18 results about "Workflow model" patented technology

The invention discloses an enterprise production management method based on digital twinning and workflow simulation, and particularly relates to the technical field of industrial internet and intelligent manufacturing, and the method comprises the steps: constructing a physical production system digital twinning body and business process workflow model, and carrying out the dynamic association through a model fusion engine to form an integrated digital twinning model; real-time event driving is used for deducing and simulating a future production process, and bottleneck and conflict prediction is output; based on the prediction result, utilizing a multi-objective optimization engine to generate a plurality of alternative scheduling schemes; performing parallel simulation quantitative evaluation on the KPI of each scheme, selecting an optimal scheme, analyzing the optimal scheme into a control instruction, and issuing and executing the control instruction; and model self-correction and closed-loop optimization are realized through real-time monitoring and feedback. According to the method, the problem of service and physical state disjunction caused by digital twinning and workflow independence is solved, the whole-process closed-loop management from prediction to execution is realized, and the production self-adaption and intelligent level is improved.

The invention provides a business workflow dynamic arrangement and optimization method based on a large model agent, and the method comprises the steps: (1) analyzing the features and operation logic of a multi-element business workflow, and defining a business workflow description language; and (2) decomposing a complex business process construction process, and providing a layered process modeling system to guide a large model agent to construct a workflow model. And (3) constructing a task execution queue based on the task dependency relationship, and dynamically executing and monitoring the workflow. And (4) according to the execution log of the business workflow, discovering the bottleneck, redundancy and abnormity of the workflow model by adopting a process mining algorithm, and proposing a process improvement and optimization strategy. And (5) constructing a collaboration framework of a plurality of large model agents, and realizing dynamic arrangement, monitoring and optimization of the business workflow. According to the method, the defects that the current business workflow construction depends on experience of designers, and effectiveness and function requirements are difficult to guarantee are overcome; the defect that the business workflow is difficult to adapt to dynamic demand changes is overcome.

1. Name of the product in this design: Graphical User Interface for Chat Assistant and Workflow Model Application Development for Electronic Devices. 2. Purpose of this design: For use in the development and / or interface display of chat assistant and workflow large-scale application programs. 3. The key design features of this product are the graphical user interface content on the screen. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The design for which protection is sought includes color. 6. Purpose of the graphical user interface: This product is a human-computer interaction interface used for chat assistant and large-scale workflow application development; the main view is the main interface; the left side of the main interface is the menu bar, and the right side is the data display and operation area. Clicking "Paper Interpretation" in the data display and operation area on the right side of the main interface will enter the interface change state diagram 1; clicking the "Monitoring" button in the menu bar on the left side of the interface change state diagram 1 will enter the interface change state diagram 2.

Systems and methods for automated software testing and test data set generation using workflow path monitoring and modeling are provided. The system includes a workflow path monitoring processor that executes a workflow monitoring software module, an artificial intelligence / machine learning ("Al / ML") software module, and a test script generation software module. The workflow monitoring software module monitors one or more workflow paths taken by a user using one or more software applications or platforms. The Al / ML module processes the one or more workflow paths monitored by the workflow monitoring software module and develops a workflow model for the software application or platform. The test script generation software module automatically generates one or more test scripts and / or test data sets based on the one or more monitored workflow.

The invention provides a collaborative office hierarchical management method and system based on a workflow model, and relates to the technical field of office management, and the method comprises the steps: constructing a hierarchical task scheduling framework based on a pre-constructed workflow model; obtaining office task data, adjusting a hierarchical scheduling rule in the hierarchical task scheduling framework according to the office task data, and generating an adjusted rule; based on the input terminal parameters in the hierarchical task scheduling framework, collecting and processing office task related data submitted or processed by each employee through a touch input device under the high-concurrency office task, and generating verification passing data; setting and adjusting bandwidth basic allocation logic according to task priority identifiers in the data passing verification, generating a bandwidth allocation result, and executing hierarchical management of office tasks by a target processing node of a hierarchical task scheduling framework in combination with the data passing verification and processing nodes and processing time limits corresponding to three pieces of task priority information. And refined hierarchical management of task processing in a high-concurrency office environment is realized.

The application provides a kind of workflow application management method and system for containerization environment, it is related to computer technology field.The method includes the following steps, the structured front-end object model is converted to by visual workflow model construction module with the drag operation of user;Front-end object model is serialized as JSON format file by static logic inspection;JSON format file is sent into template engine by templating code generation module;JSON format file is automatically converted into executable workflow drive file by template engine.The application solves the prior art workflow system usually adopts static script or fixed template to arrange task, realizes the automatic conversion from workflow design to execution code generation by visual workflow model construction module and templating code generation module, reduces the technical threshold of complex workflow construction, improves system development efficiency.

The invention discloses a seismic data interpretation automatic quality control method based on workflow engine three-layer modeling, and the method comprises the following steps: S1, building a seismic data interpretation project overall life cycle workflow model which comprises four stages: starting, planning, executing and ending; the execution stage comprises quality control stage formulation and quality check table generation; s2, setting quality control points of the whole process of the seismic data interpretation project; s3, customizing quality control points, and obtaining a quality control point time sequence combination through data modeling; s4, executing a time algorithm on the quality control point time sequence and the quality control process to generate a Gantt chart; s5, executing a distribution algorithm and parameters according to the quality control point time sequence combination to obtain a quality control distribution scheme; s6, quality control point auditing is completed; and S7, in the process of completing the quality control task, automatically generating a corresponding quality check table. According to the invention, seismic data interpretation projects can be completed efficiently, orderly, accurately and automatically; the method is suitable for the seismic exploration industry and is used for automatically completing seismic data interpretation projects.

The application discloses an enterprise production management method based on digital twinning and workflow simulation, and particularly relates to the technical field of industrial internet and intelligent manufacturing, and comprises the following steps: constructing a physical production system digital twinning and a business process workflow model, dynamically correlating to form an integrated digital twinning model through a model fusion engine, driving by real-time events, deducing simulation on future production processes, and outputting bottleneck and conflict prediction, generating multiple alternative scheduling schemes by using a multi-objective optimization engine based on the prediction results, selecting an optimal scheme and analyzing the optimal scheme into control instructions to issue and execute, and realizing model self-correction and closed-loop optimization through real-time monitoring and feedback. The application solves the problem of disconnection between business and physical state caused by independent digital twinning and workflow, realizes full-process closed-loop management from prediction to execution, and improves the production self-adaptation and intelligent level.

The application discloses a traffic research and judgment analysis platform management method based on an Activiti process engine, and comprises the following steps: S1. process modeling: using a process modeling tool provided by the Activiti process engine, defining a workflow model related to people, vehicles, roads and business processes; S2. process deployment: deploying the defined workflow model into the Activiti process engine; S3. process execution and monitoring: triggering the corresponding workflow according to actual needs and monitoring in real time; S4. process optimization and iteration: according to feedback and data analysis results in actual application, optimizing and iterating the workflow model. The application applies the Activiti process engine to the traffic research and judgment analysis platform, can significantly improve the management efficiency, accuracy and automation level of the platform, optimizes the business process, enhances the scalability and flexibility of the platform, and greatly improves the security and reliability of data.

The invention belongs to the field of workflow model establishment, discloses a workflow model establishment method supporting multiple tenants and a related system, and realizes unified consideration of multi-tenant isolation and sharing of a workflow model. The tenants are identified through mechanism codes, different branch mechanisms can establish process models based on a unified workflow modeling framework, meanwhile, the independence and safety of the branch mechanisms are guaranteed, and mutual interference of process definitions is avoided. According to the method, the consistency and the expandability of cross-mechanism process management are improved. The unified modeling method ensures that the branch mechanisms are consistent in the aspects of flow logic, node configuration, key data generation and the like, so that centralized management and control and overall optimization of the headquarters are facilitated. Meanwhile, unique codes are generated for different tenants and stored, and it is guaranteed that quick recognition and tracking can still be achieved during system expansion. According to the invention, multiplexing and maintenance of the process model are simplified.

The invention provides a multi-model fusion electronic data association and evidence chain construction method and system, a multi-model fusion layer comprises a technical battle model, an AI model and a workflow model, and a knowledge base support layer stores evidence elements, case types and a role association matrix; the multi-model fusion layer performs semantic alignment training and performs collaborative analysis to generate a triple; the evidence chain construction layer is used for performing entity matching association and entity linking, generating enhanced entities, reasoning implicit association and constructing an entity relationship network; the evidence chain construction layer aggregates evidence elements strongly associated with an analysis target into an evidence chain link, calculates a credibility score, calculates a comprehensive basic probability score of the analysis target, performs quantity gain weighting to obtain an evidence chain integral, performs closed-loop verification and integrity evaluation, and generates an evidence chain containing the evidence chain integral; and the output layer is connected with a downstream analysis platform system and visually displays the evidence chain. According to the invention, evidence chain credibility evaluation is realized, and integrity and leakproofness of the evidence chain are enhanced.

Systems and methods for automated software testing and test data set generation using workflow path monitoring and modeling are provided. The system includes a workflow path monitoring processor that executes a workflow monitoring software module, an artificial intelligence / machine learning (“AI / ML”) software module, and a test script generation software module. The workflow monitoring software module monitors one or more workflow paths taken by a user using one or more software applications or platforms. The AI / ML module processes the one or more workflow paths monitored by the workflow monitoring software module and develops a workflow model for the software application or platform. The test script generation software module automatically generates one or more test scripts and / or test data sets based on the one or more monitored workflow.

The invention relates to a multi-terminal scene arrangement and one-key linkage method and system based on workflow, and the method comprises the steps: enabling an intranet workflow control system to model scene elements into nodes of terminals, approval, actions and the like, building a directed acyclic graph (DAG) structure based on business logic, and compiling the structure into an executable workflow model; in response to a linkage instruction sent from the extranet control terminal through the one-way transmission link, the intranet system triggers the approval node to perform permission verification, executes engine scheduling workflow after approval is passed, and issues an action instruction to the corresponding terminal of the extranet through the other one-way transmission link; and the external network terminal executes a linkage playing action and returns a receipt through another one-way transmission link. Visual arrangement of complex logic is achieved through DAG modeling, and by combining a multi-link cooperation and approval mechanism in a physical isolation environment, efficient one-key linkage and automatic scheduling of multiple terminals are achieved, and safety of an intranet core control system is ensured.

An AI-driven robotic process automation system learns and replicates user workflows across web, desktop, and legacy applications using computer vision and machine learning. During training, the system observes user actions with visual and structural UI context, segments the sequence into reusable tasks, and synthesizes a generalized workflow model. At runtime, a hybrid locator fusing vision with DOM / accessibility metadata binds abstract actions to live controls, while a self-healing subsystem detects anomalies and applies recovery actions. A continuous learning loop updates models and task definitions from execution telemetry so automations remain effective as interfaces evolve. The result is resilient “learn-once, run-anywhere” automation that reduces brittle scripting and maintenance overhead.

The invention discloses a workflow mining method for incomplete cross-organization logs based on a state diagram, which comprises the following steps of: extracting state diagram track information corresponding to cross-organization, and obtaining all state conversion relationships and adjacent activity pairs in the state diagram; traversing an incomplete cross-organization log, comparing each event in the log with a state conversion relationship in the state diagram and adjacent activity pairs one by one, and identifying and marking missing activities; then, on the basis of a state conversion relationship in the state diagram, supplementing missing activities, and generating a complete cross-organization log; extracting a cross-organization interaction rule in the complete log, identifying and recording a cross-organization effective interaction relationship, and constructing a cross-organization workflow net; and verifying the workflow net according to the completion accuracy and the rule consistency. According to the method, through introduction of the state diagram, the problems of fragmentation and missing of cross-organization logs are solved, incomplete logs can be accurately repaired, a high-quality cross-organization workflow model can be constructed, and support is provided for cross-organization process optimization.

The application provides a cross-supercomputing center big data workflow collaborative computing method and device, relates to the technical field of distributed computing and workflow scheduling, and comprises the following steps: obtaining a workflow model to be executed, the workflow model defining a plurality of computing tasks and data dependency relationships between the tasks; obtaining resource state information, data distribution information and historical execution statistical information of a plurality of supercomputing centers; constructing a cost prediction model for predicting task execution time consumption and data transmission time consumption based on the workflow model and the historical execution statistical information; and distributing the plurality of computing tasks to corresponding supercomputing centers based on the resource state information, the data distribution information and the cost prediction model, and generating a scheduling scheme containing task scheduling instructions and data pre-scheduling instructions. The application provides a reliable basis for prospective scheduling decision, thereby avoiding resource waiting or invalid pre-transmission caused by inaccurate estimation.

The application discloses a kind of dynamic workflow model service deployment methods, device, equipment and storage medium, method includes receiving the model generation request sent by user end, model generation request includes service parameter;According to service parameter, corresponding workflow template is matched and loaded, and the workflow template includes multiple nodes and the initial configuration information between each node;Business parameter is parsed by parameter injection engine, and according to the mapping rule of preestablished, dynamically injects business parameter into the target attribute of corresponding node in workflow template, to generate target workflow data;Target workflow data is sent to model inference engine and executes;The execution state of model inference engine is listened to, and after obtaining generation result, generation result is fed back to user end.The application realizes that business and logic are decoupled, supports workflow dynamic arrangement, and improves service flexibility, high availability and resource utilization.

The invention discloses an instance intensive workflow scheduling method and system based on dynamic particle swarm optimization, and the method comprises the steps: building a multi-objective optimization function with the minimization of the total workflow completion time and the minimization of the total system energy consumption as the objective through obtaining an instance intensive workflow model and a container cloud resource model; a particle swarm population is initialized by adopting two-stage coding, dependency correction is performed on task priority coding, and finally, a dynamic adaptive particle swarm optimization algorithm is executed to output an optimal scheduling scheme. A task execution sequence and an instance-virtual machine mapping relation are respectively and accurately represented through two-stage coding, and a dependency relation correction mechanism is combined to ensure that a scheduling scheme conforms to workflow topology constraints, so that the scheme feasibility is improved; through a dynamic adaptive particle swarm optimization algorithm, a particle swarm structure, a particle type and key parameters are adaptively adjusted in an iteration process, and the global exploration capability and convergence efficiency of the algorithm in a complex solution space are enhanced.