101 results about "Response analysis" patented technology

The invention discloses a multi-dimensional natural resource intelligent monitoring method and system based on big data analysis, and relates to the technical field of resource monitoring, and the method comprises the steps: calculating the information sharing degree between different data streams, constructing an abnormal feature credibility distribution map, and carrying out the calculation of the abnormal feature credibility distribution map; and inputting the abnormal feature credibility distribution graph and the multi-source auxiliary information into an integrated classifier, carrying out joint analysis and comprehensive research and judgment on multi-dimensional information to output a target list, constructing an event response relation graph reflecting a monitoring task priority and an execution logic relation according to the attribute features of each element in the target list, and carrying out event response analysis on the monitoring task priority and the execution logic relation. Wherein each node represents a to-be-monitored target, an edge represents a dependency relationship between tasks, and an optimal monitoring execution path is planned for various intelligent monitoring carriers by using an improved A algorithm integrated with a multi-factor cost function. Through natural resource monitoring of multi-modal data interference correction, intelligent classification and path optimization and dynamic response, the monitoring quality and the execution efficiency are effectively improved.

The invention discloses a method for constructing an evaluation model for the influence of climate change on biodiversity, and particularly relates to the technical field of ecological modeling and climate response analysis. The method comprises the following steps: generating a high-resolution characteristic grid based on microclimate disturbance data and a remote sensing image, extracting ecological plaques and establishing a heterogeneity spatial index model, constructing a connectivity map and a coupling response path library, extracting a typical species response mode by using nonlinear dimension reduction and spectral clustering, and performing dynamic fitting in combination with biological survey data. And finally, generating a diversity attenuation trend prediction curve and a risk thermodynamic diagram, identifying a biodiversity collapse critical point and outputting an intervention priority, and the method can be widely applied to regional ecological early warning and protection planning.

The invention discloses a rock mass structural surface identification method and system based on adaptive neighborhood and multi-seed-point growth, and relates to the technical field of geotechnical engineering, geological exploration and mining engineering, and the method comprises the steps: carrying out the adaptive non-uniform downsampling of three-dimensional point cloud data based on local feature entropy; retaining key geometric features of the structural surface while compressing the data volume; fusing the normal vector and the local point cloud density to carry out multi-feature classification; an improved region growing algorithm supporting parallel growth of multiple seed points is adopted, and a structural surface is accurately recognized; automatically extracting occurrence, spacing, trace length and roughness parameters of each structural surface; performing full-automatic advantage grouping on the occurrence through a DP-DBSCAN hybrid clustering algorithm; and constructing a three-dimensional discrete fracture network model based on the statistical parameters, and integrating the three-dimensional discrete fracture network model to discrete element software for mechanical response analysis. According to the method, full-process automation of rock mass structural surface recognition is realized, and the processing efficiency, the recognition precision and the engineering practicability are remarkably improved.

The invention belongs to the field of dam flood discharge safety, and provides a dam flood discharge safety protection method and system based on earthquake response analysis, and the method comprises the steps: S1, obtaining multi-source environment and structure data in real time; s2, preprocessing the multi-source environment and structure data to form a unified time sequence multi-dimensional data set; s3, simulating and analyzing the structural dynamic response of the dam and the flood discharge gate based on the unified time sequence multi-dimensional data set, and evaluating potential damage; s4, comprehensive risk assessment is carried out by combining the earthquake response analysis and damage assessment result, the hydro meteorological data and the flood discharge gate operation state data, and early warning information is generated; s5, generating a dynamically adaptive flood discharge gate opening and closing strategy according to the comprehensive risk assessment result and the early warning information; s6, executing the opening and closing strategy of the flood discharge gate, and monitoring the actual operation state of the flood discharge gate in real time; and carrying out comparative analysis on the actual running state of the flood discharge gate and the prediction strategy, and carrying out updating and optimization according to an analysis result.

The invention discloses a real-time monitoring control system based on a thermal flow sensor and a controller, and relates to the technical field of sensor monitoring. According to the real-time monitoring control system based on the thermal flow sensor and the controller, the method comprises the steps that S1, sensor monitoring data and historical statistical data are preprocessed; s2, lagging and response time dynamic characteristics are extracted; performing modal decomposition, phase estimation, peak calculation and steady-state noise analysis; s3, executing phase compensation, peak value recovery and enhancement compensation judgment; recording a residual sequence and a compensation parameter, and outputting optimized flow data; s4, constructing a credibility interval and dynamic consistency score synthesis control credibility mark; and executing security constraint and prediction filtering and archiving. The problems that an existing thermal flow sensor generates obvious phase lag and peak smoothing distortion due to the influence of thermal diffusion thermal inertia under the rapid fluctuation and pulsation working conditions, and the real-time monitoring precision and the closed-loop control stability are difficult to guarantee due to the lack of an online dynamic response analysis and compensation mechanism are solved.

The invention relates to the field of vulnerability evaluation of extreme rainfall induced mass landslide, in particular to an extreme rainfall mass landslide vulnerability evaluation method fusing diffusion generation and interpretable learning, which comprises the following steps: firstly, constructing a multi-dimensional factor data set, and realizing rasterization preprocessing; secondly, establishing a feature response analysis module, identifying main control factors of landslide occurrence and eliminating redundant variables; then, a denoising diffusion probability model is introduced, and an enhanced balance sample library is constructed; then, carrying out landslide probability prediction based on a multi-algorithm fusion integrated discrimination model, and outputting a grid-level landslide occurrence probability; and finally, minimizing intra-class variance and maximizing inter-class variance by using a natural breakpoint method, determining an optimal grading threshold set, and realizing landslide susceptibility grade division and spatial mapping output. Under the extreme rainfall condition, the method can effectively characterize the susceptibility zoning influence of the mass-occurring landslide flow slip catastrophe process, and achieves high-precision landslide susceptibility evaluation.

The invention relates to a data processing technology, and provides a mass distribution network industrial resource collaboration method based on load interaction and response analysis, which comprises the following steps: firstly, constructing a real-time synchronous data acquisition and processing system, and fusing multi-source data to form a unified data base; secondly, realizing flexible dynamic identification through mechanism modeling and data driving, and introducing a flexible label to quantify adjustable power, duration and response rate; constructing an interactive network based on the flexibility label, depicting a space-time coupling effect and group response characteristics, and generating an equipment, station and region level scheduling scheme through a multi-target hierarchical optimization model in combination with market electricity price and renewable output prediction; and finally, comparing the plan with the actual response in the actual scene, and performing correction. According to the invention, the cooperative scheduling and fine management capability of the power distribution network on massive industrial loads can be improved, the flexible utilization level is improved, and the economical efficiency and robustness of the system are enhanced.

The application relates to the field of extreme rainfall-induced group landslide susceptibility evaluation, in particular to an extreme rainfall group landslide susceptibility evaluation method fusing diffusion generation and explainable learning, which comprises the following steps: firstly, a multidimensional factor dataset is constructed to realize grid pretreatment; secondly, a feature response analysis module is established to identify main control factors of landslide occurrence and remove redundant variables; then, a denoising diffusion probability model is introduced to construct an enhanced balanced sample library; next, a landslide probability prediction is carried out based on an integrated discriminant model of multi-algorithm fusion, and a grid-level landslide occurrence probability is output; finally, the natural breakpoint method is used to minimize intra-class variance and maximize inter-class variance, so that an optimal grading threshold set is determined, and landslide susceptibility grading and spatial mapping output are realized. Under the condition of extreme rainfall, the application can effectively represent the susceptibility partition influence of group landslide flow slide catastrophe process and realize high-precision landslide susceptibility evaluation.

The application provides a communication feature model driven relay protection device automatic test method and system, comprising the following steps: 1. Through active detection and response analysis, the communication protocol type, message format and function code mapping relationship of the relay protection device are identified, and a device communication feature model is constructed; 2. Based on the device communication feature model, test cases covering function verification, abnormal processing and boundary conditions are dynamically generated, and automatic mapping of the test cases and the device and execution sequence optimization are completed. The technical scheme can solve the problems of relay protection device test dependence on manual configuration, low efficiency and poor adaptability.

This invention provides a peak-scale response analysis method based on nested sub-basin division. By constructing a nested sub-basin structure controlled by area thresholds, and based on a unified design storm conditions and hydrological model parameter system, the method calculates peak discharge under different scale conditions by only changing the sub-basin division scale. It also establishes a logarithmic decay function model between peak discharge and the number of sub-basin units, achieving a quantitative expression of peak-scale response. Furthermore, by comparing and analyzing the scale decay coefficients under different design frequencies, the method quantifies the sensitivity of peak discharge to changes in the division scale. This method forms a complete technical process from data acquisition, structure construction, control variable setting, model running to function modeling and sensitivity analysis. It features a clear logical closed loop, strong repeatability, and good generalization, and does not depend on specific hydrological model software or specific watershed conditions. Under the premise of meeting the unified storm input and nested division principles, it can be widely applied.

The application provides a triaxial six-direction impact test simulation method and system based on F-DEM, the triaxial six-direction impact test simulation method based on F-DEM comprises a full-size model frame establishing step, an F-DEM coupling step, a model dynamic solving step and an automatic data post-processing step, and the application also provides a triaxial six-direction impact test simulation system based on F-DEM, a three-dimensional full-scale numerical model is established based on the basic parameters of a waveguide rod and a rock sample in a TEHB test system, and the three-dimensional full-scale numerical model comprises a discrete element rock sample model and a finite element waveguide rod model. The application realizes efficient coupling modeling of the finite element waveguide rod and the discrete element rock sample, has good stress wave propagation accuracy, can accurately simulate the dynamic response behavior of the rock sample under triaxial six-direction loading, and provides efficient and verifiable technical support for impact response analysis and engineering application research of rock mass in a complex stress environment.

The invention provides an interaction method, an interaction device, an intelligent agent, equipment, a medium and a program product, and relates to the technical field of artificial intelligence, in particular to the technical field of man-machine interaction, computer vision and voice. According to the specific implementation scheme, in response to received multi-modal information input by a target object to a virtual object, intention recognition is conducted on the multi-modal information, and text information representing the intention of the current round is determined; based on the text information and historical visual perception information crossing time domains with the text information, response analysis is carried out, response information is obtained, and the historical visual perception information is obtained by carrying out visual perception on historical multi-modal information input by the target object in historical rounds; and broadcasting the response information through the virtual object.

To provide a torsion response prediction method and a torsion response prediction device capable of easily evaluating torsion response caused by foundation input motion of a building located on irregular ground.SOLUTION: Calculating respective impedance ratios α γ = (γ 1 * Vs1) / (γ 2 * Vs2) of the stratum structures 1 and 2, where Vs1 and Vs2 are respective shear wave velocities of the stratum structures 1 and 2, and γ 1 and γ 2 are respective wet densities of the stratum structures 1 and 2, and calculating an area ratio β = A1 / (A2 + 2A1) from respective basic cross-sectional areas A1 and A2 of the stratum structures 1 and 2; A response analysis of a one dimensional soil column model is performed with respect to each of the layer structures 1 and 2, maximum displacements D1 and D2 of the grounds of the layer structures 1 and 2 are calculated, a difference in ground displacement Δ D = D1 - D2 is obtained, and a rotation angle θ max of the building caused by a base input motion is calculated using the following equation θ max = = p * (Δ D·L) q·α γ / β using preset coefficients p and q with a base length L of the building.SELECTED DRAWING: Figure 2

The invention provides a transformer transportation impact damage assessment method based on a damage response surface model. According to the method, refined impact excitation is constructed, and impact simulation is carried out on a finite element model of the transformer by utilizing the impact excitation. In the simulation process, the vibration response of the finite element model is collected, the damage conditions of different parts of the finite element model are subjected to harmonic response analysis, and damage point data of the part which is damaged first is selected to construct a damage response surface model. And multi-modal influence factors of impact acceleration and impact frequency are introduced into the damage response surface model, so that the damage response surface model can accurately describe the boundary of damage of the transformer under impact. By using the damage response surface model, the damage risk in the transformer transportation process can be accurately and effectively evaluated.

This invention provides an analytical method for a two-zone frequency full response model considering nonlinear elements, belonging to the field of analytical analysis of power system frequency response. First, considering the influence of nonlinear elements, a single-machine frequency full response model considering nonlinear elements is established. A piecewise modeling method for nonlinear elements and a full response analysis theory are proposed to achieve analytical analysis. Second, considering the influence of frequency spatiotemporal distribution characteristics, a two-zone equivalent frequency response model is established. An analytical method based on the model's vibration equation is proposed to achieve analytical analysis of regional frequencies. Finally, a two-zone frequency full response model considering nonlinear elements is established to achieve dynamic analytical characterization of the system's frequency response. This invention improves the accuracy of the model's description of the dynamic frequency characteristics of power systems after large disturbances, providing a new approach to solving the frequency security problem of power systems under the coupled influence of nonlinear elements and frequency spatiotemporal distribution characteristics, and contributing to the safe and stable operation of power systems.

The invention discloses a calcium carbonate processing quality on-line intelligent detection and control method, and particularly relates to the technical field of material processing quality control, and the method comprises the following steps: obtaining real-time quality parameter data in a calcium carbonate processing process, carrying out fluctuation analysis in a preset time window, judging whether to trigger a process adjustment response analysis mechanism or not, and if yes, judging whether the process adjustment response analysis mechanism is triggered or not; extracting a response feature group and an adjustment feature group in the current process adjustment process, respectively performing response analysis and adjustment analysis, then inputting the response feature group and the adjustment feature group into a pre-trained machine learning model, dividing calcium carbonate processing quality detection types under a current time window, performing feedback adjustment on calcium carbonate processing quality anomaly detection, and finally obtaining a calcium carbonate processing quality detection result. The calcium carbonate processing quality control effect is optimized; according to the method, automatic judgment of height adjustment response and low adjustment response is realized by dynamically evaluating the response capability and the adjustment effect of the system, so that the quality parameter detection standard interval is dynamically adjusted, and misjudgment and excessive adjustment are avoided.

The invention particularly relates to random response analysis of a wake flow type hybrid energy collector under fluctuating wind excitation, which comprises the following steps: on the basis of a simplified model that a static upstream bluff body is arranged in front of a main bluff body, and periodic vortex shedding wake flow force is utilized to excite vibration, establishing an equivalent electromechanical coupling dynamic model; a random phase is introduced into wake-induced vibration external excitation to represent random fluctuation of wake force under the fluctuating wind; after dimensionless and parameter scale re-calibration are carried out on the model, a multi-scale method is adopted to derive an amplitude-phase slow modulation equation set and first-order asymptotic analysis response expressions of displacement, voltage and current; further linearizing the slow-varying equation under a steady-state condition, solving a second-order statistic of amplitude and phase by combining a moment method and an Ischi differential rule, and determining steady-state moments of the output voltage and the output current and average output power according to the second-order statistic; and the output performance rapid evaluation and parameter design support of the wake flow type hybrid energy collector under random excitation are realized.

This invention discloses a rapid evaluation method for the enhancement factor of the dynamic coefficient by the high-frequency component of a strong impact load, belonging to the field of structural dynamic response analysis technology. This method performs time-frequency domain energy accumulation analysis on the strong impact load signal, extracts the concentrated frequency of load energy and its proportion in the total energy, and then, based on this, combines the dynamic amplification factor under the triangular time history assumption to quantitatively calculate the enhancement factor of the dynamic coefficient by the high-frequency component of the strong impact load. This method is further extended to arbitrary frequency components and the entire frequency band to obtain the comprehensive enhancement result of the dynamic amplification factor by the high-frequency effect of the strong impact load. Compared with traditional dynamic analysis methods based solely on idealized time history assumptions, this invention can introduce the real time-frequency characteristics of strong impact loads while maintaining computational efficiency, effectively compensating for the insufficient consideration of high-frequency excitation effects. It is applicable to rapid dynamic response evaluation in engineering fields such as aerospace structures, high-frequency components, and precision equipment.

The invention relates to the technical field of electric power monitoring, in particular to an electric power monitoring system and method based on big data analysis, and the system comprises a synchronous action recognition module, an electrical response analysis module, a topology connection verification module, a jump path construction module and a key equipment recognition module. According to the method, the time sequence of the jump action is extracted, the synchronization relation with approximate time is identified, synchronous response analysis is carried out in combination with the proportion of current change and voltage fluctuation, a collaborative identification rule among multiple devices is established, and communication path information of each serial number in the topological structure is introduced; the method comprises the following steps of: selecting serial number combinations with structural integrity and sequence consistency, constructing a jump path chain with time sequence logic, counting the occurrence frequency and cross distribution characteristics of device serial numbers in paths, identifying key devices which repeatedly appear in multiple paths and have core connection effects, and determining whether the key devices appear in the paths or not; and clear tracing of an abnormal conduction path and accurate positioning of a high-risk node are realized.

This invention provides an organizational attribute analysis system and apparatus that analyze organizational attributes through changes in the biological responses of users participating in online sessions conducted within an organization. [Solution] The tissue attribute analysis device 100 includes a bio-response analysis unit 12 that analyzes changes in the user's bio-response for each online session of multiple organizations in which the same user participates, based on video images obtained of the user during an online session conducted by multiple users, and a tissue attribute analysis unit 13 that analyzes the attributes of the organization based on the changes in bio-response analyzed by the bio-response analysis unit 12 for each online session of multiple organizations. The device analyzes the bio-response of participants in online sessions conducted within an organization and analyzes the attributes of the organization based on the analysis results.

The invention relates to the technical field of artificial intelligence, and is used for solving the problems that an existing employee digital duplication system often neglects effective collection and analysis of task performance data of employees in a unit period and lacks a screening mechanism based on historical behaviors and task performance; the problems of high response delay, task omission and overtime completion of partial clones in task execution due to employees of a construction source are solved; the enterprise-level employee digital duplication system based on artificial intelligence comprises a server, and the server is further connected with a data acquisition module, a difficulty judgment module, a response analysis module, a reliability analysis module, a planning module and an effect verification module. Quantitative analysis is carried out through the process complexity, the employee response timeliness and the task reliability degree, and the intelligence and the accuracy of the digital duplication system are improved in combination with a judgment rule and an interval classification mechanism.

The techniques herein include an inquiry controller determining whether timing criteria have been met for sending an inquiry to a particular user account. In response to determining that the timing criteria for sending an inquiry to the particular user account is satisfied, the inquiry is sent to and received by a particular user device associated with the particular user account. When a response is received, a response analyzer analyzes it and selects a first follow-up action, with associated first digital content, for the system to perform for the particular user account based on the analysis. The chosen action may include automatically creating a calendar item in a digital calendar associated with the user account, updating a digital task list for the user account, generating and transmitting a second inquiry to the particular user device, and the like. The follow-up action is then performed.

The present application relates to a kind of residual agricultural film water pollution prediction methods based on time delay embedding timing recursive network, comprising the following steps: S1: regional multi-source data acquisition and dataset construction, provide input data for prediction model;S2: build timing recursive prediction model, based on the timing recursive of multilayer gate control cycle unit GRU and time delay embedding mechanism builds prediction model, establishes the dynamic transmission relationship between residual agricultural film, soil characteristics and water pollution three kinds of medium;S3: pollution transmission chain construction and dynamic prediction, in prediction model, introduce intermediary variable and environmental driving factor, build from residual agricultural film to soil characteristics, again to water pollution, realize the dynamic prediction and response analysis of pollution process.The present application can show the time lag relationship between pollution release and water quality response, simulate the timing recursive process of residual agricultural film pollution between multiple media, provide reliable technical support for water pollution risk early warning and management decision.

The invention relates to a concrete structure fiber unit thermal-mechanical coupling response analysis method and system. Firstly, a fiber unit numerical model of a concrete structure is established according to a required analysis structure; secondly, creating a concrete section heat transfer analysis object, and calculating and outputting section temperature field data based on the concrete section heat transfer analysis object; then carrying out stress or disaster working condition simulation processing on the fiber unit numerical model of the concrete structure to obtain a processed fiber unit numerical model; finally, section temperature field data are read and mapped to the processed fiber unit numerical model, coupling calculation of a temperature field and a mechanical field is carried out, and a thermal-mechanical coupling response analysis result of the concrete structure is obtained and output. Compared with the prior art, the method has the advantages of high precision, high efficiency and the like.

The invention discloses a site differentiation earthquake response analysis method and system based on earthquake motion types, and belongs to the technical field of building earthquake-proof engineering, and the method comprises the steps: dividing a target site into three types of sites according to the obtained drilling information of the target site, and constructing a site model corresponding to each type of site; respectively calculating dynamic response results of each site model under the near-field pulse type seismic motion and the near-field non-pulse type seismic motion by adopting a time domain nonlinear analysis method; generating two groups of surface response spectrum amplification coefficients according to the dynamic response result of each site model, and comparing peak values with periods; and according to a comparison result of the peak value and the period, combining each site model to obtain a differential earthquake response analysis result. According to the method, the significant amplification effect of pulse type seismic oscillation on a soft soil site and the significant amplification effect of non-pulse type seismic oscillation on a medium-hard soil site are effectively revealed, and the problem that the difference of seismic oscillation types is not fully considered in existing analysis is solved.

The invention provides a topiramate cleaning chemical residue detection method and kit.The method comprises the steps that sampling is conducted in a specified area to obtain a sample, and the sampling step comprises wiping sampling and / or washing sampling; the method comprises the following steps: adding a mixed extraction solvent into a sample for extraction, filtering an extraction solution, adjusting the extraction solution to alkalescence, and adding a derivatization reagent for reaction to obtain a purified solution to be detected; the purified liquid to be detected is injected into a chromatographic detection system for quantitative detection, a detection result is output, and the detection step comprises chromatographic separation and signal response analysis. Accurate detection and limit judgment on topiramate residues on the surface of equipment are realized through standard sampling, extraction purification and derivatization enhanced response and in combination with chromatographic quantitative analysis, so that collinear production pollution and cross contamination risks of medicines are effectively controlled.

This invention relates to a method for diagnosing error sources in the manufacturing process of precision micro-connector molds. Addressing the challenge of integrating multi-source heterogeneous detection data and attributing errors during the manufacturing process, it proposes a method based on semantic fingerprint extraction and incremental fusion of knowledge graphs driven by multi-source raw data. Through industrial Ethernet, dedicated communication protocols, and optical character recognition, data from CNC machining, coordinate measuring machine (CMM), electrical discharge machining (EDM), and maintenance fault logs are collected in real time, and data feature compression, geometric fingerprinting, material response analysis, and semantic phrase standardization are performed. The core solution automatically constructs and evolves a knowledge graph through low-dimensional semantic fingerprint spatial mapping and anchor point expansion mechanisms, enabling real-time location of manufacturing error sources and the formation of causal chain attribution reasoning. This method achieves dynamic identification and ontology fusion of novel error patterns, improving the efficiency of anomaly diagnosis and the self-evolutionary capability of knowledge in the mold manufacturing process.

The application discloses a kind of geometric nonlinear equivalent plate dynamics modeling and response analysis method of truss structure, its implementation steps are: for the truss structure containing geometric nonlinearity, first, construct linear equivalent Mindlin plate dynamics model;Then describe the geometric constraint relationship of Mindlin plate, carry out displacement and angle approximation and simulate general elastic boundary condition;Finally, according to the extended Hamilton principle, establish the equivalent plate dynamics model containing geometric nonlinearity, and carry out nonlinear dynamic response analysis.The application overcomes the defect that the installation position characteristics of distribution hinge in the width direction of cross section is not considered in the traditional equivalent beam model, and is suitable for geometric nonlinear large deformation analysis;It is suitable for truss structure with general boundary conditions, and has strong engineering applicability;The equivalent nonlinear model established by semi-analytical method is more efficient than traditional finite element numerical algorithm, and is more suitable for dynamic analysis and control law design.

This provides information that helps optimize the placement and type of dampers, as well as the skeleton curve of the main frame. [Solution] The design support device receives skeleton setting information indicating a first skeleton curve and a second skeleton curve that define the range of the skeleton curve of the main frame in the building to be designed, and receives damper setting information indicating a plurality of placement patterns in which the placement quantity patterns of dampers that can be selected from a plurality of types and placed in the building are each different, and calculates the cost for the main frame and the dampers for a plurality of sets, each consisting of one skeleton curve that is included in the range and one placement pattern that is included in the plurality of placement patterns, performs a response analysis of the mass point system model of the building for the plurality of sets, and displays each of the plurality of sets in correspondence with the cost and the result of the response analysis.

The application provides a plastic damage trigger adaptive model reduction method.The method realizes nonlinear seismic response analysis of a large complex structure,adopts a modal analysis method for a linear substructure,compared with a traditional finite element method,significantly reduces the calculation requirement and improves the calculation efficiency; meanwhile,for a nonlinear substructure,an order reduction basis constructed by using a tangent stiffness based vibration mode and a constraint mode is used to reduce the degree of freedom,that is,calculation efficiency is further improved and the accuracy of a local nonlinear analysis result is ensured. In addition, the application is not limited to the large complex structure as the analysis object, and the same method can be used for dynamic response analysis of other types of structures.