13150 results about "Calculation methods" patented technology

The invention provides a pre-control and monitoring method for a whole process of actual grouting engineering based on digital geological model, comprising: extracting discontinuous fracture surfaces in a geologic body structure, to build a underground geologic body structure model; build a multi-source geologic body attribute model, optimizing and solving grouting simulations of a disaster high-risk region by using multiphase flow calculation method, and controlling grouting equipment by using optimized grouting parameters to carry out an actual grouting engineering; obtaining a multi-factor diffusion range of variable coefficients by adjusting physical values of the parameters in the grouting simulation and attribute data structure model by using a control variable method, learning and capturing complex mapping relationship between different parameters by using a neural network, optimizing the grouting parameters in the actual engineering in real-time, so as to realize the pre-controlling, monitoring and optimization of the whole process of the actual grouting engineering.

The invention discloses a Text2SQL (Structured Query Language) implementation method and system, and relates to the field of data processing, and the method comprises the following steps: firstly, receiving a natural language query, and analyzing a query intention, field classification and a key entity through a planner; the searcher obtains domain knowledge, entity information, a database table structure and a historical query mode in a multi-path parallel mode based on the planning result; the generator constructs an SQL framework according to the retrieval result and generates an initial statement; the verifier carries out grammar, table field, authority and logic multi-dimensional verification on the SQL, and if the verification fails, iteration adjustment is carried out to generate logic; when the SQL is executed, the result is formatted and a natural language explanation containing query logic, a data source and a calculation method is generated if the SQL is executed successfully, and a diagnosis and error correction mechanism is started for correction and then rechecking is performed if the SQL is executed unsuccessfully. According to the method, through deep fusion of domain knowledge, whole-process verification error correction and interpretability enhancement, the accuracy, robustness and user interaction experience of SQL conversion in a professional scene are improved.

The invention relates to the technical field of radar signal processing, in particular to a radar target analytical calculation method based on multi-dimensional data fusion and a radar device. Comprising the following steps: deploying a multi-band radar sensor array comprising an X band, a C band and a Ku band in a radar monitoring area; performing pulse compression and Doppler processing on the time domain echo signal, and extracting a time domain feature; spectral analysis is carried out on the frequency domain signals, and frequency domain features are extracted; performing angle estimation on the spatial signals, and extracting spatial features; a dynamic weight distribution model is constructed, a fusion weight is calculated through an adaptive algorithm based on three-dimensional quality indexes of a real-time signal-to-noise ratio (SNR), feature stability (SI) and data integrity (CI), and a joint representation vector containing time domain, frequency domain and space multi-dimensional information is generated. According to the invention, by deploying the multi-band radar sensor array, the recognition capability of the subtle feature difference of the target is improved.

The invention discloses a data-mechanism dual-drive-based rock burst early warning method and system, and the method comprises the following steps: deploying a multi-modal sensor network to collect coal and rock stratum data, building a rock burst disaster precursor information sample database, providing a rock burst disaster multi-modal data precursor feature recognition algorithm, and carrying out the recognition of rock burst disaster multi-modal data precursor features. Mining the relevance between the multi-modal data and disaster-causing key risk indexes, and establishing a rock burst disaster multi-modal data prediction model; establishing a three-dimensional geological geometric model, fusing a multi-field coupling dynamics constitutive model and a catastrophe criterion, constructing a PINN physical information neural network prediction model of the rock burst disaster, and obtaining a time-space evolution rule of an energy field of a target area; providing a loss function coupling calculation method of a multi-modal data driving sample error and a physical driving control equation residual error, dynamic data and mechanism prediction result weight, comprehensively calculating a risk score, and accurately judging a top disaster danger level.

The invention relates to the technical field of artificial intelligence and natural language processing, in particular to a key value cache compression and sparse attention calculation method and system for large language model reasoning, and the method comprises the steps: an offline calibration stage; the online reasoning stage comprises the following steps: a pre-filling step; an autoregression generation step: for each newly generated lexical element, projecting a current query vector Q and a key vector K in a key cache to a low-dimensional space to obtain Q'and K '; calculating an approximate attention score based on Q'and K ', and selecting an index I of the first k most relevant lexical elements which are ranked from high to low; and calculating an accurate attention score based on Q and K [I], and calculating with the value vector V [I] to obtain the output of the current lexical element. According to the scheme, the memory and calculation bottleneck of large model reasoning in a scene of long text sequence input are solved, and the method has the advantages of reducing video memory occupation and calculation complexity at the same time.

The invention relates to the technical field of unmanned aerial vehicle positioning, in particular to an unmanned aerial vehicle flight path positioning method and system based on multi-source information fusion. The method comprises the following steps: acquiring an original observation data stream of an unmanned aerial vehicle in real time through a sensor array, and preprocessing to output a multi-source data sample set; calculating relative motion increment between adjacent key frames through an IMU pre-integration model, and extracting local pose estimation through a visual geometric calculation method; evaluating the confidence of each sensor in real time to dynamically generate an adaptive weight coefficient; and constructing a tight coupling fusion filter taking position, speed and attitude errors as core state quantities, and outputting a global optimal trajectory of the unmanned aerial vehicle. According to the invention, the weight is dynamically distributed through the real-time confidence of the sensor, the multi-source data association is fully mined, and the flight path positioning precision and environmental adaptability of the unmanned aerial vehicle are improved.

The invention discloses a geothermal field parameter inversion calculation method, device and system, and a storage medium. The method comprises the following steps: establishing a geophysical stratified model; through Monte Carlo sampling of preset parameter spaces of the crustal heat generation rate and the heat conductivity, a temperature value is calculated in combination with a heat conduction equation, and a Gaussian likelihood function evaluation model is constructed to predict the matching degree of the temperature and the actually measured temperature; obtaining the optimal estimation of the thermal parameters, a confidence interval and a correlation matrix among the parameters based on the posterior probability distribution; and according to the correlation matrix, taking a high-confidence result generated by Monte Carlo inversion as priori knowledge of a physical guidance neural network PINNs, and finally outputting a thermal parameter spatial distribution prediction result of the target area through parameter initialization constraint, output layer range limitation and a physical regularization loss item. By adopting the technical scheme of the invention, the defects that the existing actually measured geothermal field parameters are rare and the regional characteristics cannot be described and the geophysical joint inversion of the geothermal field parameters cannot be realized in the prior art are overcome.

The invention discloses a deep covering layer panel rock-fill dam rheological numerical calculation method considering the seepage effect. The method comprises the steps that firstly, contact deformation between a panel and a dam body is simulated; then simulating the unstable seepage process of the rock-fill dam and the foundation, and solving the seepage problem with a free surface; carrying out seepage-stress coupling calculation on the dam body material, and establishing a seepage-stress coupling control equation of the dam body material; carrying out seepage-stress coupling calculation on the overburden foundation, establishing a seepage-stress coupling control equation of the foundation, and finally obtaining a relationship among stress, strain and pore pressure to realize the seepage-stress coupling calculation; numerical simulation is conducted, and a concrete faced rockfill dam rheological numerical simulation result considering the seepage effect is obtained. The problems that in the prior art, the stress deformation rule of the concrete faced rockfill dam under the seepage-rheology coupling effect is not clear yet, and meanwhile, a seepage-rheology coupling calculation method is not perfect enough are solved.

The present invention relates to the technical field of mechanical property testing and characterization. Disclosed are a method and apparatus for calculating a crack propagation life of an engine structure in vibration fatigue, which method and apparatus aim to obtain reliable fracture mechanics parameters and a crack propagation rate curve and provide an accurately quantified crack propagation life, so as to provide methodological guidance for the life assessment of reusable engines. The calculation method comprises: acquiring a time-domain random stress spectrum of stress responses in an assessment section in a finite element model of an engine structure; on the basis of the time-domain random stress spectrum, performing finite element analysis processing on a crack model of the engine structure, so as to determine fracture mechanics parameters of a cracked structure; performing a vibration fatigue performance test on a crack propagation rate model, which is set up according to a preset crack propagation mode, and determining, by using parameter identification, a target parameter value corresponding to the crack propagation rate model; and in combination with the parameter value corresponding to the crack propagation rate model and a preset critical crack length value, performing crack propagation life calculation, so as to obtain a target crack propagation life.

The invention discloses a CAD drawing engineering quantity automatic identification and calculation method based on a large language model and image segmentation, and the method comprises the steps: extracting project annotation information in a CAD drawing, understanding and reasoning a project introduction through a large language model, and carrying out the structural expression of the project annotation information; the method comprises the following steps: preprocessing a graph in a CAD drawing by utilizing computer vision, analyzing a pipeline drawing of the CAD drawing by utilizing machine learning, identifying the type and position of a component in the pipeline drawing, and realizing semantic segmentation and instance segmentation; and fusing the structured project annotation information, the semantic segmentation result and the instance segmentation result, counting and calculating the project amount of each pipeline component in the CAD drawing image, and outputting a report according to classification. According to the method, OCR recognition, natural language processing, graph semantic recognition, engineering logic calculation and other technologies are integrated, the CAD drawing processing efficiency and the engineering quantity calculation accuracy are greatly improved, and intelligent support is provided for design, construction, drawing examination, budget and other links.

The invention discloses an intelligent measurement and calculation method and system for forest carbon reserves, and relates to the technical field of carbon reserve measurement and calculation, and the system obtains a forest electronic distribution diagram through a GIS technology and surveying and mapping data, collects various carbon reserve related data, and then carries out the correction and denoising of the collected data through a FLAASH algorithm and other preprocessing technologies; the AI sampling optimization model extracts forest features based on a convolutional neural network CNN, and dynamically adjusts a sampling area; secondary acquisition is carried out, data preprocessing is carried out, the total carbon reserve of the forest is estimated by calculating the carbon reserve of each grid, and the forest succession stage, the carbon sink change and the ecological carbon cycle are further analyzed; and finally, in combination with the dynamic influence coefficient of the carbon reserves and a preset threshold value Q, judging the change trend of the carbon reserves, triggering early warning and giving a coping strategy.

The invention provides a seat comfort optimization calculation method based on a sensor and AI modeling, and the method comprises the steps: collecting the pressure distribution data of the sitting posture of a passenger and a spine contact area in real time through an attitude sensor and a pressure sensor which are disposed on a seat; a seat supporting area is divided into a cervical vertebra area, a thoracic vertebra area, a lumbar vertebra area and a sacrococcygeal area, and a pressure distribution prediction model of each area is established; constructing an input vector based on the average pressure, the maximum pressure, the pressure gravity center, the body type parameter and the pathological weight factor, and outputting a target support pressure value, a pressure avoiding curve and a neighbor cell migration proportion of each partition by using an artificial intelligence model; dynamic adjustment is achieved through the partitioned air bag and the driving unit, and secondary fine adjustment and protection are achieved in combination with feedback monitoring. The system comprises a posture sensing module, a pressure sensing module, a data processing module, a model building module, a regulation and control execution module and a feedback monitoring module, and self-adaptive regulation and control of different areas of the spine of a passenger can be achieved.

The invention relates to the technical field of remote sensing data processing and glacier area calculation, in particular to an unmanned aerial vehicle and satellite remote sensing data fused glacier area calculation method, which comprises the following steps of: cooperatively acquiring a satellite multispectral image and unmanned aerial vehicle high-resolution optical and LiDAR data, performing time synchronization, high-precision space registration and data enhancement processing, and calculating the glacier area through the unmanned aerial vehicle and satellite remote sensing data fusion. A satellite image glacier macroscopic feature and an initial mask are extracted by using a convolutional neural network and an NDSI / NDWI algorithm, and unmanned aerial vehicle image microscopic texture, edge and topographic features are acquired through a local binary pattern, edge detection and LiDAR point cloud; based on pyramid layering and a conditional random field, adopting a variance weighting algorithm to realize multi-scale feature level fusion; and after segmentation through an Otsu algorithm, calculating the area through a pixel counting method and introducing gradient correction, and evaluating the reliability through three types of precision. The method breaks through the limitation of a single data source, fuses macroscopic and microscopic features, improves the boundary positioning precision and calculation efficiency, and is suitable for glacier dynamic monitoring in a complex environment.

The invention discloses a BIM model-based water conservancy project cost accurate calculation method and system, and relates to the technical field of water conservancy project informatization management, and the method comprises the steps: obtaining BIM model component data, construction scheduling data, construction path data and construction cost data, constructing a scheduling component diagram for conflict recognition, calculating the load value of a path segment, and calculating the load value of the path segment; a construction progress deviation value is determined by combining sensing data of the internet of things, and finally a comprehensive cost estimation value is calculated; the method has the beneficial effects that BIM model component data, construction scheduling data, path data and cost data can be integrated, a three-dimensional scheduling component diagram is constructed for conflict detection, a progress deviation value is dynamically calculated in combination with sensing data of the Internet of Things, quantitative association of construction cost and progress deviation is realized, and the construction efficiency is improved. The method has the advantages of improving the construction cost calculation accuracy, enhancing the dynamic response capability of the construction process and realizing the real-time linkage of the cost and the progress.

The invention relates to a wharf sensing method and system based on data fusion of a laser radar and a camera, and the method comprises the steps: firstly employing a fisheye camera to shoot a checkerboard calibration plate at multiple angles, employing a Zhang's calibration method to calculate an internal reference matrix and a distortion coefficient of the fisheye camera, and synchronously collecting the data of the laser radar and the camera in real time; the method comprises the following steps: performing distortion removal processing on a camera image, calculating an external parameter matrix between a laser radar and a camera through a feature extraction algorithm, a feature point matching algorithm and a nonlinear optimization algorithm, and performing data fusion through an internal parameter matrix, the external parameter matrix and a bilinear interpolation method to generate fusion point cloud data with color information; and finally, identifying a key target of the wharf by marking and training a CNN model, and calculating three-dimensional parameters of the key target by adopting a specific calculation method, so that a sailor can quickly distinguish the target in the fused point cloud data, the accuracy and efficiency of wharf environment perception are remarkably improved, and accurate environment perception and decision support are provided for ship berthing and departing operation.

The invention discloses a large-model-driven intelligent calculation method and system for a water conservancy mechanism model. According to the method, natural language input, structured conversion and intelligent optimization calculation of a scheduling target are realized by integrating a field-enhanced large language model and a water conservancy professional mechanism model. The method comprises the steps of receiving a calculation target expressed by a user in a natural language, and analyzing and converting the calculation target into a constraint condition and a target function which can be recognized by a water conservancy mechanism model; a hydrological model, a hydraulic model, a hydrodynamic model and other models are called based on a workflow engine, and reverse calculation is carried out by adopting a hybrid optimization strategy of'coarse adjustment-fine adjustment-verification '; synchronously and visually displaying the parameter change and the result convergence state in the calculation process; and outputting a calculation result including parameter adjustment logic, standard conformity analysis and multi-scheme comparison. The system comprises a natural language interaction module, a target conversion module, an intelligent calculation engine module, a visualization module and a result generation module, and supports multiple application scenes such as multi-target scheduling, emergency decision making and ecological guarantee. Compared with a traditional scheme, the method has the advantages that the model use threshold is lowered, the dispatching efficiency and calculation transparency are improved, and the method is suitable for complex hydraulic engineering calculation tasks such as reservoir dispatching, cross-basin water transfer and flood control emergency.

The invention discloses a diastrophic stratum deformation analysis and calculation method for an active fault zone, and relates to the technical field of geological engineering calculation, and the method comprises the following steps: (1) constructing a three-field dynamic coupling model based on an energy density gradient, and unifying dimensions of physical parameters of a mechanical field, a seepage field and a temperature field as an energy density function; according to the diastrophic stratum deformation analysis and calculation method for the active fault zone, the problems of multi-physical field splitting and time scale solidification in a traditional method are solved by constructing an energy-mediated multi-field dynamic coupling model and a space-time decoupling algorithm. On the basis of an interaction path of energy density gradient tensor unified mechanics, seepage and temperature fields, instantaneous bidirectional feedback of three-field parameters is achieved, compared with a traditional model, the pore pressure prediction error is reduced, and the calculation efficiency is improved; and meanwhile, the joint simulation efficiency of the second-level seismic event and the ten-thousand-year tectonic motion is improved, the interface parameter continuity error is controlled, and the precision and stability of cross-scale modeling are improved.

The invention particularly relates to a laser point cloud over-break and under-break volume calculation method for tunnel engineering, and relates to the technical field of tunnel engineering construction quality detection. Modeling a tunnel design contour; matching and aligning the point cloud with the design model; carrying out over-break and under-break area division and volume calculation; and result visualization and report output. According to the method, point cloud preprocessing parameter optimization and high-precision registration are achieved through multi-dimensional quantitative analysis, and the reliability of an over-break and under-break calculation benchmark is remarkably improved; in a point cloud denoising link, a voxel evaluation coefficient is introduced to ensure that the filtered point cloud not only keeps key details such as tunnel vault radian and side wall broken lines, but also can simplify the data volume; in a model registration stage, outlier interference is eliminated and a strict iteration stop condition is set, so that a reliable reference is provided for back break deviation calculation.

The invention relates to a multi-source data fusion-based urban physical examination evaluation index calculation method and system. The method comprises the steps of extracting a multi-source data sequence; identifying a data source of the urban physical examination index set, and extracting an independent time sequence data sequence; calculating the information entropy of the independent time sequence data sequence, and distributing a basic fusion weight; calculating a dynamic state evaluation value of the independent time sequence data sequence, and performing weighted fusion on the basic fusion weight and the dynamic state evaluation value to obtain a comprehensive state evaluation value; obtaining a distribution variance of the basic fusion weight, inputting the distribution variance into the uncertainty quantification model, and obtaining an index calculation result containing uncertainty measurement; the real-time performance of the evaluation result is enhanced through an aging attenuation mechanism, and the latest state of the city system is accurately reflected; the output uncertainty measurement index provides a quantitative basis of result credibility for a decision maker, and the decision risk caused by a data fusion error is reduced.

The invention discloses a material similarity calculation method and system based on high-dimensional features and multi-modal features, and belongs to the technical field of supply chain management. The method comprises the following steps: carrying out multi-modal feature extraction on preprocessed structured data, text description and visual data, and respectively generating a structured vector, a text vector and a visual vector; synchronizing the structured data through metadata, entity names and time, and establishing association between the structured data and text description and visual data; carrying out weighted fusion on the structured vector, the text vector and the visual vector by adopting a dynamic weight distribution strategy to generate a unified material feature vector; according to the multi-modal features, identifying entities and extracting relationships, and constructing and storing a material knowledge graph; and calculating the similarity, and retrieving and outputting a matching result. The system comprises a multi-modal feature extraction module, a cross-modal association module, a feature fusion module, a knowledge graph module and a similarity calculation and retrieval module. According to the method, the weight optimization of each modal is dynamically adjusted, and the matching precision is improved.

The invention discloses a free-form surface three-axis ball-end cutter equal approximation error finish machining tool path generation method which comprises the following steps: firstly, importing a free-form surface model to be machined, and setting data such as the radius, the line spacing, the approximation error maximum allowable value and the precision of a ball-end cutter; secondly, a group of section planes are planned according to the row spacing to intersect with the curved surface, the intersecting line serves as a cutter contact curve, and an equal-bow-height-error cutter contact iterative search method for driving cutter contact adjustment through the geometric distance is provided for the cutter contact curve on the section planes; the maximum distance between a cutter cutting envelope surface and a cutter contact track line is used as an approximation error, and an adaptive discrete method is adopted to carry out approximation error calculation; and finally, the cutter location points of the equal-bow-height-error cutter contact points serve as initial values, an equal-error cutter location point calculation method of step length self-adaptive adjustment iteration is provided, approximation errors between the cutter location points are all within an allowable range, and therefore the free-form surface three-axis ball-end cutter equal approximation error finish machining cutter path is obtained.

The invention discloses a CFD-based dust explosion calculation method, and particularly relates to the technical field of dust explosion risk assessment. Firstly, initial dust parameters of a target scene are obtained, then a three-dimensional computational domain is established in combination with a geometric structure, ventilation conditions and obstacle distribution, and a dust deposition area is marked; constructing a gas-solid phase coupled dust explosion solving equation set in the CFD framework; outputting time sequence data of pressure, temperature, speed and dust concentration in the whole explosion process, and generating a risk grade distribution diagram based on the maximum explosion pressure and flame coverage time; according to the invention, the propagation and damage process of dust explosion can be accurately reproduced, the simulation precision and efficiency are improved, and the evaluation result can directly guide protection design and safety management.

The invention discloses a MoE large model reasoning optimization method and device based on expert module dynamic scheduling, and relates to the technical field of large model reasoning optimization. The method comprises the steps of performing pre-reasoning through a MoE large model according to a dialogue text data set to obtain a first evaluation score set; performing value optimization on the GPU candidate expert quantity value set through an expert cache hit rate calculation method to obtain a GPU candidate expert optimized value set; cPU expert module dynamic scheduling is carried out based on the relation curve of the expert score ascending value-the transmission expert number, and a CPU expert scheduling index list is obtained; gPU expert module dynamic supplementation is carried out according to the first evaluation score set and the CPU expert scheduling index list, a GPU expert supplementation index list is obtained, re-reasoning is carried out through a MoE large model, and a reasoning result text data set is obtained. The invention relates to a large model reasoning optimization method for balancing model reasoning speed and output result quality of a MoE large model.

The invention relates to the technical field of data linkage calculation, and provides a multistage document dependent freight trial calculation data linkage calculation method and system, and the method comprises the steps: expanding the attribute of a document node from a single business field to a composite vector containing a spatial-temporal feature through time information and geographic identification spatial-temporal dimension modeling; the dependency graph can capture the fine-grained dependency relationship of the freight service, and the space-time accuracy of data linkage is improved; when the basic information or the document information changes, the priority and the calculation path of the task queue are updated in real time through deep reinforcement learning, and calculation errors caused by change lag are avoided; through tensor synthesis operation, parallel subtask division, and a dual verification mechanism of a domain knowledge graph and a forced dependency edge, it is ensured that the whole process from dependency graph construction to calculation result output conforms to industry specifications, and the compliance and risk control ability of freight services are significantly improved.

This document discloses methods and systems for cohort identification. The methods and systems include improved calculations to perform cohort identification and practical applications of the improved calculations. Specifically, the systems and methods described herein may utilize key components that include enhancements of existing cohort clustering techniques with regard to selecting a number of cohort input dimensions, normalizing input data using a logarithm kernel-function, treatment of categorical data with mutually exclusive and not-mutually exclusive values, methods and visualization tool to determine appropriate number of cohorts, methods and visualization tool to compare cohorts extracted from different input dimensions, and methods to quantify the difference in cohorts. Beyond improvements to the cohort clustering techniques, also disclosed are ancillary tools to prepare input data by joining CRM and product usage data and facilitate subsequent automated action via an API to retrieve cohort results.

The invention relates to the field of coating material production, and discloses a coating formula calculation method and system based on self-learning feedback parameter correction, and the method comprises the steps: obtaining raw material basic parameters, target performance requirements and process feedback data of historical production batches, combining a material screening mechanism and an environment working condition correction strategy, and calculating a coating formula; constructing a coating formula initial input matrix; performing multi-dimensional variable normalization processing on the initial input matrix of the coating formula, introducing a feature sensitivity analysis model, and extracting a key variable group influencing the coating performance in the feature sensitivity analysis model; based on the performance response relation mapping model, analyzing error distribution between model prediction output and actual detection data by using a prediction deviation recognition mechanism, and extracting learning error features; a self-learning feedback updating mechanism is introduced, and dynamic weight optimization is conducted on the parameter correction factor set; and performing sample test and performance verification on the corrected candidate formula set. The method has the advantage that the coating formula precision is improved.

The invention provides a mixed data precision matrix multiplication and addition unit and a calculation method, the matrix multiplication and addition unit comprises a calculation unit, and the calculation unit comprises a format division module, a multiplication array module, an addition tree module, an accumulator module, a normalization module and a shift register module. The calculation unit converts the first input matrix and the second input matrix into input data in a middle floating point format; executing parallel multiplication operation on the input data to generate an intermediate product result; performing index alignment and accumulation on the intermediate product result to generate an intermediate accumulated value; accumulating the intermediate product result and the value of the third input matrix in a form of accumulating an intermediate accumulated value, and outputting an accumulated result; and converting an accumulation result into a normalized result and outputting the normalized result. The format division module supports various precisions and converts data with different widths into an intermediate floating point format, so that other hardware units can be reused, and the problems that hardware resources are complex and different model reasoning scenes are difficult to meet are solved.

The invention discloses a federated learning driven trusted data space cross-domain cooperative computing method, and relates to the technical field of data processing, and the method comprises the following steps: carrying out access trust verification on a plurality of data providing domains according to a dynamic trust mechanism; after the verification is passed, accessing each data providing domain into a trusted data space for local training, and generating a local model; performing cross-domain cooperative calculation on the plurality of local models, and establishing an initial global model; and carrying out loss generalization evaluation on the initial global model, and triggering a differential feedback learning module to carry out iterative reinforcement to generate a global reinforcement model. According to the method, the technical problems of limited data privacy protection, trust missing among different mechanisms and insufficient model generalization ability of cross-domain data cooperative calculation in the prior art are solved, multi-party cooperation is realized on the premise of no data leakage through a dynamic trust mechanism and differential privacy protection, and the reliability of the cross-domain data cooperative calculation is improved. And the precision and generalization ability of the global model are improved.

The invention relates to the technical field of metering pumps, in particular to an external meshing gear metering pump flow calculation method based on linear regression and curve fitting, which comprises the following steps: generating an integrated data set by monitoring the flow rate, pressure, temperature and viscosity in real time, setting flow rate, pressure and temperature thresholds based on the data set, judging the flow state and recording abnormity, and calculating the flow rate of the external meshing gear metering pump. Flow velocity and viscosity are selected for flow calculation, a corrected flow value is generated, whether flow is normal or not is analyzed and determined, a flow stability evaluation result is generated, and a visual interface is created to display parameters and a calculation result. According to the method, the multiple sensors are installed at the inlet and the outlet of the metering pump, the flow speed, the pressure, the temperature and the viscosity are monitored in real time, an integrated data set provides a precise basis for flow calculation, a threshold value is set, data are monitored, it is ensured that parameters exceeding the normal range can be recorded and analyzed in time, and the process improves the accuracy of flow calculation and improves the working efficiency. And flow evaluation is optimized, and the operation safety and efficiency are improved.

The invention discloses a complex terrain three-dimensional modeling and earthwork volume calculation method based on a multi-source fusion point cloud, belongs to the technical field of surveying and mapping and engineering surveying, and mainly solves the problems of low terrain modeling precision and insufficient earthwork calculation efficiency in a complex scene. The method comprises the following steps: constructing a ground-air integrated multi-source sensing network to synchronously acquire laser point cloud, multi-view images and positioning data; adopting PointNet + +-based initial registration and multi-scale ICP fine registration fusion to generate a unified point cloud; combining semantic segmentation and penetration probability filtering to accurately extract a digital elevation model; constructing a similar triangular prism voxel model by using a constrained Delaunay triangulation network; and finally, the earth volume is rapidly calculated by adopting a GPU parallel voxel cutting and filling algorithm, so that high-precision terrain modeling and rapid engineering quantity calculation are realized, and the method can be efficiently and reliably applied to large-scale projects such as roads and mines.