145 results about "Earthquake hazard" patented technology

The invention belongs to the technical field of earthquake disaster scene recognition, and discloses an earthquake disaster scene recognition method based on deep learning. The method comprises the following specific steps: S1, data acquisition and preprocessing; S1.1, multi-source heterogeneous data acquisition and establishment of a comprehensive database containing seismic waveform data, surface deformation data, building structure data, geographic information data and historical disaster record data; through fusion of a 3D convolutional network, a graph attention mechanism, a space-time LSTM and an adaptive cross-modal attention fusion technology, combined modeling of a seismic waveform space-time evolution law, an earth surface deformation space distribution characteristic, a building group topology vulnerability and disaster chain time sequence association is realized, the characterization capability of a complex nonlinear disaster mode is effectively improved, and the method has the advantages of high adaptability and high reliability. And disaster assessment response time is shortened to a sub-second level through mixed precision quantification and edge computing deployment, and high recognition accuracy is still kept in a scene with strong noise and data missing in combination with a multi-task classifier and a physical constraint verification mechanism.

The invention provides an emergency broadcast intelligent triggering system based on multi-source seismic data fusion, and relates to the technical field of seismic monitoring and early warning, and the system comprises a data receiving module which is used for receiving multi-source seismic early warning information in real time, including seismic source parameter data, strong vibration observation data and real-time early warning parameters, and transmitting the multi-source seismic early warning information through a built-in communication protocol; and outputting the standardized multi-source seismic data. And the localization calculation module is used for carrying out real-time analysis on the standardized multi-source seismic data, extracting a P-wave initial parameter, a seismic motion acceleration predicted value and a seismic source fracture feature, carrying out dynamic calibration on an analysis result by combining actual measurement data of a built-in intensity meter, and outputting a multi-dimensional seismic data stream verified by the intensity meter. Through multi-source earthquake data fusion, real-time analysis and calibration, dynamic risk modeling and intelligent broadcast scheduling, generation and efficient propagation of earthquake early warning information are realized, emergency response timeliness and pertinence are improved, and earthquake disaster risks are reduced.

The invention belongs to the technical field of earthquake disaster scene construction, and discloses an earthquake disaster scene construction method based on big data, and the method comprises the following specific steps: 1, multi-source heterogeneous data collection and preprocessing ground structure data collection: employing a multi-platform remote sensing technology to obtain urban building group space distribution characteristics; a three-dimensional coupling model of an underground pipe network and a ground building is constructed by integrating multi-source data, so that the defect of isolated analysis of a ground system and an underground system in a traditional method is overcome, and synchronous simulation of a dynamic association process of pipe network fracture and building damage is realized; the additional influence of pipe network failure on the building foundation stability and the linkage effect of soil erosion caused by leakage fluid are accurately analyzed, meanwhile, a time-space association rule of pipe network fracture events and multiple types of secondary disasters such as building fire disasters and fire fighting failure is established, and the building group function paralysis risk and the disaster diffusion range under different damage degrees are dynamically predicted; and the disaster evolution path is displayed in real time through a visual platform.

The invention provides an earthquake disaster prediction method based on iron tower monitoring data, and relates to the technical field of disaster prediction, and the method comprises the steps: obtaining a monitoring data set, extracting an earthquake region, extracting earthquake time node data, constructing an earthquake iron tower reference set, carrying out the model training, obtaining an earthquake disaster prediction model, and obtaining a data prediction structure. And carrying out data standardization processing on the iron tower monitoring data, inputting a processing result into the earthquake disaster prediction model to obtain a prediction result, and finally carrying out disaster relief strategy guidance feedback. The method mainly solves the problems that the occurrence time, place and magnitude of an earthquake cannot be accurately predicted, the prediction time range is short, and the long-term prediction requirement cannot be met. Through earthquake monitoring on the iron tower, potential safety hazards can be found and solved in time, earthquake disasters can be dealt with better, and casualties and economic losses are reduced.

The invention discloses a water injection induced earthquake monitoring and fault activation detection system, and belongs to the field of earthquake monitoring and fault activation detection. The earthquake observation module is used for obtaining earthquake monitoring data; the seismic phase data extraction module is used for carrying out micro-seismic identification according to the seismic monitoring data to obtain seismic phase data; the earthquake initial positioning module is used for obtaining an earthquake directory of initial positioning; the earthquake fine positioning module is used for carrying out secondary positioning to obtain an earthquake directory of fine positioning; the fault and structure modeling module is used for integrating the finely positioned seismic catalog into a three-dimensional geologic structure model and carrying out spatial positioning and visualization of seismic activities; and the fault activation and earthquake risk analysis module is used for analyzing the earthquake activity time change trend, b value change, fault activation and earthquake risk according to the three-dimensional geologic structure model. The method solves the problem that an existing method lacks monitoring of fault activation and weakening of the shale gas development area and water injection induced earthquakes.

The invention relates to the technical field of ad hoc network transmission management, and discloses a wireless ad hoc network transmission management method for earthquake early warning information, which comprises the following steps: S101, generating a comprehensive failure risk prediction value through a multi-source data fusion algorithm according to earthquake wave data, geologic structure data, historical earthquake data and meteorological data; s102, constructing a hierarchical failure probability model based on the comprehensive failure risk prediction value, and generating a node failure risk probability graph; the weight of each layer is distributed according to the earthquake stage; s103, constructing a network topology, calculating the survival time of network nodes, calculating the weighted comprehensive failure probability of each network node, and dynamically updating the network topology; and S104, according to the weighted comprehensive failure probability and the survival time of each network node, fusing to obtain a node stable utilization characteristic, and further executing staged resource scheduling. According to the invention, accurate prediction and staged resource scheduling of the network node failure risk in the whole earthquake disaster process are realized.

The invention discloses an emergency management intelligent detection alarm system and method based on multi-modal information, and the system obtains and fuses the multi-source information of seismic waves, building structures, urban pipe networks and the like through a multi-modal seismic information collection and fusion module, and calculates the dynamic response through a dynamic analysis module based on an improved Newmark-beta algorithm. And a finite element simulation model building module is combined with city parameters to build a high-precision model. The LSTM-PINN hybrid analysis model module carries out deep analysis and prediction on data, the disaster risk assessment and classification module completes risk classification in combination with population and economic parameters, and finally the intelligent detection alarm module triggers corresponding alarms according to classification results and sends information in multiple channels. The method comprises the steps of information acquisition, dynamic analysis, model construction, disaster prediction, risk assessment and grading, alarm and the like, intelligent detection and accurate alarm of urban earthquake disasters are realized, and the emergency management efficiency and reliability are improved.

The invention discloses an earthquake disaster loss dynamic assessment method and system based on multi-source disaster situation data, and relates to the technical field of earthquake disaster loss assessment, and the method comprises the following steps: S1, obtaining the multi-source original data of an earthquake disaster, and carrying out the preprocessing, the multi-source original data comprises seismic oscillation parameter data and multi-source disaster data; and S2, based on the preprocessed multi-source data, constructing a coupling driving model of the earthquake influence field and the multi-source disaster situation data, and generating a regional disaster damage thermodynamic map. According to the earthquake disaster loss dynamic evaluation method and system based on the multi-source disaster situation data, the earthquake multi-source disaster situation data is acquired, the coupling driving model of the earthquake influence field and the multi-source disaster situation data is constructed, and the influence of various factors on the earthquake disaster loss is comprehensively considered, so that the limitation that a traditional method depends on a single data source is overcome; the real situation of earthquake disaster loss can be reflected more comprehensively and accurately, and a more reliable basis is provided for rescue decision making.

The invention discloses an earthquake early warning and rapid reporting Internet of Things system, method and device and a storage medium. The system comprises an earthquake information acquisition module, a cloud server and an early warning information issuing module. The earthquake information acquisition module is used for acquiring earthquake monitoring physical quantities, generating earthquake monitoring data according to the earthquake monitoring physical quantities and sending the earthquake monitoring data to the cloud server; the cloud server is used for estimating an earthquake grade and an earthquake source position when an earthquake event is identified according to the earthquake monitoring data; and the early warning information issuing module is used for determining a to-be-early-warned area according to the earthquake grade and the earthquake source position, and sending earthquake early warning information to a broadcasting system, mobile equipment and an outdoor alarm system in the to-be-early-warned area at the same time. By adopting the technical scheme, the earthquake can be quickly and accurately detected, and the earthquake early warning information can be quickly and accurately spread, so that the influence of earthquake disasters is reduced.

The invention discloses an earthquake disaster risk assessment method based on a complex network model, and relates to the technical field of earthquake disaster assessment. Comprising the following steps: S1, constructing an earthquake disaster complex network model; s2, data acquisition and preprocessing; s3, topological structure analysis; s4, constructing a risk assessment index system; and S5, establishing a mathematical model and calculating a risk level. The earthquake disaster complex network model constructed by the invention can comprehensively and intuitively describe the complex mutual relation among the elements in the earthquake disaster system, overcomes the defect that the traditional assessment method is insufficient in consideration of the system complexity, and improves the accuracy and reliability of the assessment result.

The invention relates to the technical field of earthquake disaster emergency monitoring, in particular to an intelligent recognition system and method for an earthquake ground surface broken zone, and the system comprises a heterogeneous data registration module, a feature extraction and fusion module, a broken zone segmentation module, an active learning module, a morphological optimization module and the like, and achieves the precise processing of remote sensing data and the intelligent recognition of the broken zone. The system adopts multi-scale feature point matching and self-adaptive weight registration, so that the data registration precision is improved by more than 30%, and the dependence of a traditional method on artificial experience is overcome; through feature fusion of multi-modal feature decoupling and attention guidance, and in combination with multi-scale spatial pyramid pooling and deformation sensitive segmentation, the system effectively identifies a fractured zone and evaluates and predicts uncertainty; the active learning module optimizes training data through Bayesian estimation and a hybrid sampling strategy, and the form optimization module finally outputs accurate broken zone distribution and attribute information by utilizing geological constraint and fault topology reasoning, so that the intelligent level and efficiency of earthquake disaster emergency monitoring are improved.

The invention provides an earthquake disaster loss pre-evaluation method and system based on field investigation. The method comprises the following steps: according to a sampling survey result of a working area, establishing a localized building vulnerability matrix taking a county as a unit, and classifying the localized building vulnerability matrix according to a building function, a building age, a floor number and a fortification grade; based on the spatial database, the multiple sets of set seismic parameters and the localized building vulnerability matrix, an earthquake disaster loss pre-evaluation result is obtained through a pre-evaluation model, and the earthquake disaster loss pre-evaluation result comprises the affected area under each set of set seismic parameters, the estimated number of casualties and the direct economic loss; and when the error between the earthquake disaster loss pre-evaluation result and the actual earthquake disaster loss is greater than a preset error threshold value, dynamically correcting the model parameters of the pre-evaluation model according to the sampling survey result. According to the technical scheme provided by the invention, the evaluation error is reduced, and the accuracy of pre-evaluation is improved.

The invention belongs to the technical field of earthquake monitoring, and provides an earthquake geophysical data anomaly detection and early warning method based on big data analysis, which comprises the following steps: S1, acquiring earthquake geophysical observation data; s2, carrying out cleaning, integration and normalization processing on the collected data; s3, extracting characteristic parameters related to interference and abnormity from the preprocessed data; s4, performing anomaly detection on the extracted feature parameters by using a big data analysis technology; according to the method, various seismic geophysical data such as seismic wave data, geological structure data and underground fluid dynamics are collected, systematic cleaning, integration, normalization processing and feature extraction are carried out, anomaly detection is carried out by using a big data analysis technology, and anomaly early warning information is generated in combination with a pre-established anomaly early warning model. Accuracy and timeliness of earthquake monitoring are effectively improved, and powerful technical support is provided for prevention and response of earthquake disasters.

The invention provides a structure vulnerability analysis method and system based on earthquake magnitude, distance and site conditions, a storage medium and a computer program product. The method comprises the following steps: adopting a preset sampling algorithm to obtain preset earthquake magnitude, distance and site conditions, and acceleration time history samples corresponding to the preset earthquake magnitude, distance and site conditions; based on the acceleration time-history sample, performing nonlinear dynamic time-history analysis on a to-be-evaluated structure by using a finite element analysis method to obtain nonlinear structure seismic response corresponding to the to-be-evaluated structure and the acceleration time-history sample; establishing a change relationship between the statistical parameters of the seismic response of the nonlinear structure and the preset magnitude, distance and site conditions by using a regression fitting method; and constructing a vulnerability curved surface of a to-be-evaluated structure based on the preset earthquake magnitude, distance and site conditions based on the statistical parameters of the seismic response of the nonlinear structure and the change relationship between the preset earthquake magnitude, distance and site conditions. According to the embodiment of the invention, the four elements of a seismic source, a propagation path, a site and a structure can be completely coupled, and the method can be suitable for earthquake disaster risk analysis and rapid evaluation of post-earthquake disasters under various medium-short period structure systems.

The invention discloses a post-disaster recovery large-scale city power grid toughness evaluation method, device and medium, and the method comprises the steps: constructing a large-scale city power grid fault scene and a power transmission line time-varying fault probability model under an earthquake disaster, generating an earthquake-fault combined scene based on Monte Carlo simulation, and selecting k high-risk typical scenes, and then, by taking the maximum weighted load recovery total amount in the system full recovery period as a core optimization target, constructing a power grid post-disaster collaborative recovery model, constructing a multi-dimensional dynamic toughness index system based on the grid robustness, the system self-healing capability and the post-disaster first-aid repair capability, and evaluating the large-scale urban power grid toughness level of power grid post-disaster collaborative recovery. And outputting a good and bad sequence of the optimization strategy. By evaluating the toughness level of the large-scale urban power grid subjected to post-disaster collaborative recovery of the power grid, the performance of the whole recovery process can be comprehensively quantified, the advantages and disadvantages of strategies can be effectively distinguished, and the recovery speed and the recovery degree can be accurately quantified, so that an effective recovery strategy cannot be adopted, and a reliable basis is provided for disaster prevention and emergency of the power grid.

The invention provides a stratified rock mass cavern group earthquake safety toughness evaluation method and system, and the method comprises the steps: obtaining a geological parameter set and an earthquake motion parameter set based on geological exploration data and numerical simulation data; constructing a three-dimensional geological structure model according to the geological parameters, and generating a seismic oscillation input time history curve; inputting the seismic oscillation input time history curve into the model, and obtaining a seismic dynamic response data set through a dynamic response calculation algorithm; calculating a safety state index of each cavern in combination with a safety threshold judgment rule; and on the basis of the safety state indexes, generating an overall earthquake safety toughness evaluation result through an earthquake toughness quantitative model. According to the method, the earthquake safety toughness of the stratified rock mass cavern group can be accurately evaluated, a scientific basis is provided for aseismic design and safety evaluation of the cavern group, and the earthquake disaster risk is effectively reduced.

The invention discloses an earthquake risk evaluation method and system, and relates to the technical field of earthquake numerical simulation, and the method comprises the steps: receiving a three-dimensional geometric model of a grid fault, and setting an initial condition; constructing a simulation operation equation to solve a shear stress loading rate, a normal stress loading rate and a state variable, and constructing an ordinary differential equation system; based on the three-dimensional geometric model and the initial conditions, accelerated simulation operation of the shear stress loading rate, the normal stress loading rate and the state variables is achieved through the ordinary differential equation system, and the accelerated simulation operation method comprises the steps that accelerated simulation operation is achieved through the method of combining an H-matrix and MPI, comprising the steps that a layered matrix is obtained based on a Green function under the half-space condition in combination with an adaptive cross-approximation algorithm, the layered matrix comprises a normal stiffness H-matrix and a shear stiffness H-matrix, and MPI parallel operation matrix-vector multiplication is adopted. According to the invention, the hierarchical matrix is introduced and the MPI parallel computing framework is fused, so that the simulation period is greatly shortened.

The invention belongs to the technical field of earthquake disaster building detection, and particularly discloses an earthquake building damage degree detection method and system based on multi-modal sensor data fusion. Multi-modal sensor equipment is used for collecting multi-dimensional data, and signal preprocessing is performed on the sensor data; a data fusion module is used to enhance the feature representation capability, finally a detection model is constructed based on an improved YOLOv11 algorithm, a data set is used to train the model, and a final earthquake building damage degree detection model is obtained, and the model can detect and evaluate the damage degree of the building in real time. And results are divided into four grades: intact damage, slight damage, major damage and complete damage. The method can be used for rapidly extracting building damage information so as to assist rescue decision making and post-disaster reconstruction work.

The invention discloses an emergency rescue path planning method, system and device based on building earthquake damage simulation and a medium, and relates to the field of rescue path planning, and the method comprises the steps: building a building three-dimensional structure based on a two-dimensional plane graph of a building with an earthquake disaster; processing the three-dimensional structure of the building by adopting a physical engine to obtain a building damage and pavement accumulation result under an earthquake; performing indoor and outdoor integrated road network extraction on building damage and pavement accumulation results under an earthquake by adopting a navigation grid method to obtain a road network extraction result; and performing path planning based on the road network extraction result by adopting an optimized A * algorithm to obtain an emergency rescue path planning result. According to the method, the requirements of evacuation safety, trafficability and traffic capacity constraint and strain can be met, and indoor and outdoor integrated path planning service is provided for search and rescue personnel so as to respond to the optimal rescue path requirement of emergency.

The invention discloses an equipment attitude automatic correction method and device and an optical terminal intensity instrument, the equipment attitude automatic correction method is applied to a preset monitoring terminal comprising a triaxial MEMS accelerometer and a magnetometer, and the method comprises the following steps: collecting acceleration and magnetometer data; calculating acceleration stable three-axis offset; calculating roll and pitch angles and determining a horizontal plane; positioning magnetic north and calculating a magnetic north azimuth angle; calculating a magnetic declination angle and a yaw angle by combining longitude and latitude; generating a rotation matrix and converting a coordinate system; judging angle change and updating the matrix; and completing calibration and attitude stabilization. According to the technical scheme provided by the invention, the monitoring terminal equipment can be ensured to automatically and accurately adjust and stably maintain the attitude after being installed, so that the effective operation of the earthquake monitoring and early warning system is ensured, and the earthquake disaster prevention and flooding earthquake (vibration) monitoring performance is improved.

The invention discloses an urban heat supply pipe network emergency knowledge graph construction method and system, and relates to the technical field of emergency knowledge graph data processing. The method comprises the following steps: collecting emergency knowledge original data of the urban heat supply pipe network; constructing an emergency knowledge graph basic model of the urban heat supply pipe network; and real-time earthquake disaster information is obtained, if the emergency earthquake information is not updated, adjustment is not carried out, and if the emergency earthquake information is updated, the urban heat supply pipe network emergency knowledge map basic model is reconstructed according to the updated emergency earthquake information, and a real-time urban heat supply pipe network earthquake emergency knowledge map is obtained. According to the method, the city heat supply pipe network emergency knowledge graph construction method is optimized according to the disaster model construction contrastive analysis result, so that the effect of improving the adaptability of city heat supply pipe network emergency knowledge graph construction to external disaster changes is achieved; the problem that in the prior art, the adaptability of urban heat supply pipe network emergency knowledge graph construction to external disaster changes is insufficient is solved.

The invention relates to the technical field of large language models, in particular to a large language model anti-seismic report examination method and device based on domain knowledge enhancement, and provides a large language model anti-seismic report examination method based on domain knowledge enhancement. The method comprises the steps that firstly, a building earthquake-proof professional field large language model is trained, then data preprocessing is conducted on an earthquake-proof examination report, and finally examination is conducted on the basis of the trained building earthquake-proof professional field large language model, so that accumulated earthquake-proof special examination experience and the large language model are fused, and a professional LLM of the vertical field is built; strict examination can be carried out according to standards and files, interference of human errors and subjective factors is effectively avoided, accuracy and reliability of examination results are improved, examination efficiency is improved, a more scientific and accurate basis is provided for expert examination and internal pre-examination, the earthquake resistance and disaster prevention capacity of a construction project is further improved, and the earthquake disaster risk is reduced.

The application discloses a correction method and device of a seismic disaster personnel casualty assessment model and a storage medium, and relates to the technical field of disaster emergency management. By constructing an emergency preparedness index and an emergency response index as a nonlinear attenuation correction factor, the traditional assessment model's defects of relying on expert experience for manual correction and lacking in automation and intelligence are overcome. The coupling correction formula takes the nonlinear attenuation correction factor as the core, and through the multiplication coupling of independent double indexes, the synergistic attenuation effect of emergency preparedness and emergency response is accurately reflected. Through a closed-loop optimization mechanism, highly reliable data support is provided for emergency command. The correction process not only outputs personnel casualty prediction values, but also quantitatively diagnoses regional resilience by generating an emergency preparedness index and an emergency response index, so that emergency plans can be optimized, rescue force deployment can be adjusted or popular science drills can be strengthened, thereby directly serving the active prevention and control and rapid recovery goals of a resilient city.

The invention discloses an earthquake numerical value prediction method based on kernel density and machine learning, and belongs to the technical field of earthquake prediction. The method comprises the steps of performing magnitude standardization and energy association processing on original seismic directory data to form standard seismic directory data, performing completeness processing on the standard seismic directory data to determine a minimum complete magnitude, and performing screening to obtain a complete seismic directory; determining a first bandwidth and a second bandwidth for the complete seismic directory through a nuclear density bandwidth sensitivity test, calculating seismic frequency and energy nuclear density distribution of the target area in combination with a time and magnitude sliding window, and obtaining nuclear density anomaly distribution data by making a difference between the seismic frequency and energy nuclear density distribution and long-term average nuclear density distribution; and inputting the kernel density abnormal distribution data of the target magnitude range under multiple time scales into a pre-trained random forest model, and outputting an occurrence prediction result of a target magnitude earthquake in the target region. According to the method, the spatial accuracy and timeliness of earthquake prediction are improved, and technical support is provided for earthquake disaster risk prevention and control.

This invention discloses an automatic attitude correction method, device, and optical terminal intensity meter for equipment. The automatic attitude correction method is applied to a pre-set monitoring terminal including a triaxial MEMS accelerometer and a magnetometer, and includes the following steps: acquiring acceleration and magnetometer data; calculating acceleration-stabilized triaxial offset; calculating roll and pitch angles and determining the horizontal plane; locating magnetic north and calculating the magnetic north azimuth; calculating magnetic declination and yaw angle using latitude and longitude; generating a rotation matrix and performing coordinate system transformation; judging angle changes and updating the matrix; and completing calibration and attitude stabilization. The technical solution provided by this invention ensures that the monitoring terminal equipment can automatically and accurately adjust and maintain its attitude after installation, thereby guaranteeing the effective operation of the earthquake monitoring and early warning system and improving earthquake disaster prevention and seismic monitoring capabilities.

The invention provides an engineering machinery man-machine cooperative scheduling system and method applied to an earthquake disaster site, and relates to the technical field of man-machine cooperative scheduling, and the system comprises a site environment information obtaining module which is used for obtaining the site environment information of the earthquake disaster site; the rasterization processing module is used for performing area rasterization processing to generate a disaster area grid map; the task execution list generation module is used for performing task allocation evaluation, generating a rescue task execution list and extracting a primary task and a secondary task; the path planning module is used for performing path planning and generating a first rescue path and a second rescue path; and the collaborative rescue scheduling module is used for carrying out collaborative rescue scheduling on earthquake disasters. The technical problems that in the prior art, due to the fact that an effective man-machine cooperative scheduling mechanism is lacked, the collaboration between rescue workers and engineering machinery is poor, rescue resources are wasted, and the rescue efficiency is low are solved.

The utility model discloses an operating table for simulating earthquake disasters, which comprises an earthquake simulation vibration table, a house model is arranged at the top of the earthquake simulation vibration table, a support column is fixedly mounted at the bottom of the earthquake simulation vibration table, the bottom of the support column is connected with a bottom support plate, the house model is composed of a plurality of floors, and the floors are connected with the house model. A bridging plate is fixedly mounted at the bottom of the floor, and the earthquake disaster simulation device relates to the technical field of earthquake disaster simulation, a house model is arranged on an earthquake simulation vibration table, and earthquake waves are simulated and emitted through a simulation earthquake signal generator in the earthquake simulation vibration table, so that the disaster condition of the house model under an earthquake can be simulated; a plurality of dampers are jointly hinged between the floors, so that the different floors have corresponding swing amplitudes and directions during earthquake simulation, and the disaster conditions of the floors with different heights can be simulated.

This invention relates to the field of earthquake disaster emergency monitoring technology, specifically to an intelligent system and method for identifying earthquake surface rupture zones. The system includes modules for heterogeneous data registration, feature extraction and fusion, rupture zone segmentation, active learning, and morphological optimization. It achieves accurate processing of remote sensing data and intelligent identification of rupture zones. The system employs multi-scale feature point matching and adaptive weight registration, improving data registration accuracy by over 30% and overcoming the reliance on human experience in traditional methods. Through multi-modal feature decoupling and attention-guided feature fusion, combined with multi-scale spatial pyramid pooling and deformation-sensitive segmentation, the system effectively identifies rupture zones and assesses prediction uncertainty. The active learning module optimizes training data through Bayesian estimation and a hybrid sampling strategy, while the morphological optimization module utilizes geological constraints and fault topology inference to ultimately output accurate rupture zone distribution and attribute information, improving the intelligence level and efficiency of earthquake disaster emergency monitoring.

The application belongs to the technical field of earthquake disaster scenario construction, and discloses a method for constructing an earthquake disaster scenario based on big data, and the specific steps are as follows: step one: multi-source heterogeneous data acquisition and preprocessing ground structure data acquisition: the spatial distribution characteristics of urban building groups are obtained by using multi-platform remote sensing technology. By integrating multi-source data, a three-dimensional coupling model of underground pipe network and ground building is constructed, the defects of isolated analysis of ground and underground systems in traditional methods are solved, the synchronous simulation of the dynamic correlation process of pipe network rupture and building damage is realized, the additional influence of pipe network failure on building foundation stability and the chain effect of soil erosion caused by leakage fluid are accurately analyzed, and the space-time correlation rules of pipe network rupture events, building fire, fire fighting failure and other types of secondary disasters are established, the building group function paralysis risk and disaster diffusion range under different damage degrees are dynamically predicted, and the disaster evolution path is displayed in real time through a visual platform.

The invention specifically discloses an optimal selection method for a seismic oscillation intensity index of an underground diaphragm wall-subway station system, and relates to the technical field of underground structure anti-seismic performance evaluation. The method comprises the following steps: constructing a diaphragm wall-subway station two-dimensional nonlinear finite element model; obtaining an engineering demand parameter EDP through nonlinear time-history analysis, calculating a candidate seismic oscillation intensity index set IMs, forming an original database of IMs and EDP, and dividing a training set and a test set; generating an optimal candidate IM combination on the training set by using a filtering method, an embedding method and a wrapping method; building a multi-model verification platform, and evaluating the generalization performance of each combination based on a model-independent evaluation standard; comprehensively analyzing and determining the combination of the optimal scalar IM and the optimal vector IM; and verifying the whole optimization method through vulnerability analysis. According to the method, the limitation of a traditional method is broken through, the accuracy of earthquake resistance evaluation is improved, the adaptability of the method is defined, and reliable technical support is provided for earthquake disaster prediction and vulnerability analysis.