. Each monitoring station is equipped with a high-precision seismometer that can sense the tiny vibrations of earthquake waves.

[0076] The method for acquiring real-time earthquake data information comprises:

[0077] When an earthquake occurs, the seismograph will immediately capture the signal of the seismic wave and quickly transmit the raw data to the data center; the transmission process uses a high-speed, low-latency communication protocol to ensure the real-time nature of the data;

[0078] After the data arrives at the data center, pre-processing operations are performed, including noise filtering, signal enhancement, and waveform correction to improve the accuracy and reliability of the data;

[0079] The pre-processed data is sent to the real-time data analysis system to quickly analyze the seismic wave signals and determine the real-time earthquake data information, including the time of the earthquake, the epicenter location, the focal depth and the preliminary earthquake level; the real-time earthquake data information is the basis for the subsequent analysis of the earthquake impact range and the release of early warning information;

[0080] Once the real-time earthquake data information is determined, the basic parameters of the earthquake are packaged into a standardized format and transmitted to users and systems that need this information, including earthquake early warning systems, emergency management departments, news media, and the public;

[0081] In order to ensure the reliability and stability of the earthquake early warning system, redundant mechanisms and backup systems for data collection, transmission and analysis are set up; in this way, even if a monitoring station or transmission link fails, the system can quickly switch to backup resources to ensure the continuity and integrity of real-time earthquake data information.

[0082] In this step, the rapid transmission and immediate processing of real-time earthquake data information are ensured by the seismic monitoring stations throughout the seismically active areas and potential earthquake risk areas, as well as the sensitive capture of tiny vibrations of seismic waves by seismographs, combined with high-speed and low-latency communication protocols. This high efficiency and real-time nature buys valuable time for the subsequent early warning information release and emergency response. After the data arrives at the data center, a series of preprocessing operations are performed to effectively improve the accuracy and reliability of the data. This not only helps to more accurately determine the basic parameters of the earthquake, but also provides a solid foundation for the subsequent analysis of the earthquake impact range and the accuracy of the early warning information. The preprocessed and analyzed real-time earthquake data information is packaged into a standardized format to facilitate information sharing and interaction between different users and systems. This standardized processing enables earthquake early warning information to be quickly and accurately conveyed to the earthquake early warning system, emergency management departments, news media and the public, improving the utilization rate and coverage of information. By setting up redundant mechanisms and backup systems for data acquisition, transmission and analysis, the reliability and stability of the earthquake early warning system are effectively enhanced. In the face of emergencies such as monitoring station or transmission link failures, the system can quickly switch to backup resources to ensure the continuity and integrity of real-time earthquake data information, thereby ensuring the continuity and effectiveness of early warning services.

[0083] S2, extracting the key features of the real-time earthquake data information to obtain earthquake characteristic vectors;

[0084] The method for obtaining the earthquake characteristic vector comprises:

[0085] Preprocess the data obtained from the earthquake early warning system in real time; including noise filtering, removing background noise and interference signals in the data to ensure the purity of the seismic wave signal; signal enhancement, enhancing the effective information in the seismic wave signal through digital signal processing technology; waveform correction, correcting the seismic waveform to eliminate distortion or delay that may occur during the transmission process;

[0086] Use digital signal processing technology to perform Fourier transform and wavelet transform on seismic waveforms to extract waveform characteristic parameters;

[0087] Directly measure the maximum amplitude and main frequency components of seismic waves through the sensors of the seismograph;

[0088] Using data from multiple seismic monitoring stations, the epicenter is determined by inverting the travel time of seismic waves;

[0089] Estimate the earthquake magnitude based on parameters such as earthquake wave amplitude, frequency, waveform, and empirical formulas;

[0090] The extracted characteristic parameters are combined into a seismic characteristic vector, which is a multi-dimensional data set;

[0091] The earthquake characteristic vector includes earthquake waveform, amplitude, frequency, epicenter location and real-time earthquake level; wherein the earthquake waveform represents the shape and characteristics of the earthquake wave, including the first arrival wave and the second arrival wave, which carry the information of the earthquake source and the information of the earthquake wave propagation path; the amplitude represents the maximum vibration amplitude of the earthquake wave, reflecting the intensity of the earthquake wave; the frequency represents the vibration frequency of the earthquake wave, and earthquake waves of different frequencies have different destructive power on buildings and geological structures; the epicenter location represents the geographical location where the earthquake occurs, and is the basis for assessing the scope of the earthquake impact; the real-time earthquake level represents the earthquake level preliminarily estimated based on the earthquake wave parameters.

[0092] In this step, through preprocessing steps, including noise filtering, signal enhancement and waveform correction, the background noise and interference signals in the data are effectively removed, ensuring the purity and accuracy of the seismic wave signal, laying a solid foundation for subsequent feature extraction and analysis; using Fourier transform, wavelet transform and direct measurement methods, multi-dimensional feature parameters including amplitude, frequency, waveform, etc. are extracted from the seismic waveform; these feature parameters fully reflect the physical characteristics and propagation laws of seismic waves, providing a rich source of information for seismic analysis; through the seismic wave travel time inversion technology, the epicenter position can be accurately determined; at the same time, combined with empirical formulas, real-time earthquakes, etc. are estimated. The real-time generation of earthquake sign vectors enables the earthquake monitoring and early warning system to respond quickly to earthquake events and provide timely and accurate earthquake information to relevant government departments. It helps to shorten emergency response time, improve decision-making efficiency, and minimize the losses caused by earthquake disasters. Through in-depth analysis and utilization of real-time earthquake data information, we can better understand the causes, propagation laws and destruction mechanisms of earthquakes, and provide a scientific basis for earthquake prediction, seismic fortification and disaster prevention. The long-term accumulation of earthquake sign vector data can also help to build a more complete earthquake disaster risk assessment and early warning system.

[0093] S3, inputting the earthquake characteristic vector into a pre-constructed earthquake impact range analysis model to obtain a characteristic image of the earthquake impact range; the characteristic image of the earthquake impact range is composed of a plurality of annular areas and a central circle area, the plurality of annular areas and the central circle area are all centered on the epicenter, the plurality of annular areas and the central circle area are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into a plurality of end-to-end connected fan-shaped cells, each fan-shaped cell is marked with a corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency;

[0094] The method for constructing the earthquake impact range analysis model comprises:

[0095] Collect a large amount of historical earthquake data, including earthquake waveforms, amplitudes, frequencies, epicenter locations, magnitudes, and post-earthquake impact reports;

[0096] According to the nature of the problem, a machine learning model is selected as the basic architecture of the earthquake impact range analysis model. The machine learning model includes convolutional neural network and recurrent neural network.

[0097] Use historical data to train the model and evaluate model performance through cross-validation and other techniques to ensure the generalization ability of the model;

[0098] Adjust model parameters based on verification results to optimize model performance;

[0099] The final model can predict the earthquake impact range based on new earthquake data input and generate a characteristic portrait of the earthquake impact range;

[0100] According to the propagation characteristics of seismic waves and geological conditions, multiple annular areas are divided with the epicenter as the center, and each annular area represents a different degree of earthquake impact;

[0101] Each annular area is further divided into multiple sector-shaped cells to more finely evaluate the impact of the local area;

[0102] The real-time earthquake level predicted by the model, the quantitative value of the geological structure, the seismic resistance level of buildings and the population density information are integrated to generate a portrait of the earthquake impact characteristics of each fan-shaped cell.

[0103] In this step, by constructing and applying the earthquake impact range analysis model, the earthquake impact range can be accurately predicted based on real-time earthquake data, and a detailed earthquake impact range feature portrait can be generated; it not only provides a macro overview of the earthquake impact, but also realizes a detailed assessment of the impact on local areas through the division of annular areas and fan-shaped cells; the real-time generation of the earthquake impact range feature portrait provides timely and accurate earthquake impact information for the government, rescue agencies and the public; it helps to quickly initiate emergency response mechanisms, deploy rescue resources, reduce disaster losses and improve rescue efficiency; the model comprehensively considers multiple factors such as seismic wave propagation characteristics, geological conditions, building seismic resistance level and population density, making the prediction results more scientific and comprehensive; through the open and transparent earthquake impact range feature portrait, the public can intuitively understand the impact of the earthquake on their area, thereby enhancing their self-protection awareness and response capabilities; this step realizes accurate prediction and assessment of earthquake impact by constructing and applying the earthquake impact range analysis model, providing strong support for emergency response, scientific decision-making and the improvement of public safety awareness.

[0104] S4, obtaining an earthquake impact assessment feature set and a historical earthquake feature vector for each fan-shaped cell; the earthquake impact assessment feature set includes a quantitative value of geological structure, a building seismic resistance level, and a population density;

[0105] Geological structure is an important factor affecting the extent of earthquake damage. This value is obtained through geological exploration, satellite remote sensing or GIS data analysis, and quantitatively represents the type, hardness, fault activity and other characteristics of underground rock formations. Different types of geological structures have different responses to the propagation and energy release of seismic waves.

[0106] The seismic resistance level of a building reflects its ability to resist earthquakes; it is determined by the building's design information, building materials, structural form, and historical seismic test data; in the earthquake early warning system, a building database is established to record and update the seismic resistance level information of each building so that its potential damage can be quickly assessed when an earthquake occurs;

[0107] Population density is an important factor affecting earthquake disaster losses. Through population census, GIS data and mobile communication network data analysis, we can obtain population density information of various regions. In earthquake early warning, high population density areas need more attention and priority rescue, because once an earthquake occurs in these areas, it may cause more serious loss of life and property.

[0108] The historical earthquake characteristic vector includes the number of historical earthquakes and the characteristic value of the historical earthquake level;

[0109] Record the number of earthquakes that have occurred in a certain area in history to understand the seismic activity and potential risks in the area; areas with a large number of historical earthquakes are relatively more likely to experience earthquakes in the future, so more caution is needed in assessment;

[0110] The historical earthquake level information in the region is summarized and analyzed to form characteristic values; these characteristic values ​​include the highest earthquake level, average earthquake level and earthquake level distribution, which provide a historical reference for assessing the degree of damage that the current earthquake may cause.

[0111] In this step, by comprehensively considering the three core elements of geological structure quantification value, building seismic resistance level and population density, the constructed earthquake impact assessment feature set can more comprehensively and accurately reflect the impact that a region may suffer in an earthquake; this multi-dimensional assessment method can more effectively predict the specific impact of earthquakes on specific areas compared with single factor assessment, thereby improving the accuracy of the assessment; in the earthquake early warning system, the pre-established building database and real-time updated seismic resistance level information enable rapid assessment of the potential damage of buildings when an earthquake occurs, providing key data support for emergency rescue and disaster management; this helps relevant government agencies to make decisions quickly, allocate resources and reduce disaster losses; through the analysis of historical earthquake feature vectors, including the number of historical earthquakes and earthquake level feature values, it is possible to gain an in-depth understanding of the seismic activity and potential risks of a certain area, and also enhance the risk management capabilities of future earthquake disasters in the region, making prevention and response measures more targeted and forward-looking; considering the important impact of population density on earthquake disaster losses, this step emphasizes special attention to areas with high population density; it helps to give priority to rescue and resource allocation in these areas when disasters occur, maximize the protection of people's lives and property, and also optimize the overall allocation efficiency of rescue resources.

[0112] S5. For each fan-shaped cell, the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell are input into a pre-built earthquake impact assessment model to obtain an earthquake event impact feature index;

[0113] The structure of the earthquake impact assessment model includes:

[0114] Input layer: used to receive the historical earthquake feature vectors, real-time earthquake levels, and earthquake impact assessment feature sets of each sector cell; the input data must be standardized or normalized to ensure the stability and accuracy of the model;

[0115] Feature extraction layer: extracts high-level features of the input data through several neural network layers; the purpose is to extract key patterns and relationships from historical earthquake data, real-time data, and impact assessment data;

[0116] Fusion layer: used to fuse features from different sources; the task of this layer is to integrate information from different data sources in order to more accurately assess the impact of earthquakes;

[0117] Evaluation layer: Based on the fusion features, in-depth analysis and calculation are performed, including several fully connected layers and activation functions; this layer generates an earthquake impact characteristic index for each cell, representing the predicted earthquake impact level;

[0118] Output layer: used to output the final earthquake event impact characteristic index, usually implemented through a linear layer or regression layer, providing the earthquake impact score of each fan-shaped cell;

[0119] The mathematical calculation formula of the earthquake impact assessment model is: in, Represents the characteristic index of earthquake event impact, Indicates The weight of the feature, Indicates The value of the feature, n represents the number of features involved in the calculation of the earthquake event impact feature index.

[0120] In this step, the model can perform an independent earthquake impact assessment for each sector cell, thereby achieving a refined characterization of the earthquake impact range; it helps to more accurately understand the specific impact of earthquakes on different regions and provide strong support for subsequent rescue and emergency response; the model integrates multi-source data such as historical earthquake feature vectors, real-time earthquake levels, and earthquake impact assessment feature sets; the integration of multi-source data makes the assessment results more comprehensive and accurate, and can comprehensively consider factors such as historical experience, real-time data, and regional characteristics; through the feature extraction layer, the model can automatically extract high-level features from the input data, and the feature extraction capability improves the prediction accuracy and generalization ability of the model; since the model can receive data from the earthquake early warning system in real time, it can respond quickly to earthquake events and generate real-time earthquake impact assessment results; this dynamic response capability helps to provide effective early warning and rescue guidance as soon as possible after an earthquake occurs; integrating the earthquake impact assessment model into the earthquake early warning system can significantly improve the overall effectiveness of the early warning system; by providing more accurate and refined earthquake impact assessment results, the early warning system can better guide the public and relevant departments to take countermeasures to reduce the risks and losses of earthquake disasters.

[0121] S6, inputting the earthquake event impact characteristic index of each fan-shaped cell into the earthquake impact range characteristic image for marking, and obtaining the earthquake impact range characteristic circular matrix;

[0122] The method for constructing the characteristic circular matrix of the earthquake impact range includes:

[0123] Map the earthquake event impact characteristic index of each fan-shaped cell to the corresponding fan-shaped cell in the earthquake impact range characteristic portrait, ensuring that each characteristic index can accurately correspond to the fan-shaped cell to which it belongs;

[0124] After completing the data mapping, we start to build the earthquake impact range characteristic circular matrix; each element in this matrix stores the earthquake event impact characteristic index of the corresponding fan-shaped cell;

[0125] Since the annular area and the fan-shaped cells in the earthquake impact range feature image have a special spatial relationship, this matrix may not appear as a regular rectangular array physically; but logically, it can be regarded as a two-dimensional data structure that contains the impact characteristic indexes of all fan-shaped cells;

[0126] In the process of matrix construction, the earthquake impact range feature portrait is “marked”; the earthquake event impact feature index in each fan-shaped cell is regarded as the “marker” of the cell, which is used to indicate the potential impact of the cell in the earthquake;

[0127] Finally, a characteristic circular matrix of the earthquake impact range is obtained, which intuitively shows the impact of the earthquake on different regions.

[0128] In this step, by accurately mapping the earthquake event impact characteristic index to each fan-shaped cell in the earthquake impact range characteristic portrait, a refined assessment of the earthquake impact range is achieved; the refined assessment method is more accurate than the traditional large-scale prediction and can better reflect the potential impact of the earthquake on different local areas; the constructed earthquake impact range characteristic circular matrix intuitively shows the impact of the earthquake on different regions; it enables decision makers and rescue personnel to quickly understand the distribution of earthquake impact, and provides strong support for the formulation of scientific and reasonable early warning and rescue strategies; based on the earthquake impact range characteristic circular matrix, it is possible to give priority to the allocation of early warning and rescue resources to areas with greater earthquake hazards; significantly improve the rescue efficiency and reduce casualties and property losses caused by earthquake disasters; this step relies on the data of the earthquake event impact characteristic index and the earthquake impact range characteristic portrait, realizing a data-driven decision-making process; this data-based assessment method is more objective and scientific, reducing the subjectivity and uncertainty of human judgment; the construction method of the earthquake impact range characteristic circular matrix has certain flexibility and can be adjusted and optimized according to different earthquake early warning systems and assessment needs; at the same time, the matrix can also be combined with other geographic information systems to achieve a more comprehensive and integrated earthquake impact assessment.

[0129] S7. Input the earthquake impact range characteristic circular matrix into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and give priority to earthquake early warning and rescue strategy formulation for the areas corresponding to each cell in the earthquake hazard unit set.

[0130] According to the circular matrix of earthquake impact range characteristics, the model will identify those fan-shaped cells with higher earthquake event impact characteristic indexes, which are earthquake hazard units;

[0131] Once the earthquake hazard units are determined, the information of these units needs to be aggregated to form an earthquake hazard unit set; this set includes all the fan-shaped units identified as high-risk, each of which has its geographical location information and the corresponding earthquake event impact characteristic index;

[0132] Based on the information in the earthquake hazard unit set, earthquake early warning and rescue strategies are formulated for these areas;

[0133] The earthquake early warning and rescue strategies include:

[0134] Once a cluster of earthquake hazard units is identified, emergency warning information is immediately issued to residents in these units through radio, television, mobile phone text messages and social media; the information includes the intensity of the earthquake, the estimated arrival time and recommended protective measures; ensure the accuracy and timeliness of the warning information so that residents have enough time to take protective measures and reduce damage;

[0135] Determine the priority rescue areas according to the priority ranking of the earthquake hazard unit set; ensure that rescue teams and supplies can reach these areas first to rescue the injured and trapped people as quickly as possible;

[0136] According to the needs assessment of each unit in the circular matrix of earthquake impact range characteristics, rescue teams, medical equipment, food, drinking water and daily necessities are rationally deployed;

[0137] Organize professional search and rescue teams, carry necessary search and rescue equipment and medical equipment, and enter key areas of earthquake hazard units to conduct search and rescue work; provide on-site treatment and transfer of injured persons to ensure that they can receive professional medical assistance in a timely manner;

[0138] After the rescue work was basically completed, post-disaster resettlement work began, including building temporary shelters, distributing daily necessities and providing psychological support;

[0139] Launch post-disaster reconstruction planning, assess and repair damaged buildings, and ensure that disaster-affected people can resume normal life as soon as possible;

[0140] Establish smooth information communication channels to ensure timely transmission of information and feedback between rescue workers, disaster-stricken people and government departments;

[0141] Collect and analyze data and information during the rescue process to provide experience and reference for future earthquake early warning and rescue work.

[0142] In this step, by inputting the circular matrix of earthquake impact range characteristics into the earthquake hazard unit extraction model, the fan-shaped cells with higher earthquake event impact characteristic index, namely earthquake hazard units, can be accurately identified; compared with traditional large-scale predictions, this refined evaluation method can more accurately reflect the actual impact of earthquakes on different regions, and provide a scientific basis for subsequent early warning and rescue work; the formation of an earthquake hazard unit set makes the allocation of rescue resources more reasonable and efficient; by giving priority to early warning and rescue of areas in the earthquake hazard unit set, it can ensure that rescue teams and materials can quickly reach the most needed places, minimizing casualties and property losses; the timely release of emergency warning information enables residents to Necessary protective measures are taken before arrival to effectively reduce damage; at the same time, according to the priority ranking of earthquake hazard units, the rescue work can be carried out in an orderly manner, which improves the overall rescue efficiency; after the rescue work is completed, timely post-disaster resettlement and reconstruction planning ensures that the basic living needs of the affected people are met; the construction of temporary shelters, the distribution of daily necessities and the provision of psychological assistance provide all-round protection for the affected people and help them resume normal life as soon as possible; by collecting and analyzing data and information during the rescue process, it can provide valuable experience and reference for future earthquake early warning and rescue work; this continuous improvement mechanism helps to continuously improve the level and capacity of earthquake early warning and rescue, and better cope with future earthquake disasters.

[0143] Embodiment 2: Figure 2 As shown, the earthquake event identification device based on earthquake early warning of the present invention specifically includes the following modules:

[0144] The earthquake real-time data acquisition module acquires the real-time earthquake data information detected by the earthquake early warning system in real time;

[0145] The earthquake characteristic vector extraction module extracts the key features of the real-time earthquake data information to obtain the earthquake characteristic vector, which includes earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level;

[0146] An earthquake impact range analysis module inputs an earthquake characteristic vector into a pre-built earthquake impact range analysis model to obtain a characteristic image of the earthquake impact range; the earthquake impact range characteristic image is composed of a plurality of annular areas and a central circle area, the plurality of annular areas and the central circle area are all centered on the epicenter, the plurality of annular areas and the central circle area are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into a plurality of end-to-end connected fan-shaped cells, each fan-shaped cell is marked with a corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency;

[0147] A feature collection module is used to obtain a set of earthquake impact assessment features and a historical earthquake feature vector for each fan-shaped cell, wherein the set of earthquake impact assessment features includes a quantified value of geological structure, a building seismic resistance level, and a population density; and the historical earthquake feature vector includes a number of historical earthquakes and a historical earthquake level feature value;

[0148] The earthquake impact assessment module, for each sector cell, takes the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell as input into the pre-built earthquake impact assessment model to obtain the earthquake event impact feature index;

[0149] The feature marking module inputs the earthquake event impact feature index of each fan-shaped cell into the earthquake impact range feature image for marking, and obtains the earthquake impact range feature circular matrix;

[0150] The hazard unit extraction and response strategy formulation module inputs the circular matrix of earthquake impact range characteristics into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and prioritizes earthquake early warning and rescue strategy formulation for the areas corresponding to each cell in the earthquake hazard unit set.

[0151] The system divides the earthquake impact area into multiple fan-shaped cells and conducts independent assessments in each cell, making the assessment of earthquake impact more detailed and able to more accurately reflect the actual disaster situation in different regions. It not only takes into account real-time earthquake data, but also combines multiple factors such as the quantitative value of geological structure, the seismic resistance level of buildings and population density, as well as historical earthquake characteristic vectors, which helps to more comprehensively assess the specific impact of earthquakes on various regions.

[0152] The system can respond quickly to new earthquake events and dynamically adjust its assessment results as the earthquake impact changes. By identifying the earthquake hazard unit set, the system can prioritize early warning and formulate rescue strategies for the areas most in need of help, thereby optimizing the allocation of rescue resources and improving rescue efficiency.

[0153] The system relies on pre-built earthquake impact assessment models and earthquake hazard unit extraction models, which makes the decision-making process more scientific and reasonable and reduces the uncertainty in human judgment. By generating a circular matrix of earthquake impact range characteristics, the system provides an intuitive visual presentation, which helps decision makers quickly understand the distribution of earthquake impacts.

[0154] In summary, the system has greatly improved the effectiveness and practicality of the earthquake early warning system through multi-dimensional and multi-level data analysis and model application, and helps reduce the losses caused by earthquakes.

[0155] The various variations and specific embodiments of the earthquake event identification method based on earthquake early warning in the aforementioned embodiment 1 are also applicable to the earthquake event identification device based on earthquake early warning in this embodiment. Through the aforementioned detailed description of the earthquake event identification method based on earthquake early warning, those skilled in the art can clearly understand the implementation method of the earthquake event identification device based on earthquake early warning in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0156] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0157] The above is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the technical principle of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for distinguishing earthquake events based on earthquake early warning, characterized in that: The method is used to evaluate the impact of an earthquake event monitored by an earthquake early warning system, and the method comprises: Real-time acquisition of earthquake data information detected by the earthquake early warning system; Extracting the key features of real-time earthquake data information to obtain earthquake characteristic vectors, which include earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level; Input the earthquake characteristic vector into the pre-constructed earthquake impact range analysis model to obtain the earthquake impact range characteristic image; the earthquake impact range characteristic image is composed of multiple annular areas and central circle areas, the multiple annular areas and central circle areas are all centered on the epicenter, the multiple annular areas and central circle areas are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into multiple end-to-end fan-shaped cells, each fan-shaped cell is marked with the corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency; according to the seismic wave propagation characteristics and geological conditions, multiple annular areas are divided with the epicenter as the center, and each annular area represents a different degree of earthquake impact; Obtaining an earthquake impact assessment feature set and a historical earthquake feature vector for each fan-shaped cell, the earthquake impact assessment feature set including a quantified value of geological structure, a building seismic resistance level, and a population density; the historical earthquake feature vector including a historical number of earthquakes and a historical earthquake level feature value; For each fan-shaped cell, the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell are used as inputs to the pre-built earthquake impact assessment model to obtain the earthquake event impact feature index; The earthquake event impact characteristic index of each fan-shaped cell is input into the earthquake impact range characteristic image for marking, and the earthquake impact range characteristic circular matrix is ​​obtained; The characteristic circular matrix of earthquake impact range is input into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and earthquake early warning and rescue strategies are formulated preferentially for the areas corresponding to each cell in the earthquake hazard unit set.

2. The earthquake event identification method based on earthquake early warning according to claim 1, characterized in that: The mathematical calculation formula of the earthquake impact assessment model is: Among them, I represents the characteristic index of earthquake event impact, w i represents the weight of the i-th feature, x i represents the value of the i-th feature, and n represents the number of features involved in the calculation of the earthquake event impact characteristic index.

3. The earthquake event identification method based on earthquake early warning according to claim 2, characterized in that: The structure of the earthquake impact assessment model includes: Input layer: used to receive the historical earthquake feature vectors, real-time earthquake levels, and earthquake impact assessment feature sets of each fan-shaped cell; Feature extraction layer: extracts high-level features of input data through several neural network layers; Fusion layer: used to fuse features from different sources; Evaluation layer: performs in-depth analysis and calculation based on fusion features; Output layer: used to output the earthquake event impact characteristic index and provide the earthquake impact score of each fan-shaped cell.

4. The earthquake event identification method based on earthquake early warning according to claim 1, characterized in that: The method for acquiring real-time earthquake data information comprises: When an earthquake occurs, the seismograph will immediately capture the signal of the seismic wave and quickly transmit this raw data to the data center; After the data arrives at the data center, it undergoes preprocessing operations, including noise filtering, signal enhancement, and waveform correction; The pre-processed data is sent to the real-time data analysis system to quickly analyze the seismic wave signal and determine the real-time earthquake data information; The real-time earthquake data information is packaged into a standardized format and transmitted to the earthquake early warning system.

5. The earthquake event identification method based on earthquake early warning according to claim 1, characterized in that: The method for obtaining the earthquake characteristic vector comprises: Preprocess the data obtained in real time from the earthquake early warning system, including noise filtering to remove background noise and interference signals in the data; Perform Fourier transform and wavelet transform on the seismic waveform to extract waveform characteristic parameters; Directly measure the maximum amplitude and main frequency components of seismic waves through the sensors of the seismograph; Determine the epicenter location through seismic wave travel time inversion; Estimate earthquake magnitude based on seismic wave amplitude, frequency and waveform parameters; The extracted characteristic parameters are combined into a seismic characteristic vector.

6. The earthquake event identification method based on earthquake early warning according to claim 1, characterized in that: The method for constructing the earthquake impact range analysis model comprises: Collect historical earthquake data; Select a machine learning model as the basic architecture of the earthquake impact range analysis model. The machine learning model includes a convolutional neural network and a recurrent neural network. Use historical data to train models and evaluate model performance through techniques such as cross-validation; Adjust model parameters based on verification results to optimize model performance; Deploy the earthquake impact range analysis model into the system.

7. The earthquake event identification method based on earthquake early warning according to claim 1, characterized in that: The earthquake early warning and rescue strategies include: Immediately issue emergency warning information to residents in earthquake hazard units through radio, television, mobile phone text messages and social media; Determine the priority rescue areas according to the priority ranking in the earthquake hazard unit set; Deploy relief supplies based on the needs assessment of each unit in the circular matrix of earthquake impact range characteristics; Organize search and rescue teams, carry search and rescue equipment and medical equipment, and enter key areas of earthquake hazard units to conduct search and rescue work; After the rescue work is completed, post-disaster resettlement work is carried out, including building temporary shelters, distributing daily necessities and providing psychological support; Initiate post-disaster reconstruction planning and assess and repair damaged buildings; Establish smooth information communication channels; Collect and analyze data and information during the rescue process to provide experience and reference for future earthquake early warning and rescue work.

8. An earthquake event identification device based on earthquake early warning, characterized in that: The device is applied to the earthquake event identification method based on earthquake early warning according to claim 1, and the device comprises: The earthquake real-time data acquisition module acquires the real-time earthquake data information detected by the earthquake early warning system in real time; The earthquake characteristic vector extraction module extracts the key features of the real-time earthquake data information to obtain the earthquake characteristic vector, which includes earthquake waveform, amplitude, frequency, epicenter position and real-time earthquake level; An earthquake impact range analysis module inputs an earthquake characteristic vector into a pre-built earthquake impact range analysis model to obtain a characteristic image of the earthquake impact range; the earthquake impact range characteristic image is composed of a plurality of annular areas and a central circle area, the plurality of annular areas and the central circle area are all centered on the epicenter, the plurality of annular areas and the central circle area are successively encircled, and the boundaries of adjacent areas overlap, each annular area is divided into a plurality of end-to-end connected fan-shaped cells, each fan-shaped cell is marked with a corresponding real-time earthquake level, and the radial width of the annular area and the central angle corresponding to the fan-shaped cell are determined by the earthquake waveform, amplitude and frequency; A feature collection module is used to obtain a set of earthquake impact assessment features and a historical earthquake feature vector for each fan-shaped cell, wherein the set of earthquake impact assessment features includes a quantified value of geological structure, a building seismic resistance level, and a population density; and the historical earthquake feature vector includes a number of historical earthquakes and a historical earthquake level feature value; The earthquake impact assessment module, for each sector cell, takes the historical earthquake feature vector, real-time earthquake level and earthquake impact assessment feature set corresponding to the cell as input into the pre-built earthquake impact assessment model to obtain the earthquake event impact feature index; The feature marking module inputs the earthquake event impact feature index of each fan-shaped cell into the earthquake impact range feature image for marking, and obtains the earthquake impact range feature circular matrix; The hazard unit extraction and response strategy formulation module inputs the circular matrix of earthquake impact range characteristics into the earthquake hazard unit extraction model to obtain the earthquake hazard unit set, and prioritizes earthquake early warning and rescue strategy formulation for the areas corresponding to each cell in the earthquake hazard unit set.

9. An earthquake event identification electronic device based on earthquake early warning, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and characterized in that: When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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