436 results about "Calculation algorithm" patented technology

The invention discloses a large model prompt project optimization system and method fusing a domain knowledge graph. The system comprises an analysis module, a template generation engine module, a large model interaction interface module, a feedback analysis module and an optimization strategy module. And the analysis module forms a constraint coding signal containing an entity attribute incidence matrix. The template generation engine module forms an enhanced prompt text stream with a reservoir physical property parameter slot; the large model interaction interface module receives the enhanced prompt text stream and generates a question and answer response data stream containing geological terminologies; the feedback analysis module forms a feedback signal containing semantic deviation measurement through a semantic error vector calculation algorithm; and the optimization strategy module forms a parameter optimization instruction signal and transmits the parameter optimization instruction signal to the analysis module to complete iterative updating of the constraint condition. According to the large model prompt project optimization system fusing the domain knowledge graph, the problem of low answer accuracy of a large model in the oil-gas exploration field due to lack of professional constraints can be solved.

The invention discloses a three-dimensional model lightweight reconstruction and rendering method based on multi-strategy collaboration, and the method comprises the steps: 1, extracting geometric information, appearance information and semantic attribute information of a three-dimensional model, separating the geometric information from the appearance information and the semantic attribute information, and storing the semantic attribute information to a three-dimensional model database; 2, instantiating components with the same geometric structure in the three-dimensional model, realizing material sharing through a material reference mechanism, and reducing rendering overhead on the premise of not changing the structure of the model; step 3, carrying out lightweight processing on the exported geometric and appearance information to obtain reconstructed lightweight models with different precision grades; and 4, dynamically adjusting the geometric complexity of the lightweight model through the sight distance and the frame rate by using a hierarchical calculation algorithm for rendering, and meanwhile, obtaining component semantic attribute information and synthesizing the semantic attribute information by calling a three-dimensional model database interface to realize visual display of the reconstruction model.

A water and soil loss pattern spot landing system based on land utilization information weak constraint comprises a land utilization information acquisition module, a factor evaluation and analysis module, a time sequence analysis and pattern spot landing module and a data integration and visualization module. The factor evaluation and analysis module is used for calculating a water and soil loss erosion modulus and evaluating and analyzing influence factors, the time sequence analysis and pattern spot landing module is used for analyzing water and soil loss changes and generating landing pattern spots, and the data integration and visualization module is used for data integration and pattern spot visualization display. According to the water and soil loss pattern spot landing system based on the land utilization information weak constraint, an erosion modulus calculation algorithm based on data fusion and pixel unmixing is proposed to calculate an erosion modulus, and a water and soil loss pattern spot change analysis algorithm based on time sequence classification is proposed to analyze pattern spot change.

The invention discloses a privacy protection effect evaluation method and system, and the method comprises the steps: carrying out the hierarchical analysis of a privacy protection effect evaluation index system, defining the definition and calculation boundaries of four first-level dimensions, i.e., data features, compliance, availability and safety, and subordinate second-level indexes, carrying out the adaptation of a calculation algorithm for different types of indexes, and carrying out the weighted integration of the second-level indexes through employing an analytic hierarchy process, thereby achieving the evaluation of the privacy protection effect. Multi-dimensional quantitative evaluation is realized; an index association rule base and a matrix are constructed through static analysis and dynamic mining, and linkage analysis is achieved; determining an index fluctuation reference according to scene characteristics and historical data, converting user demands into a variation amplitude of a fluctuation reference unit, and realizing index dynamic linkage updating based on an incidence matrix; and finally, the optimization rule is verified through simulation testing and historical data backtracking, and a dynamically adaptive and self-iterative optimization relation rule system is formed, so that the limitation of traditional evaluation is broken through, a scientific basis is provided for privacy protection strategy optimization, and the privacy governance efficiency is improved.

The invention discloses a geotechnical engineering catastrophe dynamic real-time intelligent early warning method and system based on displacement monitoring, and the method comprises the steps: collecting the real-time displacement data and related parameters of a geotechnical engineering region through displacement monitoring equipment, and transmitting the real-time displacement data and related parameters to a bank slope stability evolution analysis platform to establish a multi-dimensional database; calling a fractured rock mass effective stress analysis model to calculate rock mass effective stress distribution characteristics, and inputting a multi-grid sliding surface stress calculation algorithm to obtain a potential sliding surface stress state and a critical threshold value; inputting the sliding surface stress parameters and the displacement data into a multi-field coupling analysis learning prediction model to obtain a displacement evolution trend and a catastrophe risk coefficient; and finally, real-time early warning information is generated and fed back through the catastrophe dynamic real-time intelligent early warning module. The method improves the real-time performance and accuracy of early warning, can effectively guarantee the safety of geotechnical engineering, and is suitable for catastrophe early warning scenes of geotechnical engineering such as bank slopes and foundation pits.

The invention discloses a multi-device collaborative passenger flow statistical method and system, and the method comprises the following steps: presetting a unique identity label and a physical position index for devices, reading the unique identity label and the physical position index, and initializing the attribute information of the devices; a user datagram protocol broadcasting mechanism is started, and heartbeat information including the unique identity label, the physical position index and the online state is sent according to a preset period; monitoring the user datagram protocol broadcast message in the local area network, constructing and maintaining an online equipment list, and updating the online state of the equipment according to the heartbeat information receiving analysis condition; judging adjacent equipment based on a physical location index, and deciding whether to start a first boundary or a second boundary according to the online state of the adjacent equipment; and the decision result is transmitted to a passenger flow statistical algorithm to generate a shop-crossing detection line. According to the invention, multi-device collaborative passenger flow statistics dynamic boundary configuration is realized, the shop-crossing detection line is accurately generated, and the passenger flow statistics problems of fixed boundary configuration, easy missed counting and poor multi-device collaboration are solved.

The invention discloses an industrial printer ink-jet control system based on negative feedback control, and relates to the technical field of industrial printers. The ink-jet control system for the industrial printer based on negative feedback control comprises a data input processing module which is responsible for receiving printing data input by a user, converting the printing data into a format which can be identified by the printer, and carrying out preliminary optimization and arrangement on the data at the same time; the data input processing module is connected with a high-speed data transmission module, and the high-speed data transmission module is connected with a sensor monitoring module, a feedback signal processing module, an optimization algorithm control module and a distributed local control module. The calculated amount can be reduced and the time required by deviation calculation can be shortened by simplifying the deviation calculation algorithm, and the deviation can be predicted and adjusted in advance by the predictive control algorithm, so that the system can quickly cope with the change of the ink jet state, and the printing efficiency and quality are improved.

The invention discloses a customer portrait analysis method and system based on a knowledge graph, and the method comprises the steps: S1, collecting a user behavior event flow and an external environment event flow, and generating a dynamic event signal carrying a timestamp based on a heterogeneous data source; s2, responding to a dynamic event signal, and analyzing an event type to trigger incremental updating operation; s3, in response to the real-time graph updating signal, updating the feature vector of the user node through an incremental graph calculation algorithm to generate a portrait updating signal; s4, generating a graph updating instruction and a portrait recalculation instruction to form a cooperative control signal; and S5, feeding back a graph updating instruction in the cooperative control signal to an incremental updating operation step, and feeding back a portrait recalculation instruction to a feature vector updating step to drive a real-time cooperative closed loop. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of client portrait hysteresis quality and low map-portrait cooperation efficiency can be solved.

The invention discloses an indoor research and development test platform for a multi-rotor unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle testing, the indoor research and development test platform comprises a test bench, a main control unit is arranged on the test bench, the main control unit is provided with a flight path resolving algorithm, and the test bench comprises a rectangular cubic frame. An annular outer ring is arranged in the rectangular cubic frame in a connected mode through a three-degree-of-freedom rotating shaft connecting piece and a frame body connecting plate, and an annular middle ring is arranged in the annular outer ring in a connected mode through a three-degree-of-freedom rotating shaft connecting piece and a ring connecting piece. The interior of the annular middle ring is connected with an annular inner ring and an annular outer ring which serve as unmanned aerial vehicle connecting plates through three-degree-of-freedom rotating shaft connecting pieces and fixing grooves, magnetic encoders are arranged on the middle ring and the inner ring, and meanwhile the cubic frame and the outer ring, the outer ring and the middle ring and the middle ring and the inner ring are connected through conductive sliding rings; according to the invention, an indoor unmanned aerial vehicle testing environment which is safe, reliable, accurate in data, simple to operate, friendly in interface, visual and efficient can be provided for users.

The invention provides a method and a device for generating a customized report of an SAAS (Software as a Service) system based on dynamic template configuration. The method comprises the following steps: acquiring a customized visual report template for realizing business data decoupling; editing the report template based on a preset editor, and generating a template configuration file; analyzing a structured marker in the template configuration file to generate a metadata description file; querying a business database through a unified data interface according to a data requirement defined by the metadata description file, and obtaining and assembling customized business data corresponding to the tenant ID; and at least based on the customized business data, controlling a rendering process through a dynamic position calculation algorithm, and dynamically filling the data to a corresponding position of the report template to generate a customized report. According to the method, the problems of code redundancy and difficulty in maintenance of the SAAS multi-tenant report are solved, zero code configuration is realized, and report generation efficiency and tenant personalized adaptation capability are improved.

The invention relates to a two-dimensional image and geometric constraint-based cargo stack three-dimensional pose detection method and device, which are applied to the technical field of computer vision and logistics automation, and comprises the following steps of: through an edge straight line screening strategy, combining robust fitting of a random sampling consistency algorithm, calculating a three-dimensional pose of a cargo stack; a real physical boundary can be effectively and accurately recognized from complex visual interference such as adhesive tape, labels and printed patterns on the surface of a container, the accuracy and robustness of edge detection are remarkably improved, and therefore the high precision of final three-dimensional pose calculation is guaranteed; and secondly, only a common industrial camera is needed, and an expensive three-dimensional sensor such as a laser radar or a depth camera is not needed, so that the hardware cost and the maintenance complexity of the system are greatly reduced, and the cost benefit is extremely high. And thirdly, an efficient image processing and geometric calculation algorithm is mainly adopted, the calculation complexity is low, and the requirement for real-time detection of the goods stack on an industrial automatic assembly line can be met.

The invention discloses a real-time data integration and analysis system based on cloud computing, particularly relates to the technical field of data analysis, and aims to solve the problems caused by insufficient real-time processing of multi-source and heterogeneous data and dynamic resource allocation in the prior art. Real-time data from different data sources are acquired and preprocessed through a real-time data acquisition module, and a real-time data analysis module performs windowing calculation and joint aggregation operation by using a distributed calculation algorithm to generate an intermediate analysis result; the tenant resource scheduling module evaluates the resource allocation equilibrium state of the computing node based on the intermediate analysis result, and dynamically adjusts the task scheduling strategy under the support of the task scheduling adjustment module; and finally, the analysis result extraction module further processes the intermediate analysis result to realize integration and efficient analysis of real-time data. The system has strong heterogeneous data processing capability, can optimize computing resource allocation in a multi-tenant environment, and ensures high-precision real-time data analysis and decision support.

The invention relates to the field of data query, and discloses a data aggregation query method and system based on time dimensionalities, the method comprises the following steps: obtaining a data aggregation query request, the data aggregation query request at least comprising a time index table of the time dimensionalities, the time dimensionalities being represented by at least one of year, month, day, hour and minute; analyzing the data aggregation query request, and determining an aggregation granularity, a date index value and an aggregation step length in a time index table; performing aggregation calculation according to the aggregation granularity, the date index value and the aggregation step length, and determining an aggregation date index; and performing field matching in a database through the aggregation date index, and performing grouping aggregation on matching results to determine a data query result. Indexes are added for different aggregation dimensions by creating a date index table, and an index calculation algorithm is combined, so that multiple time dimension query requirements are met, the data query speed can be remarkably increased, consumption of calculation resources is reduced, and the query flexibility is improved.

The invention discloses a rock shear seepage coupling true triaxial test system, which relates to the technical field of rock mechanical tests, and comprises a host, a sigma 1 / sigma 2 direction loading module, a sigma 3 direction confining pressure module, a pressure chamber auxiliary system, a sample clamp, a pore water seepage system, a temperature system, a control module and a data acquisition and processing module, through servo closed-loop linkage double-pump loading in the sigma 1 / sigma 2 direction, synchronous output of the double pumps and coordination of pressure supply of the two oil cylinders by the controller, a strain correction algorithm is combined, stability of a stress loading center is guaranteed, strain measurement accuracy is improved, confining pressure is accurately controlled in the sigma 3 direction through a double-balance pressure chamber and a pressure regulation algorithm, and the stress measurement accuracy is improved. The pressure chamber is in full-automatic operation, manual steps are omitted, errors are reduced, efficiency is improved, a stress-free blank angle clamp eliminates friction interference, a seepage system supports a double-loading mode, a control module achieves multi-control-mode impact-free switching, a data processing module is combined with an elastic modulus calculation algorithm, rock mechanical parameters are accurately obtained, and the multi-field coupling test requirement is met.

The invention discloses a mineral powder volume measuring and calculating method based on three-dimensional shape data analysis, and relates to the technical field of mineral powder volume measurement. The method comprises the following steps: carrying out mineral powder pile scanning based on a mineral powder pile scanning module, and collecting three-dimensional point cloud data; preprocessing the collected point cloud data based on a point cloud preprocessing module; reconstructing the preprocessed point cloud data by using a three-dimensional reconstruction algorithm based on a mineral powder three-dimensional structure model construction module; based on the volume calculation module, performing mineral powder volume calculation by using a volume calculation algorithm based on voxel representation; and analyzing a calculation result. The method has the beneficial effects that the method has high automation and accuracy, the automatic processing and analysis process reduces manual intervention, the measurement accuracy and reliability are improved, the deep learning algorithm is applied, the capability of data processing and complex structure analysis is optimized, the method is suitable for mineral powder of different shapes and sizes, and the method is suitable for large-scale popularization and application. The method can be popularized to other industries requiring accurate volume measurement and shape analysis.

According to the method for designing the reasonable arch axis of the large-span arch bridge based on the hybrid calculation algorithm and the self-adaptive load distribution, an analytic equation method, a curve fitting method and an intelligent optimization algorithm are combined, and by selecting the initial arch axis, introducing a dynamic load distribution model and applying a genetic algorithm and a particle swarm optimization algorithm, the reasonable arch axis of the large-span arch bridge is designed. Global and local optimization is carried out, and the optimal shape and load distribution of the arch axis are ensured. And finally outputting design parameters, such as a control point, a bending moment, thrust and the like. According to the method, the design precision, flexibility and safety can be effectively improved, the material utilization rate is optimized, the cost is reduced, and the method is particularly suitable for design of large-span bridges and has high practical value.

The invention discloses a land gravity far-area terrain correction method and system based on a digital elevation model. The method comprises the following steps of: performing weighted average calculation on a far first region terrain correction value and a far second region generalized terrain correction value of regular distribution measuring points near irregular distribution measuring points by adopting a bilinear interpolation algorithm on the irregular distribution measuring points to obtain a far region terrain correction value; on the basis of a calculation algorithm of a terrain unit gravitational potential vertical partial derivative of a local rectangular coordinate integral kernel of a measuring point under a spherical coordinate system, high-precision calculation and accumulation are carried out on terrain units one by one, the influence of earth surface bending is considered, and a high-precision and high-resolution digital elevation model can be utilized to the greatest extent. A high-precision digital elevation model represented by geographic latitude and longitude is uniformly subdivided for terrain interfaces of a far first area and a far second area, so that digital elevation units with different resolutions are ensured not to be overlapped or have gaps to the greatest extent, and a high-precision and high-resolution digital elevation model is adapted; and subsequent updating and maintenance of the digital elevation model and the remote terrain correction value library are facilitated.

The invention provides a smooth non-uniform rational B-spline three-dimensional terrain entity fitting creation method and system, which are mainly applied to the field of pumped storage power station engineering and realize efficient conversion from a two-dimensional contour line to a smooth terrain entity. According to the method, a technical route of an NURBS terrain entity is finally generated by establishing a triangulation network curved surface, specifying a boundary, converting DEM data, creating a grid curved surface, extracting control points and fitting an NURBS curve in a UV direction. Converting the contour line into DEM data and creating a grid curved surface; extracting control points and respectively fitting NURBS curve groups according to U / V directions; a complete NURBS three-dimensional terrain entity is formed by enclosing the surface curved surface, the bottom plane and the four side curved surfaces. According to the method, on-demand adjustment of terrain precision can be achieved, the generated entity can be directly used for CAE simulation calculation and can be combined with a panel dam partition amount calculation algorithm, and the engineering design efficiency is improved.

The invention provides a cross-country type forklift boom amplitude variation and telescopic speed optimization control system, and relates to the technical field of speed control, and the cross-country type forklift boom amplitude variation and telescopic speed optimization control system comprises the steps that an accessory self-adaptive recognition strategy is formulated, and a corresponding accessory type is selected; collecting a working posture and pressure data; according to the working posture, the pressure data and the accessory type, a load torque dynamic resolving algorithm is constructed, and real-time load torque is obtained; constructing a safety boundary constraint condition according to the real-time load moment, and obtaining a safety constraint speed instruction; obtaining an optimal speed instruction according to the security constraint speed instruction and the accessory type; on the basis of a self-adaptive anti-interference algorithm, according to the optimal speed instruction, a motor rotating speed closed-loop control algorithm is constructed, and then motor driving voltage is obtained; on the basis of the neural network inverse model and according to the optimal speed instruction, an electromagnetic valve opening instruction is obtained; and according to the motor driving voltage and the electromagnetic valve opening degree instruction, the speed of the cross-country type forklift boom of the corresponding accessory type is controlled.

The present invention relates to a low-frequency eddy current-based thermal power plant drain pipe seat inner wall defect detection method. The method comprises: organizing and collecting data to determine the distribution and characteristics of crack defects in inner walls of drain pipe seats of pressure parts, so as to provide a theoretical basis for the next step of specimen manufacturing; determining a scanning mode and designing reference specimens having cracks, so as to configure the detection sensitivity by means of the reference specimens; by means of an eddy current penetration depth formula and the reference specimens, configuring a detection frequency, and performing parallel-line or grid-line scanning along a scanning path at fillet weld parts of pipe seats and at parts from fusion lines below fillet welds to fusion lines above butt welds; and introducing an equivalent method and a formula calculation algorithm, so as to perform defect quantification and position determination on the basis of the amplitude of trajectory curve signals. The present invention solves the problem of nondestructive detection of crack defects in inner walls of drain pipe seats of pressure parts in in-service thermal power units, and can effectively avoid pipeline leakage accidents caused by expansion of crack defects. The method is simple, safe, reliable and widely applicable.

The invention discloses a current pulse generator noise reduction method and device, and relates to the technical field of current pulse generator noise reduction, and the method specifically comprises the following steps: removing a main pulse waveform from a filter response sequence, extracting filter residual response segments of a plurality of periods, carrying out the time alignment and overlapping processing of the residual response segments of the plurality of periods, and carrying out the noise reduction of the current pulse generator. Constructing a residual energy superposition trend line; based on the residual energy superposition trend line, a Savitzky-Golay sliding window polynomial fitting derivative algorithm is adopted to calculate a trend offset rate parameter, and a wavelet packet decomposition and Shannon entropy calculation algorithm is adopted to generate a disturbance frequency domain diffusivity parameter so as to reflect whether the residual energy superposition behavior of the filter is evolved into self-excitation background noise. According to the method, the problem that residual energy superposition of the filter is difficult to recognize under continuous narrow pulses is solved, precise recognition and dynamic intervention control of self-excitation background noise are realized, and the system stability is improved.

The invention discloses an intelligent monitoring control method and system for spraying equipment, and relates to the technical field of intelligent monitoring and pressure control, and the method comprises the following steps: collecting compressed air branch flow data and pipe network node pressure data in real time, obtaining a pipe network topological parameter set, extracting a characteristic frequency band energy value, and calculating a characteristic frequency band energy value; establishing a branch impedance model in combination with the pipe network topological parameters, and outputting an impedance factor of each branch through the model; if the energy value of the characteristic frequency band is greater than the set threshold value, obtaining the position of a leakage point through a leakage calculation algorithm, and outputting the leakage amount; and constructing a pipe network transfer function at the output of the impedance model, predicting a pressure fluctuation envelope, and dynamically generating a pressure control instruction according to a prediction result. According to the invention, the PID control parameters of the buffer tank are dynamically adjusted according to the comparison of the predicted value and the actual pressure fluctuation, so that the rapid pressure recovery control of self-adaptive correction according to the severity of leakage is realized, and the steady state and dynamic performance of the system are improved.

The invention discloses a database detection operation method of biological feedback equipment, and relates to the technical field of database detection operation, according to the database detection operation method, in combination with a change data capture CDC technology and a Kafka Streams streaming processing framework, myoelectricity reaction data are collected and cleaned in real time, redundant processing operation of full-amount data is effectively reduced, an incremental calculation algorithm is introduced to process dynamic data, and therefore the dynamic data processing efficiency is improved. The dynamic change of data can be quickly adapted by updating the average value and the standard deviation of the detection base line; meanwhile, a priority grouping mechanism is introduced, high-priority data with large deviation are sorted according to the abnormal amplitude from large to small, and the high-priority data are immediately transmitted to a visualization module for emphasized processing; low-priority data with small deviation is processed in a batch mode according to a detection sequence, and resource allocation and response speed are optimized; and high-priority data generates an exclusive thermodynamic diagram and a tendency diagram through an independent process, and low-priority data is integrated into a grouped thermodynamic diagram and a statistical distribution diagram, so that the intuition and practicability of data interpretation are remarkably improved.

The invention relates to the technical field of data processing, and discloses an urban space structure collaboration measurement method and system, and a storage medium. The method comprises the following steps: performing gridding processing on urban space elements through multi-temporal data acquisition to obtain a three-dimensional data matrix; calculating a space-time dynamic coupling coefficient by adopting an improved gravity model according to the three-dimensional data matrix; constructing a space-time bidirectional weighting network through a bidirectional weighting algorithm; a dynamic collaboration degree index DSCI is calculated based on network self-adaption; and determining a collaboration degree threshold value through multi-level nesting identification, and obtaining a measurement report. According to the method, through constructing the space-time bidirectional weighted network and the dynamic coordination degree index DSCI adaptive calculation algorithm, the space-time dynamic coupling relation quantification precision of the urban space structure coordination measurement is improved. Meanwhile, a self-adaptive collaboration degree threshold combination is established through multi-level nesting recognition, and the dynamic adaptability of the collaboration evaluation standard to the urban development stage and policy environment change is improved.

The invention discloses a file access cold and hot degree calculation method and system based on a large model and a medium, and belongs to the technical field of data storage. The method comprises the following steps: a system initialization and monitoring configuration stage: initializing a cold and hot degree calculation algorithm, and loading a pre-deployed large language model; a multi-dimensional feature extraction stage: extracting a multi-dimensional feature vector of the target file in real time; in the dynamic prompt generation stage, the multi-dimensional feature vectors are dynamically arranged into structured natural language prompts, and the structured natural language prompts are input into a large language model; in the popularity generation and cache management stage, a popularity score of each file is generated, and the cache space is managed according to the popularity score; and in the adaptive learning and optimization stage, an implicit user feedback loop is established, and when feedback signals with preset numerical values are accumulated, increment fine tuning is carried out on the large language model according to the collected feedback data. According to the method, the cache hit rate is remarkably improved, and the access fluency of the key data of the user is guaranteed.

The invention provides an optimization method and system of a distributed battery management system. The method comprises the following steps: acquiring battery cell parameters, scene parameters and historical charging and discharging data of a battery cell, and evaluating a battery aging stage; calling a matched battery cell state calculation algorithm according to the scene parameters and the battery aging stage; calculating battery cell state information of the battery cell according to the battery cell parameters, the scene parameters and a battery cell state calculation algorithm; according to the cell state information, the scene parameters and the battery aging stage, dynamically adjusting an equalization threshold and an equalization rate, and executing an equalization strategy to obtain equalization state information; periodically uploading the operation data to a cloud server, receiving an algorithm update package, and updating an adaptive algorithm library; and calculating the overall state information of the battery pack according to the cell state information and the equilibrium state information. The calculation precision of the battery cell state can be effectively improved, the cycle life of the battery is prolonged, and the use safety of the battery is improved.

The invention relates to an adaptive crosstalk cancellation circuit agile design method and device, and the method comprises the steps: obtaining a circuit design index of a target circuit schematic diagram inputted by a target user; sending the circuit design indexes to a preset generator, so that the generator calculates a plurality of parameters in the target circuit schematic diagram according to a preset parameter automatic calculation algorithm; and substituting the plurality of parameters into the target circuit schematic diagram to convert the plurality of parameters into a netlist file, a layout file and a tester corresponding to the target circuit schematic diagram through a preset TED built-in engine, and constructing the target circuit schematic diagram according to the netlist file, the layout file and the tester. Therefore, the problems that in the prior art, crosstalk exists in a Chiplet chip parallel interface circuit, and the design efficiency, flexibility and expandability are poor are solved.

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 relates to the technical field of animal monitoring, and discloses a wild animal multi-modal data fusion analysis method, which comprises the following steps: adding corresponding timestamp information to sensor data detected by a sensor assembly arranged at an animal necklace, performing attitude calculation on the converted attitude characteristic data by adopting a six-axis attitude calculation algorithm to obtain a corresponding pitch angle, a roll angle and a yaw angle; constructing a multi-modal feature vector according to the posture feature, the physiological feature, the environment feature, the spatial-temporal feature and the derivative feature; and inputting the multi-modal feature vector into an animal behavior recognition model to perform behavior recognition so as to determine a current behavior tag of the corresponding wild animal. According to the wild animal multi-modal data fusion analysis method in the embodiment of the invention, the state of the wild animal can be comprehensively described. The multi-modal feature vector fuses information of multiple dimensions, behaviors and physiological states of animals in different scenes can be described more accurately, and the recognition accuracy is improved.

The invention discloses a computer vision technology-based hidden engineering reinforcing steel bar quality automatic detection method, which comprises the following steps of: acquiring an image of a binding reinforcing steel bar, performing data enhancement processing on the acquired image, and performing position and size marking on the processed image to obtain a binding reinforcing steel bar data set; using the data set to train a YOLOv8 target detection network to obtain a target detection model; inputting the preprocessed image needing to be detected into a target detection model for target identification to obtain the number and position information of all steel bars in the image; extracting a contour according to the steel bar position information, and performing size calculation by using a size calculation algorithm; and comparing the size and the number of the reinforcing steel bars with reinforcing steel bar parameters indicated in a design file, and judging whether the index error meets the acceptance standard or not. The device is high in automation degree and low in cost, multiple steel bars can be measured at the same time, and the detection efficiency and precision are remarkably improved.