373 results about "Version management" patented technology

The invention relates to the technical field of base frame operation and maintenance, can be applied to business scenes such as financial science and technology and medical health, and discloses a context object-driven patch processing method, device, equipment and medium, and the method comprises the steps: extracting an equipment attribute identifier, an operation state identifier and a routing path identifier from an operation environment of target equipment to generate a context object, creating a patch definition, verifying the patch definition in a security sandbox, submitting and approving the patch definition to form a patch version identifier, configuring an environment isolation condition in combination with an effective range, issuing a patch execution instruction carrying the patch version identifier, the environment isolation condition and a hook definition, triggering patch script application repair logic, and calling a cache cleaning tool to process a resource cache. And collecting logs and indexes to generate a monitoring record, and executing rollback or off-shelf operation based on the monitoring record to finish the patch task. Through combination of dynamic patch definition, instruction issuing and version management, safe distribution of front-end patches is realized, and the stability and maintainability of the system are improved.

The invention provides a production line scheduling method and equipment fusing edge computing and machine learning, and belongs to the technical field of production line scheduling, and the method comprises the steps: deploying edge nodes in an industrial production line, and carrying out the life cycle management and control of state monitoring, task issuing, resource configuration and version management on the edge nodes by a cloud; the edge nodes collect production line data in real time; constructing a scheduling model at the cloud, and issuing the scheduling model to the edge node; outputting execution task priority judgment and path and resource optimization in combination with the scheduling model, generating a scheduling instruction, and issuing the scheduling instruction to a field control system to execute task scheduling; recording all scheduling processes and state changes, and synchronizing to the cloud after the network is recovered; according to the invention, the analysis rule and the model parameters can be adjusted according to the actual working condition and the monitoring scene of the equipment, accurate description and abnormal early warning of the operation state of the equipment are realized, and the efficiency, the accuracy and the adaptability of equipment monitoring in the industrial Internet of Things environment are effectively improved.

The invention discloses a knowledge graph generation method based on multi-source data integration, and relates to the technical field of knowledge graph generation. The method comprises the following steps: collecting multi-format data, and performing cleaning, standardization and desensitization preprocessing to ensure that the data is integrated; using the fusion model to extract entities and relationships, and adapting to multi-source data types; similarity is calculated in combination with multi-dimensional features, and entity alignment disambiguation is achieved; carrying out weighted fusion on multi-source knowledge to construct a triple, and processing relation conflicts; evaluating the quality of the atlas through multiple indexes; triggering conditions are set, incremental updating and version management are adopted, and dynamic iteration of the atlas is guaranteed. According to the method, the multi-source data preprocessing quality is improved, the entity recognition and alignment precision is enhanced, relation conflicts are solved, and a high-quality time sequence knowledge graph is constructed; incremental updating is efficient and energy-saving, version management is traceable, and multi-field dynamic application requirements are met.

The invention provides an application environment and version management method and system suitable for a low-code platform, and relates to the technical field of platform management.The application environment and version management method comprises the steps that a directed dependency graph is constructed by obtaining change records, and a dependency loop is detected and intelligently decomposed through a depth-first traversal algorithm; and packaging the node clusters into micro-services based on a function relevancy model to form an acyclic directed dependency graph, constructing a version backtracking index and a difference analysis matrix to determine a change influence range, executing incremental deployment according to a topological sequence, and recording deployment information. According to the method, the problem of version management and environment dependence in a low-code platform is solved, and the application deployment efficiency and the system stability are improved.

The invention discloses an industry knowledge graph automatic construction method oriented to multi-source heterogeneous data, and relates to the technical field of knowledge engineering. Structured, semi-structured, unstructured and distributed data are supported, and high-concurrency data are cached through Kafka; preprocessing and standardizing, and executing cleaning, field unification, text conversion and format conversion; a pre-training model and a rule engine are adopted to cover entities and relations of multiple industries; designing a dynamic Schema, storing the dynamic Schema in a graph database, and constructing an index; evaluating and correcting from multiple dimensions; and dynamic updating and maintenance, incremental updating based on data change, and support of version management and knowledge service. According to the method, the knowledge graph is automatically constructed through multi-source heterogeneous data, the construction efficiency and quality are improved, cross-domain fusion is supported, dynamic updating is adapted, and multi-industry intelligent application is assisted.

The invention relates to the technical field of computers, in particular to a dynamic configuration initialization and version synchronization method and system for multi-agent service, and the method comprises the following steps: obtaining a database update lock, constructing a database migration script dependency relationship, determining a current version of a database mode, upgrading and deploying the database mode, and verifying agent versions. The method has the beneficial effects that a rigorous database updating lock control mechanism, perfect migration script dependency chain verification, agent version management, port availability detection, idempotence and transaction safeguard measures are introduced, so that the processes of database structure upgrading and agent version initialization in a distributed deployment environment can be effectively supported; and the data consistency, the operation stability and the service continuity of the system are ensured.

The invention discloses a large language model knowledge base self-adaptive updating method combining documents and interactive feedback, and relates to the technical field of knowledge base updating, and the method comprises the steps that a real-time change detection module monitors streaming documents and interactive feedback, and captures and marks a single fact change event; the decision module calculates a shunting decision coefficient according to the heat density index and the linkage sweep index, and the event is shunted to a Micro-Edit or Incremental-Tune path; if shunting to the Micro-Edit path, the positioning module executes attention backtracking and gradient sensitivity analysis, and determines a to-be-updated weight address; the rank-one editing module implements rank-one updating and records an audit log; the verification module generates an online token or a rollback instruction through consistency comparison; the version management module manages a version, activates a new version route and cleans out expired branches. Through event granularity identification, intelligent shunting, local updating and multi-version management, the timeliness of knowledge base updating is remarkably improved, and resource consumption and maintenance cost are reduced.

The invention discloses a large model cue word intelligent design and verification system supporting multi-person cooperation, which designs cue words in a manner of cue word project management and multi-person cooperation to realize specialized design of the cue words. The difficulty of cue word design is simplified by using AI aided design; the operation stability and accuracy of cue words in different models and different computing power are verified through single-point testing and batch testing, so that cue word verification and iteration form a closed loop, and the cue word quality is improved; after the cue word is published, directly outputting an interface with an access key for external calling, and storing the interface as a cue word case into a cue word knowledge base; compared with an existing system and technology, the cue word version management difficulty is effectively reduced, the workload of cue word designers is reduced, the cue word quality is improved, and the risk of cue word asset loss is reduced.

The invention discloses a distributed service deployment method and a distributed service deployment device based on Kubernetes. According to the method, resource object definition and service metadata are extracted by automatically analyzing a configuration file, and accurate acquisition and standardized processing of deployment information are realized; optimal deployment nodes are dynamically matched based on service characteristics and cluster real-time states, and resource scheduling rationality and service operation efficiency are improved; then automatically creating and starting a service instance at a target node according to an analysis result, and ensuring configuration consistency and standardization of a deployment process; and the service flow is controllably migrated to the new instance through the predefined version switching rule, so that smooth transition and risk controllability of version upgrading are realized. According to the method, the efficiency, the reliability and the version management capability of micro-service deployment are remarkably improved through full-process automatic closed loop from configuration analysis, intelligent scheduling to instance creation and flow switching.

The invention provides a medical knowledge graph dynamic construction method, system and device based on a large model and a medium, and belongs to the technical field of medical informationization. The method comprises the steps that multi-source heterogeneous medical data is collected, and data cleaning, anonymization privacy processing and encryption security processing are carried out; performing medical entity identification and relation reasoning between medical entities on the processed medical data through a multi-modal large model, establishing a knowledge triple, and performing multi-modal feature alignment; performing IPFS fragmentation storage on the aligned knowledge triads, calculating hash values of the knowledge triads, performing chaining storage on the hash values by using a block chain, and performing dynamic verification and version management on the knowledge triads through hierarchical consensus and an intelligent contract; and establishing a semantic retrieval interface for the knowledge triad by using an SPARQL query tool to complete the construction of the medical knowledge graph. According to the method, efficient construction, dynamic updating and credible verification of the medical knowledge graph are realized, and the construction efficiency and safety of the knowledge graph are improved.

The invention discloses a government affair knowledge graph updating and version control method and system, and belongs to the technical field of artificial intelligence and knowledge graphs, Git-based file change drives incremental updating of knowledge graphs, and the method is implemented by the following steps: change monitoring: integrating Git version management; capturing file change through double modes of timing scanning and event triggering, establishing one-to-one mapping between a file Git version and a map version, and transmitting difference contents; difference preprocessing: standardizing difference contents into an analysis unit containing positions, types, original contents and updated contents, and filtering meaningless differences through a G-NF algorithm; constructing a difference subgraph; carrying out difference atlas fusion; and version control: storing version archives, and providing a multi-dimensional query tracing function. According to the method, version closed-loop management is achieved, change traceability is accurate and efficient, incremental atlas updating is achieved, total processing resource consumption is reduced, meanwhile, multi-scene version switching is supported, and repeated construction and maintenance cost is reduced.

The invention discloses a file metadata multi-version storage management method and device, computer equipment and a storage medium. The method comprises the steps of obtaining file metadata; in response to the received generation instruction, generating a snapshot version for the file metadata to obtain a snapshot version set; extracting a first snapshot version and a second snapshot version from the snapshot version set, updating the snapshot version set, and storing the snapshot version set in a memory area; packaging the file metadata, the first snapshot version and the second snapshot version to obtain a coded data structure, and storing the coded data structure in a memory area; storing the updated snapshot version set and the coded data structure in a storage device; querying the memory area according to the query instruction, querying the storage device if the query fails, and returning a query result; by means of the method, decoupling storage of multiple versions of file metadata can be achieved, and the system memory utilization rate and the snapshot version management efficiency can be improved.

The invention belongs to the technical field of computer server management, and particularly discloses a laboratory collaborative environment-oriented user and data full-life-cycle server management system, which comprises a container virtualization layer, a server management layer and a server management layer, dynamic resource allocation is supported through a state saving-resource reallocation-environment recovery mechanism; the heterogeneous transaction coordination layer adopts a Saga transaction mode to coordinate a heterogeneous system so as to realize cross-system transaction consistency; the data collaboration ecological layer establishes typed management of a personal data volume, a shared software environment volume and a public data set volume, and supports software environment encapsulation sharing and versioning management; and the metadata management layer realizes real-time update and high-performance query of metadata based on a Redis hot update architecture. According to the method, the problems of inflexible resource allocation, incomplete environment isolation, dilemma in authority management and difficulty in data collaboration and recovery in the prior art are solved.

This invention discloses a full lifecycle management system and method for scientific computing programs. The system includes a build environment subsystem and a production environment subsystem. The former provides computer resources for the build process of the scientific computing program throughout its lifecycle, while the latter provides computer resources for the testing and deployment processes. This invention, through a full lifecycle management method for scientific computing programs, operates on corresponding computing resources, encompassing a series of steps including querying, triggering scheduling, build execution, result distribution, and test deployment. It automatically generates the executable file of the scientific computing program and configures its runtime dependencies. Simultaneously, it automatically generates a corresponding description file recording the entire lifecycle process. Furthermore, based on version management of these description files and their sets, it achieves full lifecycle traceability and cross-platform migration and deployment of scientific computing programs in a high-performance computing environment.

The invention belongs to the technical field of large model fine tuning, and particularly discloses a large model fine tuning parameter version chain management method and system, a terminal and a medium. Comprising the following steps: in the fine tuning process of a large model, performing difference calculation on model parameters after two adjacent times of fine tuning to obtain corresponding parameter increments; packaging the parameter increment, the time information, the model identifier and the fine tuning metadata into log entries; establishing a time index based on the time information of the log entries, establishing a model index based on the model identifier, and associating the log entries according to a time sequence to form a parameter version chain; when a model parameter recovery request is received, retrieving a log interval before a target time point according to the time index, loading and accumulating each parameter increment, reconstructing a model parameter state corresponding to the target time point, generating a parameter snapshot in a memory, and caching the parameter snapshot; according to the method, multi-version management and quick rollback can be realized under the condition that a full-quantity model is not stored, the storage occupation is reduced, and the parameter recovery efficiency and the system stability are improved.

The invention belongs to the technical field of product production cycle management, and particularly relates to an electronic image-text file remote multi-bin collaborative storage method based on a PLM. Comprising the steps that a 1 + N hybrid storage architecture is constructed, one center bin is deployed in an enterprise headquarter data center and stores full document metadata and latest version files, and N area bins are deployed according to geographic areas and store cache copies and incremental update data of local high-frequency access documents; the remote multi-warehouse document increment synchronization is realized through an intelligent synchronization engine, and the intelligent synchronization engine adopts a content awareness increment synchronization algorithm and a dynamic synchronization strategy based on network quality; version management is realized through a version cooperative control module, and the version cooperative control module is used for establishing a global version number mapping mechanism and a conflict resolution decision tree; cross-warehouse process automation is realized through a cross-warehouse workflow engine, and the cross-warehouse workflow engine integrates a BPM process engine and a message queue; the method can adapt to a remote network environment, and the large file synchronization efficiency is improved.

The invention discloses an architecture system and method for large-scale task allocation, and belongs to the field of spaceflight measurement and control, and the system comprises a large-scale hardware device which is used for deploying processing units with different performances and various heterogeneous physical communication link resources; the hardware resource dynamic modeling and visualization framework is used for realizing a dynamic modeling system based on multi-source heterogeneous hardware topology perception; the resource topology awareness database captures and synchronizes system deployment changes by maintaining the dynamic topological relation of hardware resources, presents the life cycle state of the hardware resources, and supports system-level resource situation visualization and decision making; a versioning management engine of component arrangement is applied, a multi-version executable unit is packaged based on an atomization component, and an application instance is completed through a combined modeling component; and deploying a scheduling decision system for deploying a scheduling decision. The method can adapt to task deployment requirements of a current large-scale spaceflight measurement and control system.

The invention provides a heterogeneous data mapping optimization method, and relates to the technical field of software development. A JSON Schema model library containing business and voucher objects is constructed by obtaining heterogeneous source data, the construction process comprises data format analysis and feature extraction, and construction and classified storage are completed by means of DSL rules and visual editing; based on the model library, generating a mapping relation description document by utilizing a preset abstract mapping rule template and an expanded JSON Schema grammar; a mapping engine analyzes the document to construct a field-level dependency graph, data conversion is executed according to the field-level dependency graph, and an inerting execution and caching mechanism is adopted in the conversion process; and verifying the converted data and the mapping process by adopting a mode of combining static pre-verification and incremental verification, dynamically adjusting a mapping rule according to a verification result or model change, and performing version management. Through the steps, the data mapping efficiency, flexibility and accuracy are improved, and the system performance is optimized.

The invention provides an automatic management interaction method, system and device of a whole vehicle software version and a medium, and relates to the technical field of vehicle software engineering.According to the method, functions of version monitoring, change analysis, test management and version management are provided through an integrated main interface, and a user can check the software version state and tasks to be done in real time; and performing multi-dimensional version comparison and risk assessment to generate a detailed change and risk report. In addition, the method supports configuration of a test strategy, execution of an automatic test and generation of a test report and a defect positioning list, and the test efficiency and accuracy are effectively improved. And in the aspect of version management, the whole process operation from creation to release is realized, the timeline and historical report of the whole life cycle can be displayed, and the transparency and traceability of version control are ensured. On the whole, the method effectively improves the efficiency and reliability of whole vehicle software version management, simplifies the operation process, and enables the version control to be more efficient, more accurate and easier to manage.

The invention discloses a graph database-oriented vector embedding management and query method. The method comprises the following steps of: defining semantic vector attribute fields for graph nodes in a graph database; constructing a hierarchical multi-dimensional index architecture; in the write-in stage, a transaction engine senses vector attribute change, vector data is routed to the corresponding classification index according to the node type, and synchronous updating of the local index is completed in the fragment to which the vector data belongs; in the query stage, the fusion query statement is analyzed, the graph structure condition and the vector similarity condition are combined, and a unified logic execution plan is generated; aggregating the local optimal result returned by each fragment, and performing global sorting and outputting according to the semantic distance; and establishing a registration and version management mechanism of multi-version and multi-mode vector data, so that the query can be switched and backtracked according to the difference of the model version or the data mode. According to the vector embedding management and query method oriented to the graph database, an efficient and extensible vector search engine is realized in the graph database.

The invention discloses an intelligent document writing system based on a large language model, belongs to the technical field of natural language processing and intelligent office crossing, and aims to solve the technical problems of how to realize intellectualization, standardization and high efficiency of a whole document writing process and improve document writing efficiency and accuracy. According to the technical scheme, the system comprises an input layer, a core layer and an output layer; the input layer comprises a multi-modal input interface and a demand analysis engine; the multi-mode input interface is used for voice input and text input; the demand analysis engine is used for text recognition and automatic element providing, and only subject fields can be filled and document unit fields can be received; the core layer is used for adopting a mixed training strategy of comparative learning and curriculum learning, improving professional field content generation capability, integrating format verification and an OCR feedback mechanism, ensuring document format compliance and supporting a quick response mechanism of standard updating; and the output layer is used for realizing export and version management of documents in standard DOCX, signature PDF and HTML5 formats.

The embodiment of the invention provides a production process configuration method, system and device, a storage medium and a program product, and relates to the field of artificial intelligence. The method comprises the following steps: after obtaining a service demand, analyzing the service demand based on an intelligent agent, and generating corresponding configuration information in combination with a configuration information management rule; in the code development process, the configuration information is adjusted based on the agent according to the change information of the code; and after code development is completed, packaging the latest code according to a preset version management rule based on the intelligent agent, generating a version package, and deploying the version package to a corresponding environment. According to the method, the configuration information is automatically generated according to the service requirements, the configuration information can be automatically adjusted according to needs in the development process, and after the codes are completed, the codes can be automatically packaged and deployed into the corresponding keys, so that developers only need to provide some key service requirements, and the development efficiency is improved. Manual operation links in the production process are reduced, the production efficiency is improved, and the error rate is reduced.

The invention relates to the technical field of intelligent forms, and discloses an intelligent workflow form system based on state driving, which comprises a field authority control module, an auditing process configuration module, a node storage verification module, a composite authority control model and a dynamic form rendering engine. According to the application, through the field authority control module and the audit process configuration module, the static stiffness problem of the authority and the process is solved; through a node storage verification module, the problem of splitting of data verification and version management is solved; all the modules are linked through a unified docstatus value to form closed-loop management, and the problem that the system modules are lack of collaboration is solved. By the adoption of the method and device, the core pain points of a traditional workflow form system in authority dynamics, process flexibility, data consistency and user experience are solved, the enterprise operation efficiency is improved, the adaptability of the system to complex business scenes is enhanced, and the core requirements of intelligence, high efficiency and safety in current digital transformation are met.

The invention discloses a BMS protocol adaptation method and system based on a CSV file and a storage medium. The method comprises the steps of standardizing CSV configuration file design, storing BMS protocol data in a fixed format and integrating a verification error correction mechanism; dynamic configuration management and initialization are conducted, a FATFS file system is used for managing CSV configuration files in an SD card, multiple transmission modes are supported, and dynamic loading and hot plugging are achieved; efficient data processing and analysis are carried out, and a complete process is designed to ensure that protocol data and CAN bus data are accurately matched; and performing security encryption and access control, performing encryption processing on the configuration file, and introducing an adaptive protocol version management and rollback mechanism. The system and the storage medium correspond to the system and respectively comprise related function modules, a storage layer, a management layer and the like. According to the scheme, standardized storage and efficient processing of the BMS protocol data are achieved, unified management is facilitated, development and maintenance cost is reduced, and effective management and use of the system on the configuration files in different environments are guaranteed.

The invention discloses a front-end list componentization code automatic generation method and system based on visual configuration, and belongs to the technical field of computer software front-end development, and the method comprises the following steps: a visual configuration interface is used for realizing the structure, state and interaction logic of a user-defined component, including component type selection; header configuration: supporting definition of column names, field names and display formats; column configuration is operated, and button adding and event logic binding are supported; the template library is used for storing preset or user-defined component templates; the code generation engine is used for dynamically generating codes meeting componentization specifications according to configuration; version management supports version backtracking and sharing of templates and codes. According to the method, high-quality modularized codes can be quickly generated in a standardized configuration mode; and according to the preset rules and templates, HTML, CSS and JS codes meeting specifications are automatically generated, so that the repeated labor of developers is reduced, and the development efficiency and the code quality are improved.

The invention relates to a collaborative learning method and system based on edge sample intelligent grading and cloud intelligent decision, and belongs to the technical field of edge intelligence and big data processing, and the method comprises the steps: (1) AI model real-time reasoning and difficult sample preliminary screening; (2) intelligently grading edge end samples; (3) uploading data with priority labels; (4) cloud server state aggregation; (5) running a cloud intelligent training decision algorithm; (6) carrying out on-demand training and version management on the model; (7) online updating and closed-loop feedback of the model; according to the method, scene self-adaption and autonomous evolution of the AI model are realized, the efficiency and the economical efficiency of model iteration are remarkably improved, the robustness and the quick response capability of the system are enhanced, and the automation and intelligence levels of the system are improved.

The invention relates to the technical field of software engineering, and discloses a Git-based file baseline management method, which comprises the following steps of: constructing a baseline management architecture to carry out baseline management work; providing a data model required by the baseline management interface according to the interface operation; in response to the interface operation, providing a baseline management capability; the git warehouse provides version management capability and reads and stores baseline information of a final state; intermediate state baseline metadata is stored and read. According to the technical scheme, based on the file baseline management capability of the git, a user can establish baselines for part of files or folders in a version based on the git, the file content contained in the file baselines is detected, the content contained in the file baselines is checked in the form of a tree directory, the file baselines can be continuously updated, and the user experience is improved. And continuous optimization of the whole process from generation to application of the baseline is realized.

The invention discloses an AUTOSAR development configuration system and method based on a Docker container, and the system comprises an interaction layer container which is used for the interaction between the system and a user, and comprises a user interface, an authority management interface, a configuration management interface, a code generation interface and a test interface; the application layer container is used for configuring and testing key functions of the AUTOSAR and comprises an authority management module, a configuration management module, a code generation module and a test module; and the output layer container is used for outputting the code file and the configuration file and comprises a code file output module and a configuration file output module. According to the invention, the problems of strong environmental dependence, high resource occupation, complex version management, low deployment efficiency and the like of the existing AUTOSAR development configuration tool can be improved.

The invention relates to the technical field of data management and information systems, in particular to an experimental data management system conforming to GLP specifications, which comprises a data acquisition and standardization unit, a data storage and version management unit, a natural language query and interaction unit, a data quality and compliance verification unit and an audit tracking and authority management unit. According to the method, professional terms and query intentions are accurately analyzed by means of a field-specific language model, intelligent recognition and visual interaction of image data are realized by the multi-modal interaction module, dialogue continuity is maintained by the context dialogue management module, and an association analysis scheme is actively pushed by the intelligent recommendation module. Intelligent retrieval and analysis requirements of animal experiment data are efficiently supported, the compliance and quality of the experiment data are guaranteed, and data risks are effectively identified and handled.

A system for automated real-time publication processing may comprise a data collection module configured to automatically gather data from multiple external sources. A data analysis module may be configured to process the gathered data using artificial intelligence models. A data visualization module may be configured to generate interactive visual representations of the processed data. An update control module may be configured to automatically update published content and maintain version history with timestamps. The data collection module may utilize application programming interfaces and web scraping tools to gather data from government databases and real-time data feeds. The data analysis module may employ machine learning libraries to process and analyze the collected data. The data visualization module may use visualization tools to create interactive charts and graphs. The update control module may use Git-based version management and automated scheduling scripts to implement updates and record modification dates.