12 results about "Unified Process" patented technology

The application provides a configuration-driven DL4NLP model automatic training and deployment method, which comprises the following steps: parsing a YAML configuration file and verifying parameters to generate a unified process configuration; automatically loading data and performing preprocessing according to the configuration to generate a model input tensor; instantiating model components through a component factory and assembling the model components into a complete network model; automatically configuring a training environment to train and evaluate the model to obtain an optimal model; exporting the model into a TorchScript format binary file; and automatically generating a standardized deployment package based on a template engine. The application abstracts the whole process of model development and deployment into a configuration-driven standardized pipeline by parsing the YAML configuration file, automatically performs data loading and preprocessing, model component instantiation and assembly, training optimization and deployment package generation, and solves the problems of low development efficiency, long cycle and technical gap between training and deployment caused by repeated code writing and manual conversion and deployment for different tasks in traditional model training and deployment.

The invention relates to the technical field of sample labeling, in particular to a quantum inspired active learning type defect detection sample labeling method which can reduce the manual labeling amount and the labeling cost. Specifically, sample representativeness and uncertainty are balanced through unified process design, firstly, a center cluster set is obtained based on Hamiltonian operator clustering, secondly, the quantum entanglement degree is calculated, a representative sample set is screened, residual unlabeled sample sets are processed in combination with virtual time evolution and a Schrodinger equation, and a to-be-labeled sample set is obtained through a fusion result; a budget scene does not need to be distinguished, sample selection can be adaptively optimized, the labeling efficiency is improved, and the problem of strategy simplification is effectively solved; in addition, samples are mapped into quantum states through self-supervised learning, clustering precision is optimized based on Hamiltonian operators, quantum entanglement is utilized to quantify sample association, uncertainty is captured by means of virtual time evolution and a Schrodinger equation, the quality of labeled samples can be improved, and the problem of representation limitation of a classical framework is solved.

The application discloses a kind of distributed application batch release method, it is characterized in that, for user, provide a one-key node release configuration and the program entrance of the deployment center of monitoring, in DeployCenter, after the node search range that needs to be released is selected and configuration update is completed, one-key can be completed node batch upgrade, DeployCenter is preset with a finite state machine, reach the solidification of all operations of operation and maintenance personnel in node batch upgrade, replace the operation of operation and maintenance personnel by program, replace the number of operation and maintenance personnel by thread number, so that the process efficiency of application node batch release is greatly improved, unified process control can be accurately and timely found in the process of release Abnormal and make interrupt processing, compared with original multi-person operation, greatly reduce the possibility of error caused by communication effect.

The invention provides a method, a system, equipment and a medium for realizing unified process management, and the method comprises the steps: building an extensible access architecture based on a multi-protocol adaptation layer and a dual-interface separation mechanism, and achieving the standardized access and elastic data management of a heterogeneous system through the combination of dynamic business object modeling; a four-layer processing system with data full life cycle management as a core is constructed, and flow data standardization management is achieved through a dynamic rule engine and hierarchical storage; a full-link process intelligent sensing and self-adaptive early warning system is constructed, and a rule engine is used for driving multi-stage alarm closed-loop management, process abnormity active sensing and hierarchical management and control; an intelligent closed-loop optimization system based on holographic modeling and AI diagnosis is constructed, and end-to-end process efficiency quantitative evaluation and continuous improvement are realized through dynamic digital twinning, so that the problems of data real-time performance, system compatibility and implementation economy of a process management technology based on a data platform are solved.

Methods and systems include converting an event log for an application into event log process information. The source code for the application is converted into source code process information. Relations between the event log process information, the source code process information, and an initial process model that is implemented by the application are identified using fuzzy logic on a set of events. A unified process model is generated using the relations. A problem in execution of the application is resolved based on the unified process model.

Methods and systems for system incident resolution include converting an event log for an application into event log process information. Source code for the application is converted into source code process information. A unified process model is generated from the event log process information, the source code process information, and an initial process model that is implemented by the application. A problem in execution of the application is resolved based on the unified process model.

The invention relates to the cross technical field of intelligent manufacturing, industrial artificial intelligence, a big data technology and high-end material engineering, in particular to a neodymium iron boron production process management method based on artificial intelligence and a big data technology. According to the method, a'big data platform + AI algorithm engine 'double-wheel-driven intelligent management system is constructed, artificial intelligence technologies such as machine learning, deep learning, knowledge graph and digital twinning are deeply fused with a mass multi-source heterogeneous big data processing technology, and the method runs through the whole process of neodymium iron boron material production. The core comprises the steps of constructing a unified process data lake based on a big data technology, and realizing fusion treatment of multi-source data; establishing a quantitative correlation model of process parameters and product performance based on a machine learning algorithm; digital expression and intelligent reasoning of process knowledge are realized based on the knowledge graph; constructing a virtual process simulation optimization platform based on a digital twinning technology; and finally, a continuous evolution closed loop of data acquisition, feature extraction, model training, intelligent decision making and feedback optimization is formed. The technical problems that in traditional neodymium iron boron production, value mining of mass data is insufficient, process decision depends on artificial experience, quality control lags behind, and the process optimization period is long are effectively solved, and fundamental transformation of the production process from experience driving to data and intelligent double-wheel driving is achieved.

The invention relates to the technical field of process management, and discloses a service approval method, device and equipment and a storage medium, and the method comprises the steps: receiving a node completion notification submitted by an initial service system; writing the service information into a process data storage module corresponding to the task number, and updating a process instance state based on an approval result corresponding to the service information; and determining a next node according to the updated process instance state, and sending a task triggering request to a target service system corresponding to the next node, so that each service system reads the service information from the process data storage module based on the task number. The approval and service data in each service node are recorded by establishing the general storage capability, so that all service systems read the service information from the unified process data storage module based on the task numbers, the complex coupling relationship formed by direct docking among the service systems is avoided, the system architecture is greatly simplified, and the stability is improved.

The application discloses to the technical field of building control, specifically is based on digital twinning building intelligent three-dimensional visualization control system, including internet of things sensing collection module, multi-source data fusion module, digital twinning modeling module, three-dimensional real-time rendering module, intelligent linkage control module, abnormal early warning disposal module, edge collaborative computing module, cloud iterative optimization module, the application has the beneficial effect: through internet of things sensing collection module and multi-source data fusion module, can real-time acquisition and unified processing various data in building, establish standardization data base, eliminate data island, improve data utilization efficiency, digital twinning modeling module can construct 1:1 high-precision three-dimensional model, collect and update regularly and compare with benchmark model, automatically mark structure deformation, component offset and other differences, realize early prediction and active protection of safety hidden danger.

The invention discloses an industrial process configuration system based on a unified model, which comprises a unified process configuration module and a unified interaction and diagnosis module, and is characterized in that the unified process configuration module comprises a unified process modeling unit for providing a graphical configuration interface based on a single full-process model, the upper computer business logic and the lower computer control logic can be simultaneously defined in one editing environment, and unified standardized definition and management are carried out on all signals, variables and equipment interfaces in the process. According to the method, through unified modeling and configuration, the development complexity and communication cost are greatly reduced, and the project period is shortened; through interaction and diagnosis based on a unified model, an unprecedented full-link transparent view angle is provided for operation and maintenance personnel, and the operation and maintenance efficiency is greatly improved; the process design, development, test, deployment, monitoring and maintenance are all completed in a unified platform, a complete closed loop is formed, and the manageability of the whole system is improved.

The invention discloses a model homomorphic transformation method for test demand formalized simulation, and belongs to the technical field of computer modeling and simulation. The problem that the consistency of a designed system model and a generated FMU file is poor in an existing system modeling and simulation method is solved. According to the method, in the process of generating the FMU file, through unified process definition, system model construction, JSON data, python code generation, code optimization and pythonfmu library tool packaging are conducted to form a complete tool chain of the FMU file, setting consistency is guaranteed, one-key type FMU file automatic generation is achieved, intermediate links are reduced, and efficiency and accuracy are improved. The method and the device are mainly used in the automatic generation of the FMU file and the simulation test.

This invention relates to an automated operation and maintenance (O&M) system based on unified process management technology, belonging to the field of IT system O&M technology. The system includes an O&M middle platform; the O&M middle platform includes an O&M business middle platform; the O&M business middle platform includes an automated O&M module and other O&M scenario modules; the automated O&M module includes a runtime support platform and a runtime resource management platform; the runtime resource management platform is used to manage various runtime resources required by the automated O&M system based on unified process management technology; the automated O&M module also includes automated deployment units, automated inspection units, automated batch processing units, automated disaster recovery units, and automated software installation units. This invention enables automated O&M, reduces the risks associated with manual operations, improves O&M efficiency, lowers O&M costs, and is easy to promote and apply.