29 results about "Structure comparison" patented technology

The invention discloses a smart park digital twinborn management platform and a virtual-real interaction method, and belongs to the technical field of park management. Structural states, equipment behaviors, environment disturbance and user activity data of entity objects are hierarchically collected according to frequency, and a plurality of digital twinborn models are synchronously constructed based on a scene labeling mechanism; the platform can generate a control strategy and mark a prediction channel according to the model evolution trajectory, then acquire entity response and perform graph structure comparison with a prediction path, identify response deviation and generate a deviation graph; the platform further constructs an error learning weight according to the deviation map, drives a twin model to perform progressive optimization adjustment of confidence parameters, and can trigger structure-level network evolution to realize dynamic enhancement of a model structure and prediction capability; compared with the prior art, the invention provides a smart park digital twinning implementation scheme supporting virtual and real closed loops, self-learning evolution and structure reconstruction.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a database data verification method which comprises the following steps: configuring source database connection parameters and target database connection parameters, setting comparison task parameters, and associating the comparison task parameters with corresponding database connection parameters; determining a source table and a target table corresponding to the source table identifier and the target table identifier, executing table structure comparison to generate a structure difference record, determining a data range according to a comparison mode parameter, executing data volume comparison to generate a quantity difference value, determining a data sampling strategy, and performing content comparison to generate a feature identifier comparison result; and finally, integrating the structure difference record, the quantity difference value and the feature identification comparison result to generate a verification report. According to the method, the data range and the sampling strategy are driven by comparing the mode parameters, so that the integrated processing of structure comparison, quantity comparison and content comparison is realized, and the accuracy and efficiency of data synchronization verification are improved in a heterogeneous database environment.

The invention discloses a rapid imaging method and system for a multi-time-sequence magnetic resonance image group, particularly relates to the technical field of multi-time-sequence magnetic resonance image processing, and is used for solving the problems of low imaging speed and poor time sequence consistency. According to the method, sampling reference distribution is constructed in a frequency domain, the reconstruction difficulty is predicted by using graph convolution, a multi-scale under-sampling mask is generated, and sampling is distributed according to channel sensitivity, so that high information priority and sparse controllability are realized; sending the registered sparse data into a space-time-parameter three-domain network, extracting structural, dynamic and parameter characteristics, and obtaining an image group with a clear structure and a stable time sequence through cross-domain fusion, non-rigid body registration and wavelet domain artifact suppression; and forming a comprehensive score by using four indexes output by the quality scoring network, performing reinforcement learning feedback, adaptive adjustment of a sampling rate, a mask, a reconstruction parameter and closed-loop optimization, and finally outputting the comprehensive score together with a sequence parameter, a timestamp and a score, and generating a structure comparison diagram and a time curve to facilitate quality control and presentation.

The invention discloses a spectrum and molecular structure comparison matching system based on machine learning, and relates to the field of spectrum intelligent analysis, and the system comprises a model construction module, a training optimization module, a calculation candidate module, and an interpretation visualization module. According to the method, the deep semantic features of the spectrum and the structure are automatically extracted by constructing the multi-modal deep learning model, and the accuracy and robustness of spectrum analysis and molecular structure matching are greatly improved. A shared embedding space learning strategy is adopted, different modes are projected to the same feature space, and unified matching and similarity scoring are achieved. An attention mechanism is introduced, visual mapping between spectrum peaks and molecular structure fragments is achieved, understanding of corresponding chemical groups or atoms behind each spectrum peak is facilitated, and interpretability of a matching result is enhanced.

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 federal learning model leakage traceability method based on model structure confusion, and the method comprises an initialization step: S1, a server copies an initial model for subsequent structure comparison, and generates a unique binary user identity (UID) for each client; a UID embedding step S2, before each round of training is started, independently executing structure confusion for each client model by the server, embedding a client UID into a model structure, and then issuing the model to the client; a model structure recovery step S3, when one round of training is finished, the server executes structure recovery on each client model, and then executes model aggregation; and S4, when a model ownership owner doubts that a model with an unknown source comes from leakage in a training process, the structure of the model is detected, and a suspicious UID is extracted through structure comparison with an initial model so as to find a leakage person. The method has the characteristics of no negative influence on the performance of the original model, low embedding time overhead, high robustness and the like.

The invention relates to the technical field of technical gene detection, in particular to a recombinase and recognition site screening method and system based on structure classification prediction.The method comprises the steps that to-be-matched recombinase is obtained for structure resolution prediction.The functional domain of the to-be-matched recombinase is obtained; searching in a first database according to the functional domain, searching candidate recombinase of which the similarity meets a preset condition, and screening to obtain optimal recombinase; determining an interaction region of the current large serine recombinase and the target DNA sequence from a second database, and sequentially obtaining interaction amino acid sequences corresponding to the preferable recombinase; and matching with the amino acid characteristic sequence of the current large serine recombinase in the second database to obtain the target large serine recombinase with the highest similarity in the preferred recombinase and the corresponding recognition site sequence. According to the method, the structure of the large protein is subjected to structure comparison mining and splitting, and recognition site prediction is performed on interaction region amino acid characteristics, so that the research and development period is shortened, and the research and development cost is saved.

The invention discloses a medical diagnosis optimization method and system based on big data, and relates to the technical field of diagnosis optimization. According to the symptom intensity transition criterion and the collapse mechanism, the target path with the highest diagnosis priority can be quickly focused in the multiple possible diagnosis paths, and the accuracy of preliminary judgment is improved; interference correction is carried out on inconsistent parts between diagnosis paths and medical rules by adopting structural comparison and conflict degree calculation means, so that misjudgment caused by logic deviation or local abnormality is avoided; besides, through construction of a consistency verification graph and a forward and reverse path consistency scoring mechanism, bidirectional verification and screening of the overall structure of the diagnosis path are realized, so that the output path has logic rationality and clinical feasibility.

The invention discloses a data comparison method and device, electronic equipment and a storage medium. Obtaining a first type of field metadata from the reference data table according to a predefined standardized metadata obtaining method, and obtaining a second type of field metadata from the to-be-analyzed data table; according to the first type of field metadata, the second type of field metadata and the specified dimension metadata, calculating the field similarity between the first type of field in the reference data table and the second type of field in the to-be-analyzed data table, and according to the field similarity, realizing structure comparison between the reference data table and the to-be-analyzed data table; and acquiring the current reference data record and the current to-be-analyzed data record according to a predefined fragmented data acquisition method, and performing field content comparison on the current reference data record and the current to-be-analyzed data record to realize content comparison of the reference data table and the to-be-analyzed data table. According to the technical scheme, the compatibility of heterogeneous data is improved, the large-scale data processing capacity is improved, and comprehensive difference analysis is achieved.

The invention discloses a bid invitation service information management method and system based on intelligent risk assessment, and relates to the technical field of information management, and the method carries out hierarchical preliminary and secondary risk assessment through three complementary risk indexes, i.e., a behavior path deviation score Rbp, a behavior resonance index Rcorr and synchronous behavior intensity Rsync, in combination with a set threshold value. Particularly, by introducing the scoring model constructed by multi-source parameters such as the editing distance, the residence time difference degree and the asynchronous behavior frequency of the user behavior path diagram, whether the user has a strategic access behavior or an unconventional process avoidance behavior can be effectively identified. Meanwhile, on the basis of a behavior resonance index Rcorr and synchronous behavior intensity Rsync calculated based on a resonance feature vector set, mining of organizational bidding features such as behavior coordination, access synchronization and path multiplexing among bidding groups is achieved, and the method has time modeling capacity, path alignment capacity and graph structure comparison capacity.

The invention relates to the technical field of industrial detection data processing, and discloses a coal detection data calculation and analysis system based on multi-agent reinforcement learning and knowledge graph fusion, which comprises a priori constraint domain construction module, a state space mapping module, a multi-agent cooperative calculation module and a strategy game and fusion output module, according to the system, a calculation framework embedded with a coal physical and chemical topological graph is constructed, the dynamic game of a sensing agent and a cognitive agent is utilized, and feature reweighting and graph path searching are executed under the constraint of a physical rule. Based on the verification capability of the system on the causality of a reasoning path, the problems of logic collapse and pseudo-correlation reasoning caused by lack of physical constraints of a data-driven model under the working conditions of strong noise and small samples are effectively solved, and the logic self-consistency and environmental stability of heterogeneous material detection are improved.

The present application relates to the technical field of smart forestry and under-forest planting planning, in particular to a kind of under-forest ginseng ecological niche space layout intelligent optimization method, comprising: benchmark construction and simulation steps: obtain forest land data to construct ideal habitat capacity model to generate potential energy grid chart, and carry out virtual planting simulation to generate simulated output data;Double-track residual generation step: generate real residual matrix in combination with historical data and potential energy chart, generate theoretical residual matrix in combination with simulation data and potential energy chart;Structure comparison and optimization step: calculate matrix structure similarity;Logic determination step: in response to similarity greater than threshold, determine as spatial layout factor and execute rearrangement optimization;Otherwise, it is determined as environmental factor and generates improvement prompt;The present application realizes the accurate decoupling between the environment background and the space layout of the low yield reason.

The invention discloses a visualized comparison and selection model for a plate buckle frame supporting scheme and a use method, and the model comprises an input data modularization module, a self-weight calculation module, a bearing capacity calculation module, and a comparison and selection scheme thermodynamic diagram drawing module. The input data modularization module is used for forming a vertical rod interval combination, a step combination and an erection height on the basis of inputting range parameter data corresponding to the erection height, the standard step, the top layer step, the transverse interval and the longitudinal interval, and sequencing according to interval increment; the self-weight calculation module is used for carrying out accumulative calculation on the weights of the corresponding rod pieces in all the combined working conditions; the bearing capacity calculation module is used for calculating and obtaining bearing capacity data of the ring lock frame under all working conditions; the comparison and selection scheme thermodynamic diagram drawing module is used for drawing and outputting a thermodynamic diagram with the vertical rod interval combination as the longitudinal axis, the step pitch combination as the transverse axis and the color gradation corresponding to the bearing capacity data as the filling color. The problem that different structures corresponding to different supporting schemes of the disc buckle frame are inconvenient is solved.

The present invention discloses a spectrum and molecular structure comparison and matching system based on machine learning, which relates to the field of spectral intelligent analysis. The system includes a model construction module, a training optimization module, a candidate calculation module, and an interpretation visualization module. The present invention automatically extracts the deep semantic features of the spectrum and structure by constructing a multimodal deep learning model, thereby greatly improving the accuracy and robustness of spectral analysis and molecular structure matching. A shared embedding space learning strategy is adopted to project different modalities into the same feature space to achieve unified matching and similarity scoring. The introduction of an attention mechanism realizes the visual mapping between spectral peaks and molecular structure fragments, which helps to understand the chemical groups or atoms corresponding to each spectral peak and enhance the interpretability of the matching results.

The invention relates to the technical field of multi-modal RNA feature fusion and high-confidence data set construction, and particularly discloses a protein-RNA interaction prediction method based on multi-modal deep learning, which models and predicts an RBP binding mode, classifies cell line specific RBP-RNA interaction by applying a computing technology, and provides a method for predicting protein-RNA interaction based on multi-modal deep learning. An interpretable group of binding specificity between different cell lines is determined; establishing a cell line specific RNA structure similarity matrix by adopting a structure comparison and clustering technology; predicting the exact nucleotide binding positions of these sites as markers RBP; mRNA (messenger ribonucleic acid) and lincRNA are used as controls; the positive correlation between the RBP-RNA interaction and RNA translation, especially the positive correlation between the RBP-RNA interaction and the RNA translation, is established, a theory and a strategy are provided for cancer targeted therapy, the solution of data heterogeneity and the calculation complexity are reduced, and the prediction efficiency of the protein-RNA interaction is improved.

The application discloses a kind of human resource matching method and system based on machine learning, specifically related to human resource intelligent matching technical field, for solving the problem of dynamic human matching distortion risk big;The application collects post description, ability requirement, resume, project and interview feedback, completes standardization and time stamp calibration according to unified time reference, generates the dynamic representation pair of post state vector and candidate ability vector, the difference is extracted along the semantic structure comparison path and the ability evolution comparison path by matching representation generation model, form matching representation vector and output person-post recommendation pair sequence, continuously track recommendation pair, construct the feedback path atlas associated with post state vector, calculate structure offset and locate feature path segment, according to positioning correction parameter subblock, and update output logic by time sliding window to identify stability offset, realize the dynamic optimization and traceability of matching, reduce the risk of employment, improve the efficiency and accuracy of human resource matching decision.

The invention relates to the technical field of decision support systems, in particular to a cloud intelligent decision support system and method supporting heterogeneous data sources, and the system comprises a heterogeneous logic alignment module, a pressure parameter derivation module, a self-adaptive simulation deduction module, a computing power value evaluation module and a decision confidence quantification module. According to the method, by means of numerical field combination calculation and topological structure comparison, an attribute constraint graph is constructed to judge logic isomorphism, the problem that heterogeneous source semantics are fuzzy is solved, gradient disturbance parameters are generated based on sliding window statistical superposition pressure coefficients, and extreme scenes are simulated in a definition domain boundary. A high-frequency log stream and a low-frequency aggregation table are dynamically switched according to index deviation, high-granularity data support is guaranteed during abnormal fluctuation, resource occupation is reduced in a stationary period, the storage efficiency ratio is calculated in combination with CPU instruction cycle consumption and access counting, high-calculation-cost data is prevented from being mistakenly deleted, the risk opening and efficiency ratio is evaluated, the reliability of a decision scheme is quantified, and the reliability of the decision scheme is improved. And an explanatory confidence basis is provided.

The invention relates to a grating structure generation method and device, a grating coupler and a computer readable storage medium, and the method comprises the steps: carrying out the initial structure optimization processing of a preset grating structure in a grating generation region, and obtaining a plurality of first grating structures, each first grating structure being provided with a first initial structure and a second initial structure; comparing the first initial structure of each first grating structure with a preset first structure parameter to obtain a structure comparison result; based on the structure comparison result, performing structure processing on the first initial structures of the plurality of first grating structures to obtain a second grating structure; and performing secondary structure optimization processing on the second initial structure of the second grating structure to obtain a target grating structure. According to the grating structure generation method and device, the grating coupler and the computer readable storage medium, the performance balance between the coupling efficiency and the bandwidth is realized.

The invention discloses a database migration test method, device and equipment, and the method comprises the steps: designing and defining a unified programming interface through a JDBC standardized interface and driver decoupling, and loading a driver of a to-be-compared source database and a driver of a migrated target database through the interface, so as to establish the connection between the source database and the target database. And for different types of databases, unified access can be realized through the interface only by developing the driver of the database, so that the compatibility of the database types is improved. In the testing process, a user configures a table list comprising a source table name and a target table name which need to be compared, the table structures of the source table and the target table are automatically read according to the table list, the table structures are compared according to the configured field mapping rule, and a table structure comparison result is obtained. In addition, the table data comparison operation of the source table and the target table can be executed according to the table list to obtain a table data comparison result, and the verification effect of the data integrity in the data migration test process is improved.

The invention discloses AR scene experience equipment for furniture assembly, which comprises a hardware unit, and a modeling unit, an AR processing unit and an interaction unit which are in communication connection with the hardware unit, and is characterized in that the hardware unit adopts an integrated lightweight architecture; a calculation module with a processor as a core, a high-definition camera used for visual perception and display and a high-resolution display screen are integrated. By fusing gesture recognition, fine touch control of a pressure sensing knob, tactile feedback of a linear motor and spatial audio, a user can'grab ', 'pull' and'sense 'occlusion and separation of a virtual tenon-and-mortise structure in a mode close to reality, and by means of high-precision modeling and an AR rendering engine, the virtual tenon-and-mortise structure can be obtained. A complex tenon-and-mortise structure which is difficult to observe in traditional furniture is subjected to three-dimensional digital reduction and dynamic disassembly, an intelligent labeling module highlights key parts in real time, and a structure comparison module supports visual comparison with a traditional process.

The application discloses a power grid atlas maximum common subgraph discovery method based on seed-expansion heuristic search, which is used for topology structure comparison between power grid atlases in homologous physical power networks and different application scenes, discovers the maximum common subgraph and comprises the following steps: 1. constructing a similarity score function of nodes between atlases according to node labels and degrees of the atlases; 2. a power grid atlas global comparison method based on seed-expansion heuristic search, and then discovering the maximum common subgraph between atlases. The application converts two compared power grid atlases into undirected graphs, establishes corresponding comparison graphs, and then converts the structure comparison problem of two networks into a common subgraph problem, calculates the similarity between all nodes according to the defined node similarity measurement method and the topological structure relationship between nodes, and finally solves the problem by means of the seed-expansion-based heuristic search to obtain the maximum common subgraph between homologous power grid atlases.

Described herein are systems and methods for providing wager recommendations and wager comparisons based on a player prompt by preparing the input context of a large language model. A system can maintain an indexed data structure comprising wager scenarios for live events, each associated with a respective odds value. The system can receive, from a client device during a session identifying a first wager scenario, a prompt requesting a comparison to the first wager scenario. An input context can be generated using the prompt, data of the first wager scenario, and second wager scenarios retrieved by searching multiple indexes of the data structure. Using the language model and the input context, the system can generate an output message indicating the comparison between the first and second wager scenarios, and provide the output message to the client device in response to the prompt.

The invention discloses a spinosad synthetic strain metabolism model reconstruction method integrating protein structure comparison and application, and belongs to the field of system biology. The streptomyces albus mature GEMs are taken as a template, protein sequence comparison and structure comparison are comprehensively utilized, the gene (protein) homologous relationship of the streptomyces albus and the saccharopolyspora spinosa is established, and the high-quality saccharopolyspora spinosa GEMs are obtained by combining additional gene function annotation, gap filling and the like. The GEMs can systematically represent all metabolic enzyme functions of saccharopolyspora spinosa, accurate prediction from genotype to strain phenotype is realized, and systematic design research of saccharopolyspora spinosa cell factories is facilitated.

The invention provides cytosine deaminase SvSddA, a base editor containing the cytosine deaminase SvSddA and application of the cytosine deaminase SvSddA, the amino acid sequence of the cytosine deaminase SvSddA is shown as SEQ ID NO.1, SddA which is not reported yet is found near a branch of high-activity protein, the cytosine deaminase SvSddA serves as candidate protein to be further subjected to structure comparison, and the cytosine deaminase SddA from Saccharothrix violaaceirubra is selected as one of final candidate cytosine deaminase for activity evaluation on the basis of a structural comparison result, the editing efficiency of SvSddA at four nuclear target sites in HEK293T cells is detected, and efficient C-T editing efficiency is displayed at the position of a target, so that CBE containing SvSddA has the advantages of high activity, small size and the like, and the CBE can be used for preparing the CBE. Compared with other existing CBE, the method has obvious advantages.

The invention relates to the technical field of three-dimensional modeling, in particular to a natural resource earth surface matrix layer three-dimensional modeling system which comprises a density profile construction module, a granularity regulation and control calculation module, a structure node correction module, an attribute sequence extraction module and a hierarchy template generation module. According to the method, by obtaining rock core drilling lithologic paragraphs and dry density data, constructing a density sequence and recognizing the change trend, density-driven section segmentation expression is achieved, the structure division precision is improved, space coordinates and construction parameters are combined, the voxel grid size and the layout mode are regulated and controlled, the modeling granularity is matched with geologic features, and the modeling precision is improved. Extracting an included angle between a node and a fault vector in an intersection area; matching a correction factor and correcting a coordinate; enhancing the reasonability of structure expression; performing attribute processing to extract master control lithology and sort the lithology, constructing a difference matrix, enhancing attribute structure comparison logic, identifying a representative area by minimum difference variance, and extracting naming logic and a layering rule; and multi-region expression standard unification and model adaptability improvement are realized.

The invention discloses a multi-structure comparison pile pushing test method for a large-section circular anti-slide pile, and belongs to the technical field of geotechnical engineering model tests. The method comprises the following steps: a model preparation stage: designing and preparing a model pile and a slope body material based on a strict similarity theory, and installing an autonomous friction resistance reducing system; in the accumulation test stage, a single-row pile test, a multi-type pile comparison test, a double-row pile test and a portal pile test are sequentially conducted on the same slope body model, and the structure is changed from simple to complex; in the decline test stage, a single-row cantilever pile test and a side friction resistance test are conducted in sequence, and the structure is simplified. According to the invention, through the closed-loop test logic of accumulation-decline, systematic comparison of various slide-resistant pile structural forms is realized on one set of model, the test efficiency is high, and the data comparability is strong; systematic similar design is integrated, the friction resistance reduction and test technology is innovated, the test precision and authenticity are effectively improved, and a comprehensive and reliable test means is provided for design optimization and theoretical research of the large-section circular anti-slide pile.

The invention discloses a lightweight heterogeneous database structure migration method, apparatus and device, and a program product. The method comprises the steps of obtaining a table structure definition statement DDL from a source database; the DDL is analyzed into an abstract syntax tree AST; traversing the AST by adopting a visitor mode, and identifying and converting structural elements in the AST to generate a target DDL conforming to a target database dialect; wherein the conversion at least comprises intelligent data type mapping based on semantic similarity; executing the target DDL in the target database; according to the method, metadata is obtained by directly querying a system table or a metadata view of a source database; the method further comprises a migration execution control step, namely performing parallel processing on a plurality of Schema by taking a database mode Schema as a concurrent processing unit; after obtaining the metadata, applying a filtering rule based on black and white list and / or mode matching; the method further comprises a structure comparison verification step. The method has the advantages that the DDL translation and structure conversion precision is greatly improved, and the lightweight architecture is optimized to the greatest extent.

The invention provides a DOM (Document Object Model) structure comparison method and device for DOM reconstruction, equipment and a medium, and the method comprises the following steps: when a remote browser opens a set website, injecting a JavaScript code; the JavaScript code obtains first HTML (Hypertext Markup Language) content of the current page; when the user operates the page, the operation is synchronized to the remote browser, and second HTML content of the current page of the remote browser is obtained at the same time; analyzing the first HTML content to obtain a first DOM structure, analyzing the second HTML content to obtain a second DOM structure, comparing the first DOM structure with the second DOM structure to obtain a comparison result, and then caching the second HTML content; the comparison result is sent to the client, and the client directly performs incremental updating of the current page according to the comparison result; and the method is suitable for scenes requiring accurate DOM updating.

The application provides a database migration method and device, equipment and storage medium, relates to the technical field of database, can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving, and includes the following steps: acquiring first data table information and first view information of a source database and second data table information and second view information of a target database respectively; generating a table creation statement of a first data table corresponding to the source database according to the first data table information and the first view information; generating a table creation statement of a second data table corresponding to the target database according to the second data table information and the second view information; comparing the table creation statement of the first data table and the table creation statement of the second data table by string comparison to obtain a table structure comparison result; and performing database migration based on the table structure comparison result to migrate target data in the source database to the target database, which can effectively improve the security of database migration.