388 results about "Difference analysis" patented technology

The invention discloses a live-action three-dimensional dynamic change modeling method based on digital twinning. The method comprises the following steps: collecting multi-source data; carrying out space registration and time synchronization processing, and outputting a fusion data set; carrying out three-dimensional modeling, optimizing model parameters, and generating a live-action three-dimensional model; virtual-real mapping is carried out, and generated virtual space data and state parameters thereof are stored; performing differential analysis to generate a change detection result data set; performing dynamic change modeling to generate an updated virtual model; executing geometric accuracy optimization and semantic consistency check, and outputting an optimized virtual model; bidirectional data flow association and dynamic updating are executed, and the live-action three-dimensional dynamic change modeling process is completed. The real scene dynamic updating is realized by adopting the improved Gaussian sputtering modeling, and the method has the advantages of high precision, strong real-time performance and virtual-real synchronization.

Provided in the present invention are a method and system for real-time update of a medical knowledge base, and a medium and a device. The method comprises: acquiring medical literature data in real time; analyzing the medical literature data, so as to obtain first structured data; performing correlation analysis on the first structured data and second structured data in a medical knowledge base, so as to obtain an analysis result; on the basis of the analysis result, determining whether to update the medical knowledge base; identifying the differences of the medical knowledge base before and after the update, so as to obtain a difference identification result; assigning a unique version number to each difference in the difference identification result, so as to obtain version update records; and on the basis of the version update records, using incremental hash table technology to perform data storage for each difference. The present application has a higher update efficiency without the risk of omission; and by means of difference analysis and by using incremental hash table technology to store difference data, the present application significantly reduces data storage space requirements, and also improves data access speed.

The invention relates to an AI-based supply chain demand prediction and inventory optimization method and system, and the method comprises the following steps: calling a sales record from a supply chain, recognizing a periodic demand rule of a corresponding commodity, and predicting an estimated demand quantity in a future time period according to the periodic demand rule; carrying out supply and demand difference analysis by combining the current warehouse commodity stock margin, and judging the stock state; if the commodity stock surplus exists, making a corresponding stock digestion strategy; if a shortage quantification result appears, carrying out key degree evaluation and urgency sorting based on a shortage amount in combination with market factors, and generating a key commodity list and an out-of-stock urgency index; and finally, in combination with a preset commodity constraint condition, according to the key commodity list and the urgency index, an optimal replenishment scheme meeting resource and time limit is formulated, and the technical problem of how to realize conversion from passive response to active pre-judgment in a supply chain environment with large demand fluctuation and complex influence factors is solved.

The invention relates to the technical field of anti-collision systems, in particular to an offshore wind power construction safety pre-warning system based on AIS (automatic identification system) data, which comprises a ship dynamic uncertainty modeling module for acquiring AIS signal updating frequency and positioning precision marks of a target ship and generating a ship future position probability ellipse. According to the invention, the position coordinate, the speed value and the course angle of the ship are obtained in real time based on the AIS data, the reliability and the motion trend of ship position prediction are determined by combining the AIS signal updating frequency and the positioning precision mark, and the future position probability ellipse of the ship is accurately generated; a protection area is dynamically constructed, comprehensive calculation is carried out in combination with the spatial relation between a ship future position probability ellipse and the positions of surrounding fan pile foundations, and a hourly dynamic collision risk index sequence is obtained; and further according to the statistical deviation between the current motion state of the ship and the standard parameter of the function partition, combining with path difference analysis to obtain a navigation abnormity comprehensive index.

The invention provides a network security malicious code binary search method and system, and relates to the technical field of data processing, and the method comprises the steps: calculating the multi-dimensional structural similarity between a to-be-detected binary file and each standard binary reference file based on a function level control flow semantic feature vector; determining a finally matched standard binary reference file according to the multi-dimensional structural similarity; performing fine-grained difference analysis on the binary file to be detected and the finally matched standard binary reference file to obtain a fine-grained difference analysis result; and on the basis of a fine-grained difference analysis result, in combination with sensitive data operation behavior feature detection, judging whether the to-be-detected binary file is a maliciously tampered version, and positioning a malicious code injection point. According to the method, the defects that in the prior art, dependence on fixed features is too high, and compilation optimization is sensitive are overcome.

The invention discloses a spare power automatic switching device test switch simulation test system, and belongs to the technical field of power grid simulation test. Probability distribution generated through kernel density estimation covers a fault scene of a 99% confidence interval, and the characterization capability of an extreme scene is enhanced; the time delay precision of a switch action sequence is controlled timely and reliably by combining the global search capability of quantum annealing and the local fine tuning of the particle swarm algorithm, and equipment damage caused by time sequence dislocation is avoided by combining the UWB technology and the phase compensation algorithm; through an objective function weight coefficient and a closed-loop feedback mechanism, an optimization objective can be dynamically adjusted according to a fault type, through real-time comparison of a physical device and digital twinning and through logic criterion goodness of fit analysis, control logic consistency can be guaranteed, and through loop response time difference analysis and two-dimensional index quantification, verification precision can be guaranteed. And the strict requirements of the power system on correct logic and quick action of the spare power automatic switching device are met.

The invention relates to a large silo coal blending analysis system, and belongs to the technical field of coking. The system comprises a silo coal resource access statistics module, a switching analysis module, a coal blending ratio difference analysis module, a coal blending and coke quality prediction module and an information display module. Firstly, the silo coal seam distribution condition is established, then the coal seam resource switching condition is analyzed and judged according to the discharging weight, the accumulated coal blending execution deviation rate is calculated, and the coal blending amount and the switching condition of the next period are estimated; the blended coal and coke quality prediction module predicts the quality and analyzes the change condition according to the actual coal blending ratio and the like; and the information display module stores and visually displays the result. The system has strong analysis and prediction capabilities, and can comprehensively and deeply analyze yesterday coal blending conditions, scientifically predict coke quality, intelligently plan today coal blending by means of accumulated coal blending execution deviation rates, simply, conveniently and quickly grasp dynamics and trends, guide coal blending and quality control, improve product quality, reduce cost and enhance competitiveness.

The invention discloses a project quality detection method and system based on green building design, and relates to the technical field of project quality detection. The engineering quality detection method and system based on the green building design comprises the steps that S1, BIM structured data, real-time monitoring data, structure acceptance data and construction event and window data are preprocessed; s2, on the basis of BIM structured data and in combination with a BIM model, the qualification state of the component and the quality grade of the partition are judged; s3, identifying a working condition switching anchor point and an event, and performing segmented division of a working condition process; s4, feature clustering and performance state discrimination are carried out, different working condition types are identified, and tagging management is carried out; s5, identifying dominant factors and performing attribution assignment through multi-dimensional label attribution and traceability judgment; and S6, performing grade judgment and grade response through multi-source time sequence item-by-item difference analysis. The problems of state interval disjunction and difficulty in accurate attribution and stable diagnosis caused by space-time mismatching of construction progress, BIM nodes and energy consumption environment data and data asynchronization are solved.

The invention provides a factory three-dimensional digital twin model reconstruction and incremental updating method for industrial space intelligence, and the method comprises the steps: obtaining a factory multi-view basic image for a factory panoramic scene, so as to train a bifurcated structure neural implicit field network containing a radiation field branch and an SDF branch, and generating an initial three-dimensional digital twin base; acquiring factory real-time inspection images acquired by the inspection robot under different inspection poses, rendering the initial three-dimensional digital twin base by using a radiation field branch to obtain a virtual reference view, and performing difference analysis on the virtual reference view and the factory real-time inspection images to position a structural change area in a factory; determining an axis alignment bounding box for changing the physical range of the entity in the area, taking the axis alignment bounding box as an effective boundary of the local space patch, and determining matched radiation field network weight and SDF network weight according to the effective boundary; and adjusting the radiation field network weight and the SDF network weight, and updating the radiation field network weight and the SDF network weight to the network in an incremental updating manner to generate a factory three-dimensional digital twinning model based on the implicit three-dimensional geometric field.

The invention belongs to the technical field of environmental risk assessment, and particularly discloses a BIM-based fabricated steel structure assembly scheme comparison and selection method and system, and the method comprises the steps: building a three-dimensional building model based on BIM software, and extracting component information and GIS data; establishing national and local standard libraries, matching applicable standards through building positioning information, and generating parameterized assembly rules; generating a plurality of assembly type combination schemes according to rules and component logic, and interactively binding with the BIM model; calculating an assembly rate and a standard score of each scheme, and screening candidate schemes meeting structural safety and a cost threshold value; and constructing an incremental cost library, completing cost difference analysis of the candidate schemes, and outputting an optimal assembly type steel structure combination scheme. And data driving and automatic comparison and selection in the whole process are supported, the method can be applied to prefabricated building scheme design and optimization links, and the design efficiency and the scheme economy are improved.

The invention discloses a business question answering method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining source domain and target domain data sets corresponding to new and old businesses of an electric power business hall, and extracting subsets to form a differential training set; determining a semantic association distance based on the difference between the vocabulary feature vector and the word vector, and obtaining a clustering cluster semantic association difference analysis value in combination with the similarity between the inter-cluster vocabulary semantic association distance and the text topic vector after the word is clustered; the vocabulary topic distribution conditions of different data set clustering clusters and the analysis values are fused, and the overall semantic feature values of the vth topic of the source domain and the kth topic of the target domain are calculated; determining attention weight and establishing a matrix, and generating a migrated intelligent language model by combining the two types of data sets; and answering can be obtained by inputting the questioning service text. The method can improve the accuracy of the output reply of the intelligent language model.

The invention discloses a rich text multi-dimensional difference analysis and accurate revision method and system based on AI, and relates to the technical field of artificial intelligence and data analys.The rich text multi-dimensional difference analysis and accurate revision method comprises the steps that firstly, a rich text file is analyzed, a document structure is reconstructed, vectorization and key information labeling are conducted on semantic blocks, and structuralization and semantic enhancement of a text are achieved; the method comprises the following steps of: firstly, carrying out text surface layer, semantic deep layer and structure association dimension difference analysis in parallel, then carrying out system knowledge graph-based revision influence degree evaluation on the basis of difference analysis, tracing associated terms through penetrating analysis, calculating an influence degree score and early warning potential conflicts, and automatically generating accurate revision suggestions; visual difference preview and one-key generation of a revised draft are provided, a closed loop from problem discovery to problem solving is realized, and the efficiency and accuracy of system revision are greatly improved.

The invention relates to a novel power distribution system data mining processing method and system based on transfer learning, and the method comprises the steps: collecting multi-dimensional operation data of a source power distribution network and a target power distribution network, carrying out the feature extraction of the multi-dimensional operation data, and forming a corresponding feature set; training the load prediction model of the source power distribution network to obtain a trained model, and performing knowledge extraction and mobility evaluation on the trained model; carrying out comparison loss measurement on the feature sets of the target power distribution network and the source power distribution network, and then carrying out comparison loss extraction and difference analysis; based on a difference analysis result, designing an adaptive transfer learning model, and performing adaptive adjustment on the structure of the target power distribution network load prediction model; and migrating the parameters of the source power distribution network load prediction model to the target power distribution network, and reducing the cross-domain distribution difference through a distribution alignment mechanism. Through a customized migration strategy, the method has stronger generalization ability and adaptability in a heterogeneous data scene of the power distribution network.

The invention belongs to the technical field of glioma image recognition, and discloses a glioma area rapid recognition method and system based on a medical image. The method comprises the following steps: acquiring a multi-modal image sequence of a brain to be detected; performing weighted fusion on the multi-modal image sequence to generate a fused image; performing gray asymmetry analysis on the fused image, and identifying an asymmetry salient region of the fused image; performing texture difference analysis on the fused image, and extracting a high-difference region of the fused image; performing spatial intersection operation on the asymmetric salient region and the high-difference region, and taking a spatial intersection operation result as a glioma suspicious region; and carrying out dynamic region growth segmentation on the glioma suspicious region, and rapidly outputting a glioma region boundary. According to the method, dual feature screening of gray and texture is combined with dynamic region growth segmentation, the tumor infiltration boundary is accurately captured, the positioning precision is improved, and the false positive rate of recognition is reduced.

The invention relates to the technical field of reinforcement learning, in particular to an intelligent task decision-making and execution optimization method based on multi-modal perception fusion and dynamic feedback, which comprises the following steps of: analyzing space coordinates and brightness difference to construct a dynamic scene graph by collecting and fusing multi-modal data such as visual laser radar torque and completing filtering normalization; the method comprises the following steps: acquiring a task target extraction target area and a reachable area, generating an action sequence in combination with a mechanical arm pose decomposition task, weighting according to joint angle deviation to form an initial trajectory, and performing prediction control rolling optimization of an execution trajectory in combination with a real-time joint state sequence. Vision, laser radar and force sense data synchronous representation is enhanced through multi-modal fusion, a dynamic scene graph is constructed in combination with spatial difference analysis and category division, a task action sequence is generated, a track is corrected, a continuous closed loop of perception, decision and execution is formed, and the problems of insufficient environmental representation, task decomposition stiffness and track adjustment lag are solved.

The invention relates to the technical field of mold detection, and discloses a special working state inner wall detection device for a neutral borosilicate molded bottle mold, which comprises a workbench, an opening and closing mechanism is arranged on the middle side of the top of the workbench, a clamping mechanism is arranged on the top of the workbench, and a six-degree-of-freedom mechanical arm is mounted on the rear side of the top of the workbench. A ceramic probe is arranged on the outer side of the six-degree-of-freedom mechanical arm, and a base fixing seat is fixedly connected to the outer side of the ceramic probe. A real-time image differential analysis module is arranged, a blowing and powder spraying mechanism is used for carrying out pneumatic excitation on a suspected defect area, and a multispectral endoscope module is controlled to respectively collect optical images before and after excitation; by calculating the normalized difference measure of the two images and comparing the normalized difference measure with the preset physical displacement threshold value, the non-solid-phase attachments displaced due to pneumatic excitation and the solid-phase defects with fixed positions can be distinguished, and the technical problem that two abnormal areas with different properties are difficult to effectively classify in the prior art is solved.

The invention discloses a metadata version control and automatic structure comparison method and system based on incremental snapshot and intelligent decision, and the method comprises the following steps: managing a metadata version through an incremental snapshot model, and enabling the incremental snapshot model to support the complete backtracking of a historical structure through storing changed incremental information and associating with a version chain; carrying out difference analysis on the metadata structure by adopting a hierarchical progressive comparison algorithm; an intelligent DDL decision engine is adopted, and an executable DDL script is generated according to the difference analysis result; in the process of generating the DDL script, metadata consanguinity information is jointly checked so as to carry out change risk assessment. Through collaborative design of all the modules, double benefits of systematic breakthrough and conventional effect enhancement are brought, and the technical effect is directly associated with collaborative design.

The invention discloses a protocol message tamper-proofing method and system based on symmetric encryption and a medium, and relates to the technical field of industrial automation Ethernet time synchronization. According to the method, mirror image monitoring is carried out on the message receiving and sending process in the protocol processing process of time synchronization equipment, a protocol message is obtained and analyzed, and the protocol message tamper-proofing effect is achieved; a message abstract and encrypted verification data thereof are generated at a sending end, and a corresponding abstract is obtained through decryption at a receiving end; consistency comparison is carried out on the sending side abstract and the receiving side abstract based on the time window, and a tamper-proof consistency coefficient is calculated to judge the integrity of the protocol message; on the basis that the integrity is qualified, performing difference analysis on an encryption verification result, and calculating an encryption credibility coefficient to evaluate the credibility state of the symmetric encryption link; and further performing coupling calculation to obtain a time synchronization security coupling coefficient, comprehensively evaluating the influence of tamper-proofing and symmetric encryption on the time synchronization operation security, and implementing a security regulation and control strategy according to the influence, thereby improving the security and stability of the time synchronization system.

The invention relates to the field of firmware upgrading, in particular to a firmware upgrading method and system based on cloud computing. The method comprises the following steps: identifying equipment firmware configuration information based on a cloud, performing module layer version information difference analysis, and generating version difference information of each module layer; performing increment updating range analysis according to the version difference information, and extracting an upgrading increment package of each module; carrying out personalized adaptation customization and firmware operation compatibility verification on the upgrade increment package, and constructing an executable upgrade task package; and carrying out adaptive decomposition and fragmented time period updating processing on the executable upgrading task package. According to the method, accurate, efficient and safe firmware increment upgrading is realized through cloud computing, and the operation stability of equipment is improved.

The invention relates to the technical field of plate processing production management and industrial data processing, in particular to a plate production order management system based on edge sealing drilling, which comprises an order data acquisition step: constructing a holographic data input layer, and acquiring a process data set and real-time performance process data; a performance benchmark construction step: establishing a dual reference system, generating an ideal performance time benchmark, and generating theoretical performance delay evaluation data in combination with a process complexity parameter; a performance difference analysis step: separating the noise and the signal, and respectively calculating an actual performance deviation and a theoretical performance deviation only containing a process complexity factor; an order state judgment step: analyzing the distribution mode similarity of the deviation, if the distribution mode similarity is higher than a threshold value, judging that compliance process delay exists and the delivery time is adjusted, and if the distribution mode similarity is lower than the threshold value, judging that abnormal performance risk exists and generating a management instruction; according to the method, confusion of processing endogenous complexity and exogenous abnormity is successfully stripped, and fine attribution oriented management is realized.

The invention discloses an intelligent robot integrated debugging system based on digital twinning, and the system comprises a model building module which is used for building a digital twinning model, collecting data, and generating a virtual mapping body; the structure analysis module is used for carrying out structure analysis on the virtual mapping body and constructing a simulation data set; the virtual debugging module is used for performing virtual debugging according to the simulation data set, generating action track data and constructing a debugging instruction set; the feature extraction module is used for extracting an image feature set of an instruction execution process; the difference analysis module is used for comparing the image feature set with the action track data and constructing a difference feedback matrix; and the circular updating module is used for updating the digital twin model and starting a new round of virtual debugging and instruction generation process. According to the invention, digital twinning, AI vision and trajectory clustering technologies are fused, and an intelligent robot debugging closed-loop system with high intelligence, high efficiency and high-precision feedback capability is constructed.

The invention relates to the technical field of computer vision and industrial equipment fault diagnosis, in particular to a fault image diagnosis system for a remote controller of a bolter miner driven by a CMC chip. Comprising a data sensing module for synchronously acquiring a CMC chip internal logic state vector and a real-time observation image, and preprocessing to obtain target visual data; the generative reconstruction module maps the logic state vector to a high-dimensional space to generate an ideal feature map; the visual analysis module is used for extracting an observation feature map through a convolutional neural network, generating an interference distribution mask based on frequency domain texture statistics, and identifying an unstructured environmental noise region; the difference analysis module is used for calculating a semantic residual image by combining the ideal feature map, the observation feature map and the interference distribution mask, and generating an image difference analysis result; according to the method, ideal features are generated by using the internal logic state vector of the CMC, and the residual calculation of the coal dust noise area is shielded by the interference mask, so that the false alarm caused by the environmental noise is effectively eliminated, and the closed-loop verification that what you see is what you control is realized.

The embodiment of the invention provides a database table structure repairing method and device, equipment, a medium and a product, and relates to the field of big data. The method comprises the steps of obtaining connection information of a source database and a target database; based on the connection information, obtaining first table structure metadata of a data table of the source database and second table structure metadata of a data table of the target database. And comparing the first table structure metadata with the second table structure metadata to obtain table structure difference information of the source database and the target database. And based on the table structure difference information, obtaining a table structure repair suggestion of the target database by utilizing a difference analysis model constructed based on a large language model. And repairing the table structure of the target database according to the repairing suggestion. According to the method, the database table structure difference is automatically and intelligently recognized and repaired, the efficiency and accuracy of database table structure consistency maintenance are greatly improved, and errors possibly caused by manual operation are reduced.

The embodiment of the invention relates to the field of intelligent ship planning, and discloses a ship man-machine collaborative planning method, device and equipment and a storage medium, and the method comprises the steps: obtaining the historical ship configuration information of different types of ships; constructing a shipping labor knowledge graph according to the historical ship configuration information; performing difference analysis by using the shipping labor knowledge graph to obtain difference reason analysis information, and updating the shipping labor knowledge graph; obtaining target ship configuration information of the target optimized ship; analyzing the target ship configuration information by using the updated shipping labor knowledge graph, and generating a plurality of candidate ship equipment replacement schemes; and optimizing each candidate ship equipment replacement scheme to obtain an optimal candidate ship equipment replacement scheme. According to the method disclosed by the invention, the problem that ship man-machine cooperation resources are difficult to reasonably plan is solved, comprehensive and intelligent optimization analysis is carried out on the ship man-machine cooperation scheme, and efficient, safe and low-cost crew substitution planning is realized.

The invention relates to a medical quality control dynamic scoring system, device and equipment based on multi-modal perception and federal evolution, and the method comprises the steps: obtaining original scene information through multi-modal input based on a medical equipment recognition model, carrying out the scene analysis and semantic fusion, generating structured medical scene data, and carrying out the dynamic scoring of the medical quality control according to the structured medical scene data. Multi-source evidence verification is carried out through a medical scoring rule base, a quality evaluation result is generated through weight dynamic adjustment, difference analysis is carried out through comparison with a manual correction result according to the quality evaluation result, and model parameters and scoring rule updating are generated. Multi-modal input is fused based on a medical special perception layer, anti-interference scene analysis and equipment semantic binding are achieved, multi-source evidences are verified in real time through a dynamic scoring engine, deduction weights are dynamically adjusted, subjective item scoring floating is compressed, an identification model is updated through federation, and a rule base is thermally loaded in real time, so that the anti-interference scene analysis and equipment semantic binding is achieved. And automatic closed-loop processing of problem items is realized.

The invention discloses an anomaly detection method and system based on image alignment and feature difference analysis, and relates to the technical field of computer vision and industrial automation detection, and the method comprises the steps: obtaining a to-be-detected image and a reference image, and carrying out the image alignment processing of the to-be-detected image and the reference image; obtaining a region of interest corresponding to the reference image, wherein the region of interest is a preset region; cutting in the aligned to-be-detected image according to the region of interest to obtain a local image corresponding to the region of interest; obtaining a reference feature corresponding to the region of interest, wherein the reference feature comes from a pre-established reference feature library; extracting features of the local image as to-be-detected features; and comparing the to-be-detected feature with the reference feature to obtain a comparison result, and judging whether the target part existing in the local image is abnormal or not. The problem of dependence of offset interference and abnormal samples is solved, and the method is adaptive to multiple industrial scenes.

The invention relates to the technical field of remote sensing surveying and mapping, in particular to a three-dimensional terrain reconstruction method and system based on a remote sensing image, and the method comprises the following steps: collecting visible light and near-infrared three-dimensional multispectral data, carrying out pixel-level registration based on geometric calibration, constructing a geometric registration multispectral image matrix, generating waveband difference, and extracting a structure edge; the method comprises the following steps of: constructing a spectral signal diffusion impedance field, forming a terrain self-adaptive matching support domain, calculating a multispectral matching parallax error, and resolving a three-dimensional terrain reconstruction model based on space forward intersection, in the method, the terrain boundary recognition capability is enhanced through multispectral geometric registration and waveband difference analysis, and stable edge features are extracted in combination with gradient amplitudes; the matching process adapts to topographic fluctuation changes, signal diffusion impedance constructed based on spectral difference restrains a matching support domain form, cross-ground object interference is suppressed, parallax calculation stability is improved, and three-dimensional elevation and structure expression reliability under complex earth surface conditions is enhanced.

The invention relates to an aero-engine fault diagnosis method and device based on tensor decomposition and a medium, and the method comprises the steps: collecting the gas path parameter time sequence data of a plurality of parts of an aero-engine, and carrying out the time alignment and working condition label labeling; for the multi-parameter data of each component, a kernel principal component analysis and automatic encoder fused feature extraction method is adopted, and parameters of different components are unified into fixed dimension features; the feature matrixes obtained after feature extraction of all the components are combined, and a time-component-feature third-order tensor is constructed; training a high-order singular value decomposition model based on the engine health monitoring data; fault diagnosis is carried out by calculating the reconstruction error of the test data and the monitoring data; and fault positioning is realized by combining core tensor difference analysis. According to the method, the problem of feature fusion of engine multi-source heterogeneous data under variable working conditions is solved, and the engine fault detection sensitivity and positioning precision are improved.

The invention relates to the technical field of tumor marker detection, in particular to a breast cancer lung metastasis related biomarker screening system which comprises a differential genetic factor mining module, a function association module, a verification screening module, an interference elimination module and an optimization integration module. According to the method, the candidate genetic factors highly associated with lung metastasis are extracted, and the expression fluctuation characteristics are combined to carry out difference analysis, so that the preliminary screening accuracy is improved, pathological information and pathway annotation are integrated to construct an action network, pathway weights are analyzed, and functional expressions of the candidate factors are quantitatively evaluated; an independent sample is called to verify transcription consistency and clinical relevance, interference factors with poor repeatability are eliminated, non-tumor tissue high-expression interference items are rejected in combination with background transcription characteristics, the specificity and adaptability of screening results are improved, and finally a marker set with metastasis mechanism indicating significance and prognosis prediction value is formed through comprehensive evaluation. And clinical transformation support is provided for identification of lung metastasis of breast cancer.

The invention discloses an MBSE model version pedigree iteration method and system based on a graph theory and a knowledge graph. The method comprises the following steps: constructing an MBSE model of an aerospace craft and mapping the MBSE model into an attribute graph; a directed acyclic graph is adopted to record a version iteration process, management is carried out through a version number system comprising a main version number, a combined version number and a revised version number, and a differential storage strategy is adopted; and performing change detection and merging based on a baseline, accurately identifying changes through a model comparison algorithm including internal attributes, internal relationships, overall relationships and difference analysis, and processing conflicts in collaborative design. According to the method, atomic-scale version control is realized, the problems of missing change traceability, low verification efficiency and multi-baseline conflict are solved, and the efficiency and quality of aerospace craft full-life-cycle model management are improved.