77 results about "Database construction" patented technology

The application discloses a soil property data layered database construction method, which comprises the following steps: collecting soil monitoring data and related data of a preset area, and preprocessing the soil monitoring data and the related data; calculating water and soil loss risk contribution degree depth weight based on soil erosion mechanism, acquiring texture continuity clustering weight according to continuous runs, judging and obtaining loss risk factors by parallel multi-conflict and conflict resolution through the water and soil loss risk contribution degree depth weight and the texture continuity clustering weight; calculating texture transfer entropy of different depths, determining that the current depth is a mutation point when the texture transfer entropy of two continuous depth points is greater than a mutation threshold, and adaptively optimizing layer section boundaries according to the mutation point to obtain layer section adjustment boundaries; and constructing a three-region interactive soil property data layered database according to the loss risk factors and the layer section adjustment boundaries, and outputting a target database.

The application belongs to the field of agricultural biotechnology, and discloses a database construction and analysis method for soybean transgenic crops, which comprises the following steps: obtaining soybean high-throughput sequencing original data and metadata, performing soybean specificity quality control, storing in a database sub-database according to a scene label, and generating standardized sub-database data; identifying the priority of each sub-database scene, allocating hardware according to a priority-resource matching rule, generating resource configuration records, synchronously executing multi-dimensional feature extraction, and generating a multi-dimensional feature dataset; dynamically adjusting the feature importance degree according to the scene, performing feature collaborative analysis, combining an enhanced decision knowledge base to retrieve and match results and solving feature conflicts, and generating a dynamic confidence identification report; extracting key feature data and identification process information to generate a hash value, writing the hash value into a consortium chain, and associating a soybean sample ID to form a digital traceability certificate; dynamically optimizing the feature importance degree, the enhanced decision knowledge base and the database sub-database rule, and forming a full-link iteration.

This application provides a method, system, medium, and terminal for constructing a knowledge graph of faults in key ship equipment. The technical solution of this application is aimed at building a professional ontology model for ship equipment fault diagnosis, defining seven types of entities and five types of relationships, and is compatible with component nesting and bilingual expression. It can completely depict the equipment architecture, fault propagation, and maintenance knowledge. Relying on the large model prompt word engineering, it achieves efficient knowledge extraction with few samples, saving large-scale data annotation and reducing the cost of database construction. It integrates a hybrid alignment algorithm of semantic vectors and edit distance, coupled with a three-level decision mechanism, to efficiently solve the problem of differences in domain entity representation and complete the fusion of multi-source knowledge. The overall solution has outstanding versatility and scalability, and can be quickly adapted to the construction of fault knowledge graphs for various industrial equipment by fine-tuning parameters.

This invention discloses a method for constructing a database for the survey of traditional Chinese medicine (TCM) cultural resources based on knowledge graphs, belonging to the field of database construction technology. Specifically, it includes: collecting classical texts and field survey texts; extracting core entity terms using sequence labeling technology; establishing an ontology model including lineage and medicinal material origin dimensions to form a knowledge architecture for the TCM field; extracting entities and events from the text using neural networks, aligning entities to ontology nodes according to the domain knowledge architecture, and generating a basic TCM resource graph; calculating feature vectors of graph nodes, using inference algorithms to mine implicit connections between origin changes and treatment customs, and completing missing semantic edges in the graph; performing multiple path searches for resource nodes, aggregating their associated nodes in the lineage and regional dimensions, and generating a subgraph containing spatiotemporal evolution trajectories; and converting the generated subgraph into topological data to complete the construction of a network survey database.

This invention belongs to the field of text printing technology and discloses a text printing method and system based on speech recognition. The method includes the following steps: constructing a text printing template database; constructing a mixed-language speech recognition model; acquiring speech audio data in real time and performing speech recognition; matching several corresponding text printing templates; selecting a text printing template; fusing the real-time speech text data with the selected text printing template; and printing the real-time text printing data. The system includes a database construction unit, a model construction unit, a storage unit, a speech audio acquisition unit, a speech recognition application unit, a template matching unit, a template selection unit, a data fusion unit, and a printer. This invention solves the problems of low intelligence, poor speech recognition effect, low recognition efficiency, and lack of organic integration in existing technologies.

The application discloses a kind of based on GiST spatial index multi-resolution fragmentation DEM database construction method, comprising: S1, with the resolution of fragmentation DEM image tile as hierarchical division standard;S2, existing DEM image tile is hierarchically divided according to S1 hierarchical division standard, to minimum outer rectangle as unit independent storage;S3, based on DEM image tile, the hierarchical structure rule of R tree is used to establish parent-child node relationship, and the initial R tree multi-resolution skeleton is constructed;S4, on the basis of initial R tree multi-resolution skeleton, uniform different hierarchical spatial relationship description rule is formulated, and according to the rule, the spatial correlation between DEM image tile is described, and the preliminary establishment of multi-resolution DEM database based on GiST spatial index is completed;S5, the DEM image tile to be stored is stored into database, and the database is improved.The application improves the performance of DEM data storage.

The application discloses an intelligent splitting and assembling method of a database model based on a business scene, belongs to the technical field of database management and application, and relates to the technical field of database management and application. The splitting method comprises the following steps: converting an abstract or unstructured business model into a calculable or structured graph representation form, mapping a business function unit into a node in the graph, mapping the relationship between businesses into an edge, and constructing a business topology structure. The assembling method comprises the following steps: acquiring the business topology structure, automatically analyzing a natural language business requirement into a structured requirement model, performing feature extraction on the analyzed requirement, generating a multi-dimensional feature representation, and assembling business model slices in a progressive matching mode. The application can improve the database operation efficiency, reduce the database construction and management cost, and enhance the adaptability and flexibility of the database to business changes.

The state association database construction method and device, the storage medium and the computer device provided by the application, when constructing the database, first start the time synchronization control and cumulative error correction function of the multi-source data acquisition system, and monitor the target user through the system to ensure the synchronization and accuracy of multi-source data acquisition; if a collection event that meets the event triggering rule occurs in the monitoring process, the system automatically collects multi-modal data in the preset collection window, and performs association feature mapping and cognitive label matching on the data to form a multi-element data group with a clear data framework, meeting the fine-grained modeling needs of dynamic mapping of music-induced emotions and cognitive states; after the system monitoring ends, the collected data groups are subjected to data quality verification and model adaptation verification, and after the verification is passed, they are stored in the preset multi-layer structure database in layers, and the state association database formed in this way has high reliability and usability.

This invention discloses a method and system for constructing a multi-dimensional dairy cattle breeding database, belonging to the field of computer data processing. It includes: constructing an original record set by performing temporal alignment and normalization using individual identifiers; extracting data associations to construct a dynamic ontology model and instantiating it into an initial knowledge graph; traversing the graph to identify logical contradictions and mark anomalous nodes; constructing a dynamic confidence matrix using anomaly distributions; performing weighted filtering on the original record set to extract net phenotypic values; solving for the genetic prediction baseline and calculating the residual vector; mapping the residual vector to environmental temporal fluctuation features to construct an environmental interaction matrix; and aggregating the genetic prediction baseline and the dynamic confidence matrix into a structured database. This invention achieves dynamic cleaning and environmental decoupling of breeding data through graph logical arbitration and multi-dimensional tensor fusion, improving data quality and analytical dimensions.

The present application relates to the technical field of database construction, and particularly relates to a construction method of a foraminifera morphological feature database, comprising the following steps: S1, collecting foraminifera images from multiple sources, identifying scale drift and shooting deviation based on principal axis normalization and local vorticity field, performing structure-preserving image enhancement, and outputting an enhanced image set consistent in shell substance, shell arrangement, shell opening, suture line and micro-pore features; S2, extracting a multi-scale shell structure atlas, constructing a structure-semantic coupled label nested tree, performing polysemy recognition and ambiguity resolution, and generating a structured annotation set; S3, fusing the image set and the annotation set, and constructing a three-layer database model containing a part layer, an attribute layer and a variation layer according to the label nested tree. Through image structure enhancement, semantic ambiguity resolution and three-layer database construction, the present application effectively improves the recognition accuracy of foraminifera morphological features, the label organization logicality and the information retrieval efficiency.

The application belongs to the technical field of groundwater resource management, and discloses an integrated method of groundwater source environment safety and sustainable utilization technology, which comprises the following steps: first step, multi-source database construction and feature recognition; second step, technology system construction and applicability evaluation; third step, technology combination comparison and effect evaluation; fourth step, system integration and output. The beneficial effects are as follows: the technical problems of cross-disciplinary joint interpretation and mechanism identification caused by the format and scale conflicts of original data are solved completely. The repeated calculation contribution caused by the strong internal correlation of indexes is effectively weakened, so that the applicability score of the final calculation can truly and accurately reflect the physical matching relationship between the technology and the complex hydrogeological environment condition. The globally optimal integrated technology path screening with high self-adaptation and cross-scenario robustness in the multi-dimensional conflict solution space is realized, and a scientific and operable tool for fine management is provided.

This specification provides a cardiac ultrasound coronary artery stenosis diagnostic system and method based on a visual language transfer model. The system includes: a database construction module for standardizing multi-view cardiac ultrasound video sequences and radiological reports; a cardiac region of interest (ROI) standardization and labeling module for segmenting myocardial segments, obtaining ROI data, and generating a coronary artery-specific perfusion region mask as the ROI for vascular-level stenosis prediction; a visual language transfer pre-training module for semantic alignment of video data and report text using a visual language transfer model; and a downstream task prediction module for utilizing the enhanced attention mechanism of the coronary artery-specific perfusion region mask, based on the global visual features output by the visual language transfer pre-training module, to output patient-level classification results for obstructive coronary artery disease and vascular-level stenosis prediction results for LAD, LCX, and RCA.

The application discloses a log anomaly detection system and method for a cloud native service system, collects log data and divides the log data into normal logs and abnormal logs; a normal log sample set is constructed and vectorized, a log vector obtained is used to form a normal log knowledge base with corresponding log content; a to-be-processed log is preliminarily judged to determine normal logs and abnormal logs; abnormal logs after judgment of a primary judgment module are received, similarity retrieval of the abnormal logs obtained by the primary judgment is performed based on a normal log knowledge base constructed by a database construction module, and a final log classification result and a corresponding review reason are output; a judgment result output by a re-judgment module is received and recorded, and the judgment result is stored together with a primary judgment result; and through a multi-stage judgment mechanism, high-precision classification and abnormal detection of logs are realized.

This invention discloses a highly robust web crawler system, belonging to the fields of big data acquisition and artificial intelligence technology. The system is a closed-loop intelligent system with multiple modules working collaboratively. It includes a multi-data source database construction and pre-training module, a real-time monitoring module for crawler operation status, a data semantic analysis and association mining module, a data request-matching evaluation and parameter optimization module, and a dataset generation and delivery module. Through tight coupling between modules and effective transmission of data flow and control flow, the system achieves full-process automation and intelligence from data discovery, intelligent crawling, dynamic adaptation to high-quality delivery. The system features high robustness and anti-crawling capabilities, strong data semantic understanding and association accuracy, and low manual costs.

The application relates to the field of crystal structure symmetry classification and retrieval, and specifically discloses a crystal structure symmetry determination and retrieval method using electron diffraction, which comprises the following steps: a multi-view selected area electron diffraction data input module is used to acquire a two-zone axial diffraction spectrum and perform pretreatment; a symmetry feature coding module is used to extract a single-view descriptor through a double-branch convolutional neural network, to obtain a material descriptor through view pooling fusion; a hierarchical symmetry classification module is used to realize hierarchical classification of crystal systems and space groups, and to guarantee the logic of the results through consistency constraints; a high-dimensional feature embedding and database construction module is used to standardize crystal structure files, to generate descriptors, and to construct a vector database; and a constrained structure retrieval module is used to combine the classification results and user constraints to filter candidate structures, and to complete retrieval through cosine similarity. The application solves the problems of poor generalization, insufficient multi-view feature fusion and inability to associate a crystal library in the prior art, and realizes full-process automation of crystal structure symmetry classification and retrieval.

The application discloses a kind of Sabina pollen aerosol chemical component detection and feature database construction method, comprising the following steps: (1) sample processing: collecting Sabina flower, after drying and crushing, extraction is obtained to be measured solution;(2) using the method of ultra-high performance liquid chromatography-quadrupole / or electrostatic field orbitrap high-resolution mass spectrometry, small molecule chemical components in Sabina pollen are systematically separated and identified;(3) data processing: including database establishment, data acquisition and processing, relevant literature search, representative compound selection and cleavage rule derivation.The present application not only lays a theoretical foundation for the rapid screening of Sabina pollen allergenic small molecule markers, the analysis of allergenic mechanisms, and the prevention and control of spring pollen allergy, but also provides a referenceable technical method for the identification of chemical components and mass spectrometry behavior research of similar pollen plants.

This invention relates to the field of industrial boiler equipment manufacturing technology, and discloses a multi-node, high-efficiency, energy-saving, and automated welding process for supercritical boiler supports, including the following steps: pre-detection and database construction of welding material composition: using a miniature laser-induced breakdown spectroscopy sensor to detect the elemental content of welding materials used in supercritical boiler supports, establishing a basic database of welding material composition, and calculating the deviation values ​​of each element from the standard composition; workpiece pre-treatment and fixture installation; equipment system linkage debugging; pre-adaptation of pre-welding parameters; layered and segmented collaborative welding; time-division and frequency-division four-mode collaborative quality closed-loop control; post-weld treatment and system reset. Through time-division and frequency-division four-mode collaborative quality control, dynamic compensation for welding deformation, and interpass temperature control technology, this invention effectively reduces the incidence of defects such as incomplete fusion and cracks in welds, ensures that the pass rate of weld radiographic inspection meets standards, and improves the stability of welding quality.

This invention discloses a database system for the mechanical, thermal, and moisture properties of C / C honeycomb sandwich structures and its collaborative optimization design method, belonging to the field of digital design and manufacturing technology for high-performance composite materials. The database system adopts a three-layer desktop application architecture: a data access layer for data persistence and transaction management; a core business layer based on Python for data processing, user authentication, and core logic encapsulation; and a front-end interaction layer providing guided data entry, multi-dimensional querying, statistical analysis visualization, and interactive detail preview functions. The collaborative optimization design method comprises four steps: data entry and database construction, pattern mining and sensitivity analysis, construction and verification of a multi-scale prediction model, and automatic optimization by combining sensitive parameters and the model. This invention breaks down data silos, improves design efficiency and prediction accuracy, and shortens the development cycle of spacecraft structures.

This invention provides a method for constructing a knowledge database. The method includes: acquiring a dataset of images to be processed, comprising multiple images to be processed; performing entity recognition on the images to be processed to obtain at least one entity combination of the images, the entity combination including two target entities; constructing at least one knowledge data corresponding to the entity combination based on the two target entities; constructing a knowledge dataset of the images to be processed based on the at least one knowledge data corresponding to the entity combination, with each image to be processed corresponding to one knowledge dataset; and constructing a knowledge database corresponding to the dataset of images to be processed based on the knowledge datasets of all images to be processed. In this invention, the knowledge data not only contains information about the entities themselves but also implicitly contains relationships between entities. The constructed knowledge database expands the dimensions and accuracy of image recognition, thereby improving the accuracy of image recognition results.

The application relates to a database construction method and a database system based on mixed index retrieval, and the database construction method comprises the following steps: step one, performing multi-granularity segmentation on collected data to form data segments at different levels; step two, marking key information for each data segment; step three, simultaneously establishing a field index and a vector index for each data segment; step four, establishing a mapping relationship among the collected data, the data segments and the key information; and step five, based on a user query task, simultaneously calling the field index and the vector index for retrieval, fusing and sorting preliminary retrieval results, and generating final retrieval results. The database comprises a document segmentation module, a key information marking module, a mixed index construction module, an association mapping establishment module and a retrieval fusion module. The application can simultaneously consider accurate retrieval and semantic retrieval, improves a database hit rate, supports fine-granularity positioning of parameters and evidence, and improves checkability of retrieval results.

This invention discloses a non-contact, age-friendly handrail safety evaluation method and system. The safety evaluation method includes: step S1: boundary condition identification and input; step S2: matching specific sub-databases; step S3: non-contact vibration detection; step S4: load-bearing capacity assessment and calculation; and step S5: safety level determination and result output. This method achieves low-cost, highly accurate, and easy-to-operate on-site safety evaluation of age-friendly handrails. Furthermore, database construction does not require physical testing, and the hierarchical storage and version update mechanism ensures practicality and scalability, significantly reducing promotion costs.

The present application relates to the technical field of carbon footprint database construction, and specifically provides an electric equipment product carbon footprint list data collection method and device, comprising: collecting process level original production data list of electric equipment products; verifying the process level original production data list, and taking the process level original production data list that passes the verification as carbon footprint list data of electric equipment products. The technical scheme provided by the present application realizes systematic and standardized processing of electric equipment product carbon footprint list data from collection to verification, improves the comparability, traceability and reliability of the list data, and provides high-quality data support for electric equipment product life cycle modeling and carbon footprint evaluation.

The application discloses a kind of based on power grid measurement data construction power grid database method and system, it is related to power grid field, existing power grid database construction method is solved the problem of construction effect, including step S1: respectively to each electric power node is carried out measurement data generation quantity analysis, according to analysis result, the first data quantity index deviation and the second data quantity index deviation corresponding to target area power grid are obtained, data quantity historical monitoring data is obtained, step S2: respectively to each electric power node is carried out measurement data access quantity analysis, according to analysis result, the first access quantity index deviation and the second access quantity index deviation corresponding to target area power grid are obtained, access quantity historical monitoring data is obtained, step S3: according to data quantity historical monitoring data and access quantity historical monitoring data, target area power grid is carried out power grid database storage mode matching, the application can improve the storage efficiency and access efficiency of power grid database.

The present application relates to the technical field of pipeline corrosion detection and data analysis, and provides a pipeline corrosion defect database construction method for artificial intelligence training, wherein a multi-scene corrosion experiment platform is constructed to simulate typical corrosion environments that the pipeline may encounter during service, real corrosion defects with different morphologies are prepared on pipeline steel samples through accelerated corrosion experiments; then high-precision three-dimensional measurement technology is adopted to obtain fine morphology data of the corrosion pits, and standard magnetic flux leakage detection equipment is used to collect magnetic flux leakage signals corresponding to the defects; finally, the corrosion environment parameters, corrosion pit geometric characteristic parameters and magnetic flux leakage detection signal data are uniformly and structurally processed to form a queryable and extensible associated database. The database can truly reflect the internal relationship between the corrosion morphology and the magnetic flux leakage signals, and provide key data support for subsequent quantitative evaluation of pipeline corrosion defects, optimization of detection models and research on intelligent inversion algorithms.

This invention relates to the field of database construction technology, and discloses a knowledge base construction method and system based on AI text parsing and hybrid retrieval. By integrating semantic relevance and document layout features through adaptive block segmentation, it achieves accurate identification of core semantic units in the text and maintains logical integrity in the division, fundamentally avoiding information fragmentation and laying the foundation for high-quality knowledge organization. Secondly, through a hybrid retrieval mechanism combining keyword, semantic vector retrieval, and multi-dimensional re-ranking, it effectively balances retrieval response speed with the depth and accuracy of results, meeting users' multi-level query needs from rapid location to in-depth correlation mining. Finally, through dynamic updates and automatic association mapping functions, it achieves real-time synchronization and intelligent association of newly added knowledge, not only ensuring the timeliness of the knowledge system but also proactively building a cross-document knowledge network, thereby breaking down information silos and enhancing the overall utilization value and discovery capability of knowledge.

This invention discloses a full-cycle digital management and control system for multiple varieties of rare Chinese medicinal herbs, belonging to the field of digital technology for Chinese medicinal herbs. The system includes the following steps: collecting hyperspectral cubic data of plants and soil water potential time series data; generating a non-uniform pulsed micro-stress control matrix based on a twin model; collecting acoustic emission events of xylem vessel cavitation, and re-watering via a drip irrigation solenoid valve driven by a dry contact when the event rate exceeds a limit; performing joint scanning of medicinal herb samples, extracting biochemical topology, and generating biological intrinsic hash values ​​for on-chain processing; collecting two-dimensional near-infrared and multispectral data of medicinal herb fragments, then retrieving moisture content and performing inverse expansion registration, and verifying the results with the on-chain biochemical topology through tomographic matching. This method achieves closed-loop management and control of Chinese medicinal herbs from induction, boundary control, fresh-state database construction to end-point ownership confirmation, enhancing the consistency between source information and physical samples, and thus improving the accuracy of authenticity verification in dried sliced ​​state.

This invention discloses a deep learning-based intelligent analysis method and system for land surveys, belonging to the fields of computer vision and remote sensing mapping technology. The method includes: acquiring multi-source high-resolution remote sensing images and extracting features using a super-resolution semantic segmentation network; extracting sub-pixel-level features of land cover edges using a boundary refinement module and completing sub-pixel feature point offset calibration; performing adaptive topological vectorization of patch boundaries based on edge probability response maps and offset vector fields, and using spatial geometric mechanisms to perform high-precision fine-tuning of vector boundary lines; performing coordinate space transformation and topological verification on the fine-tuned boundaries, and encapsulating the data to complete database construction and data mapping. This invention effectively overcomes the defects of sub-pixel-level boundary blurring and topological distortion in remote sensing images, achieving sub-meter-level high-precision patch boundary extraction, and meeting the needs of accurate database construction in land surveys.

The application discloses a building full life cycle database construction method and system based on BIM, relates to the technical field of building cycle databases, and aims at solving the problem of poor effect of building data in the collection and management process. Through data support of the BIM model, the project team can make more wise decisions at different stages, improve the overall performance and sustainability of the project, and through the encryption transmission mechanism, the data is encrypted when being transmitted to the BIM collaborative platform and being transmitted in the platform, so that the leakage and tampering of the data in the transmission process are effectively prevented, and the security of the data is enhanced. Through the joint index and the covering index technology, quick query of multiple column conditions can be realized, diversified data retrieval requirements in business scenarios are met, invalid indexes can be found and optimized in time through regular monitoring of the use and performance of the indexes, and the storage pressure is reduced and the writing speed is improved.

The application provides a kind of nuclear power plant pipe system flow-induced sound vibration evaluation method based on IDF model, through realizing the whole process automation and standardization from IDF format file analysis, structured parameter conversion, pipe system digital model reconstruction, to sensitive component screening, special database construction and key frequency automatic calculation, risk assessment, effectively avoid the low efficiency, human error and other disadvantages caused by the dependence of traditional evaluation method on manual parameter extraction and manual calculation, greatly improve the efficiency and accuracy of nuclear power plant pipe system flow-induced sound vibration evaluation, simplify the repeated evaluation process of parameter iteration update, provide efficient and reliable technical support for nuclear power plant pipe system structural integrity guarantee and safe operation, significantly reduce the consumption of manpower and material resources.

The present application relates to the technical field of ethnic minority music data processing, and particularly relates to an ethnic minority music database construction and application system, comprising a data collection module, a data processing module and an application module, wherein the data collection module acquires original music data and cultural background data; the data processing module generates an optimized label set by means of the extraction of multi-dimensional cultural attribute labels, clustering analysis and a cultural correction function; and the application module uses a deep learning model to model musical cultural characteristics, and generates an optimized cultural attribute distribution to execute adjustment operations. The present application enables comprehensive collection and processing of unique cultural attributes of ethnic minority music, and supports the requirements of complexity and diversity, thereby meeting the requirements for cultural dissemination and application.