236 results about "Process engine" patented technology

The invention provides an intelligent laboratory full-process collaborative management system and method based on multi-dimensional data fusion, and the method comprises the steps: obtaining an original data stream from laboratory instrument equipment, carrying out the format recognition and conversion of heterogeneous instrument data through a standard protocol adapter, and generating a first data set in a unified format; aiming at the first data set, executing automatic analysis by adopting data middleware, and integrating into a structured second data set based on a metadata rule of field mapping and unit conversion; according to the second data set, a multi-source data fusion model is constructed, data are classified according to instrument types through batch processing and aggregated according to timestamps, and a fused third data set is generated; aiming at the initial process configuration, adjusting a node sequence and a parameter threshold value by using a visual design tool, and generating an optimized process configuration adaptive to the diversified scene; according to the optimized process configuration, process scheduling is executed through a dynamic process engine, execution time and resource occupation are monitored in real time, and a process execution log is generated.

The invention provides an enterprise financial comprehensive management system based on an intelligent technology, and relates to the technical field of financial management. The accounting intelligent subsystem is used for acquiring financial data, performing semantic analysis and conversion on the financial data through a preset rule and a multi-stage data mapping mechanism, generating a standardized accounting service instruction and issuing the standardized accounting service instruction to an automatic process engine, thereby automatically generating a financial document meeting an accounting criterion; the financial management subsystem is used for integrally realizing execution of backlog management, compliance guidance manual query and financial data structured storage according to a preset standardized process; and the business service subsystem is used for providing tax-related business service, asset management service, fund management service and operation management service processing and guidance for enterprises through modular design. The invention aims to improve the operation efficiency, reduce the error rate, break information islands, realize effective integration and utilization of resources, and provide powerful support for decision making of enterprises.

The invention relates to the technical field of data processing, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a payment business processing method based on a process engine, which comprises the following steps: standardizing an input / output interface, packaging business logic into business nodes, and storing the business nodes in a node library. And selecting nodes, configuration information and a connection relationship according to service requirements, and generating a process model. And starting the process engine, and converting the process model to obtain a process instance. And extracting node information and a connection relationship, scheduling node execution, obtaining real-time data, and generating a dynamic adjustment decision. And according to the decision and the real-time data, adjusting a process instance execution path and node parameters, scheduling node execution, completing payment service processing, and storing process instance information in a historical record library. By standardizing the interface, packaging the service nodes, generating the process model and dynamically adjusting the execution path and parameters, the payment service processing is efficiently completed, the flexibility and efficiency are improved, and the process information is convenient to store and trace.

The invention discloses a scheduling and approval process control method and device for digital product online leasing, and the method specifically comprises the steps: carrying out the cloud native operation environment preparation, building a process control system based on a workflow engine capable of being arranged, carrying out the system initialization, and carrying out the operation of a cloud server; comprising the steps of initializing a lease process engine, an equipment resource scheduling module, an approval strategy and credit engine and a performance monitoring and state management system; and then a lease application and process control method, an equipment scheduling and conflict detection method, an examination and approval execution and process driving method and a performance monitoring and state write-back method are designed in sequence. After a user submits a leasing request, generating an approval process and distributing the approval process to an approval node; executing resource allocation and locking after the approval is passed; an event-driven mechanism is adopted to manage state circulation of all stages of leasing, and reverse-driven scheduling adjustment of approval results is supported. According to the invention, the approval efficiency of online renting of digital products is improved, the manual intervention cost is reduced, and the rationality and traceability of equipment resource configuration are guaranteed.

The invention discloses a lightweight knowledge graph rapid construction method and system based on an NLP technology. The method comprises the steps of preprocessing an unstructured text and segmenting the unstructured text into semantic segments; unsupervised clustering is combined with the contour coefficient to determine the optimal clustering number, and a semantic association fragment cluster is obtained; performing word segmentation, part-of-speech tagging, NER and entity linking on the fragment cluster, extracting an entity and initial relationship, and fusing semantic similarity, TF-IDF word frequency collaboration degree and co-occurrence frequency to calculate a relationship edge weight; constructing a lightweight knowledge graph; in the question and answer stage, questions are disassembled through a process engine, related sub-graphs are retrieved, and answers with reasoning links are generated. The system correspondingly comprises a text preprocessing module, a clustering module, an entity relation processing module, a graph construction module, a question and answer reasoning module and a storage module. According to the method, the construction cost is reduced, the interpretability and the module coupling degree are improved, multiple scenes such as government and enterprise public opinions and medical assistance are adapted, and the problems of weak generalization, poor real-time performance and'black box 'in the traditional technology are solved.

The invention discloses a workflow and form association method and device based on a low-code platform and a medium, and belongs to the technical field of computer software. The method comprises the following steps: constructing a workflow consisting of a plurality of workflow nodes based on a low-code platform, and configuring an identifier for the workflow; defining a form, and associating a form field in the form with a workflow variable in the workflow to generate an associated database; converting the workflow into a standardized workflow, and issuing the workflow through a process engine; the form template is stored in a metadata table, a process automatic triggering mechanism based on a form submission event is configured, and the triggering mechanism comprises data format verification and authority verification; constructing a process instance table, and mapping the process instance table, the workflow variables and the form fields; and obtaining a submitted form, and analyzing the submitted form according to the association database to update the process state to the process instance table. By means of the method, flexible adaptation of the workflow and the form in multiple scenes is achieved.

The invention provides a flow and form decoupling cooperative processing method, and relates to the technical field of business flow management, and the method comprises the steps: constructing a layered architecture, separating a flow control layer from a form service layer, defining a flow node jump rule by the flow control layer based on a BPMN standard, and dynamically defining a form structure by the form service layer through JSON Schema; a form identifier is declarated in the process definition file, a corresponding form template is matched through a dynamic mapping service according to context information, and the context information comprises a process instance state, a user role, a device type and a service type; establishing a data sandbox isolation mechanism, generating a unique data space identifier for each process instance, and managing data access authority through a multi-dimensional isolation strategy of a tenant level, a service level and a process instance level; deploying an event bus communication mechanism, triggering two-way communication between a process engine and a form engine through a predefined event type, and ensuring the consistency of cross-system operation by adopting a transaction compensation mechanism.

The invention discloses an Internet of Things process engine automatic arrangement method and system based on a large model. The method comprises the steps of obtaining a process demand described by a natural language of a user; the method comprises the following steps: analyzing a natural language of a user through a first-layer large model, and identifying related equipment, variables, conditions and action information; information identified by the first-layer large model serves as input of a second-layer large model, and the second-layer large model matches actual corresponding equipment and variable information under the user permission based on the user token, the equipment and the variable information; transmitting actual corresponding equipment, variables, conditions and action information under the user permission to a third-layer large model; and the third-layer large model matches the corresponding flow nodes according to the received information, the matched flow nodes are connected in series through a connecting line, and a structured flow JSON is generated. According to the method, the fuzzy natural language intention is gradually converted into an accurate and executable structured process through the three-layer large model, and the accuracy of an output result of each link is improved.

The invention relates to the technical field of collaborative management, in particular to a business collaboration method based on a process engine, which comprises the following steps: acquiring approval process nodes and post fields, establishing node parameter mapping, extracting customer reconciliation process field paths, generating a field coverage set, analyzing contract archiving responsibility actions, and constructing a responsibility sequence link. And matching a financial reimbursement process cooperation path, correcting an offset node to generate a cooperation task flow, calculating an internal instruction process node priority, and generating a task triggering list. According to the method, the node fields and the role identifiers in the approval process are obtained, the field consistency mapping relation is constructed, and a field continuous path screening mechanism is combined, so that the penetrating power and the tracing accuracy of parameters among cross-process nodes are improved, and the sequence of node responsibilities has a verifiable logic chain; through a node offset detection and path connectivity construction mode, accurate task execution sequence control is provided in multi-source task scheduling.

The invention relates to the technical field of communication, in particular to an intelligent chemical single-process optimization design method and system based on dynamic decision, work order state change is carried out through a process engine according to a rule result, and when a rule engine returns a single node, a state field of a current work order record is updated as a target node name; the method has the beneficial effects that the flexibility and the automation degree of the process are improved, automatic adjustment of the process path is realized through a dynamic decision mechanism, manual intervention is reduced, and the processing efficiency is improved; multi-system integration and cooperative processing are supported, and seamless connection with a third-party system is realized due to an open interface and an integration capability, so that the cooperative efficiency of a business process is improved; the mobile terminal is adapted, so that the service linkage efficiency is improved; the process is imported and exported in a one-button mode, the traceability and stability of process configuration are ensured through a process management and version control mechanism, and maintenance and optimization of the process are facilitated.

The invention discloses a supply chain order business automatic processing system and a method thereof. The system comprises a dynamic intelligent center, an elastic process engine, a green loop network and a trusted security layer, the dynamic intelligent center dynamically optimizes decisions through federated learning and generative AI, and the elastic process engine realizes flexible recombination of processes based on micro-service and a low-code platform. The green circulation network utilizes a block chain to track carbon footprints and manage reverse resources, and the credible security layer adopts quantum encryption and dynamic authority to guarantee data credibility. The corresponding method comprises the steps of combining a multi-party data training model and generating a multi-scheme, performing a micro-service splitting and low-code configuration process, driving intelligent contract transaction by a carbon label, and performing quantum encryption evidence storage and anomaly detection. Through the edge-cloud collaborative architecture, the scheme synchronously improves the efficiency, flexibility and sustainability, solves the problems of insufficient intelligence, framework stiffness and security defects in the prior art, and is suitable for complex scenes such as e-commerce and manufacturing.

The invention discloses an intelligent business handling process management and control platform, and particularly relates to the technical field of computers, the management and control platform is internally provided with a dynamic process engine module, and the dynamic process engine module is used for analyzing a third-party platform business process structure, supporting visual configuration of process nodes and rules and realizing automatic execution and scheduling of a process. And the flow execution process is monitored and fed back. According to the method, through automatic analysis and adaptation of dynamic changes of the third-party platform, reinforcement learning of dynamic scheduling resources, full-link monitoring and intelligent diagnosis, the problems of high adaptation cost, low resource scheduling efficiency and insufficient monitoring capability in traditional process management and control are systematically solved, and the automation rate, execution efficiency and stability of the business handling process are comprehensively improved.

The invention relates to the technical field of artificial intelligence, and discloses a business process configuration method based on Activiti and AI decision, and the method comprises the steps: collecting the historical execution data of a business process through a process instance monitoring module, generating a process behavior feature data set, carrying out the training processing of an AI decision model based on the process behavior feature data set, and carrying out the analysis of the AI decision model. A business process decision tree model is constructed, AI decision routing labels are configured for decision nodes in an Activiti process engine, non-intrusive intelligent decision integration is achieved, and when a process instance is executed to a key decision node, a system automatically calls the pre-trained business process decision tree model to conduct real-time path analysis and generate an optimal dynamic routing instruction. The problem of decision stiffness caused by the fact that a traditional workflow depends on artificial experience configuration is solved, the accuracy and adaptability of flow branch selection in a complex service scene are improved, and meanwhile the compatibility and stability of an original flow engine are guaranteed.

The invention discloses an intelligent verbal skill process configuration system and method based on a dynamic rule engine, and the system comprises a configuration analysis module, a process engine module, an execution engine module and a large model intention recognition module. The problems of rule solidification, high maintenance cost and low intention recognition accuracy in existing verbal skill process configuration are solved. The configuration analysis module analyzes a JSON format verbal skill rule configuration file to realize visual definition and dynamic update of the rule; the process engine module completes rule instantiation through variable replacement and drives dynamic routing based on an intention recognition result; the execution engine module instantiates a service class by using a reflection mechanism to realize decoupling of rules and service logic; the large model intention recognition module innovatively adopts a semantic similarity weighting algorithm, and intention recognition accuracy is remarkably improved by calculating semantic vector cosine similarity of user input and branch intention and combining service weight and context correlation degree.

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 a government affair function efficiency optimization method and system based on multi-modal data fusion, belongs to the technical field of artificial intelligence and intelligent services, and aims to solve the technical problem of how to optimize government affair functions from a data level, a process level, a decision level and a feedback level and improve government affair processing efficiency. According to the technical scheme, the method comprises the following steps: data acquisition: acquiring data from a government affair extranet platform, a paper document and a third-party database in real time or in batches in a government affair extranet data capture mode, acquiring original data, constructing a data pipeline by using Apache NiFi, and connecting an enterprise benefit service and a grassroots governance interface; intelligent data analysis and processing: performing deep analysis, semantic understanding and regularization processing on the collected original data, extracting structured information, generating decision support content, and realizing conversion from data to knowledge; process execution is optimized through an Activity 7 process engine; and closed-loop interaction feedback.

The invention relates to a visual process automatic arrangement method and system, and belongs to the technical field of computers.The method comprises the steps that a natural language requirement input by a user is obtained; modeling knowledge is determined, logic typesetting and structured processing are conducted on the natural language requirement input by the user and the modeling knowledge through a large language model LLM, and XML process definition data meeting the BPMN standard are generated; sending the XML process definition data conforming to the BPMN standard to a process engine so as to create a visual process model; and rendering the visual process model to a front-end interface for a user to review, and determining a review result. According to the method, business personnel can directly participate in process design without learning professional modeling languages such as BPMN, and a business-driven development mode is really realized.

The embodiment of the invention discloses a multi-engine task processing system and method, electronic equipment and a readable storage medium, and relates to the technical field of computers. According to the multi-engine task processing system provided by the embodiment of the invention, a plurality of service clusters can be configured to execute the task processing instructions corresponding to different instance identifiers, so that a task allocation process and a task execution process can be decoupled, and the same task processing instruction is executed by the same target service cluster as far as possible; and the same instruction is prevented from being processed across multiple databases. Due to the fact that the dependency relationship does not exist between the service clusters and the process engines in the service clusters, a user can randomly increase or reduce the service clusters and the process engines in the multi-engine task processing system, the problems that the bearing capacity of the system is insufficient, the transformation cost is high, and capacity expansion is difficult are solved, and the user experience is improved. And meanwhile, the system has the capabilities of high concurrency, large capacity, high stability and high expandability.

The present application relates to an optimization method, system and medium for a process engine in a high-concurrency process scenario, including the following steps: attaching a priority tag to a process task; attaching a resource type tag to a process task; the process engine is provided with an early warning mechanism for entering the high-concurrency process state. When the early warning is triggered, new tasks enter the waiting queue, and the process engine preferentially processes tasks with higher priorities. When the priorities are the same, the process tasks with resource type tags matching the system resource type with a higher idle rate are preferentially processed according to the real-time idle rate of the system resources; the process engine is provided with an exit mechanism. After exiting the high-concurrency process state, new tasks no longer enter the waiting queue but enter the normal processing queue of the process engine. By establishing a high-concurrency process state early warning mechanism and a high-concurrency task processing method, the present application enables the process engine to quickly and efficiently process multiple concurrent tasks when facing a high-concurrency task scenario, alleviating task backlog.

The invention provides a measurement and control method and device based on a general process engine, electronic equipment and a storage medium, and relates to the technical field of spacecraft measurement and control. The method comprises the following steps: configuring function nodes through a pre-designed general process engine; receiving a satellite measurement and control task sent by an upstream system; wherein the satellite measurement and control task comprises task time; based on a flow scheduler of the general flow engine, when the current time reaches the task time, determining a target function node in the function nodes based on the satellite measurement and control task; and calling the target function node to realize the satellite measurement and control task. The unified scheduling platform is constructed through the general process engine, so that system resources and satellite data can be integrated, the equipment state can be collected and analyzed in real time, the measurement and control task can be automatically scheduled and completed, the measurement and control efficiency is improved, the cost is reduced, and stable operation of the measurement and control task is ensured.

The invention provides a business process intelligent configuration and security execution method, system and device, and the method comprises the steps: converting a natural language demand into a BPMN 2.0 process model based on a large language model and an enterprise knowledge base; the service rule description is converted into a Grouping script through multi-level security compiling; the process and the script are executed in the Flowable process engine integrated with the security sandbox, and execution data are collected; and calculating a process health score based on the data, generating and implementing an optimization suggestion, and feeding back a result to the knowledge base. The problems that a traditional process system depends on manual coding, the script safety is poor, and continuous optimization is lacked can be solved. The full-link automation and intelligentization of the business process from design, execution to optimization can be realized, the development efficiency and the system security are greatly improved, and the process has the self-evolution capability through closed-loop feedback.

The invention discloses a data query method and device based on a process engine, and the method comprises the steps: receiving a task submission request of a user, and calling a preset process template according to the task submission request; according to the BPMN graph and the task submission data, a process instance and a task instance of the current task node are generated; the process instance comprises a process instance ID; creating a token for the current task node, binding the flow template, the flow instance and the task instance of the current task node with the token of the current task node, and storing the token of the current task node into a cache; when the current task node receives a task query request fed back by the rear end, querying the token of the current task node from the cache according to the flow instance ID of the current task node; and querying the corresponding data object from the cache according to the token ID of the current task node. According to the invention, the query complexity can be reduced, and the flow business processing efficiency can be improved.

The invention relates to the technical field of data management, in particular to a project data management system for research and development of small and medium-sized enterprises, which comprises a data acquisition module for acquiring research and development project data of the small and medium-sized enterprises through a multi-source data fusion technology; the quality diagnosis module analyzes research and development data by applying a deep learning network, and automatically identifies and predicts data quality abnormity and a potential risk mode; the process collaboration module is combined with artificial intelligence and a process engine technology, and automatically adjusts research and development task processes and authority distribution according to project progress and member collaboration requirements; the resource interaction module coordinates resource allocation, sharing and recovery between the research and development project and the enterprise internal resource pool; and the decision optimization module coordinates data of each module and a research and development project target to realize collaborative optimization of project planning, resource allocation and risk control, so that the problems of data fragmentation, low flow efficiency and unreasonable resource allocation in the research and development process of small and medium-sized enterprises are solved, and the research and development efficiency and the achievement transformation capability are improved.

The invention discloses a method for managing service nodes capable of being dynamically expanded based on a Camuda process engine, which belongs to the technical field of electric digital data processing and comprises the following steps of: uniformly configuring service process nodes into a pointing proxy delegation class; querying an external mapping table based on the execution context to obtain a business logic unit identifier; obtaining metadata from a logic registration center according to the identifier, and dynamically loading and instantiating a business logic implementation class through a sandbox class loader; driving service logic execution through a security context object of a white list only exposure method; and recording a full-link audit log. According to the method, structural decoupling of process definition and service logic is realized, so that the process definition does not need to be modified during service change, and dynamic replacement and gray release are supported; through sandbox isolation and security agent, isolated operation of dynamic codes and security and stability of an engine are ensured; and in combination with an audit tracking and fusing mechanism, the observability, the reliability and the operation and maintenance efficiency of the system are improved.

The invention provides a task process repairing method, device and equipment, a medium and a product, and the method can be applied to a process engine, such as a process engine in a low-code platform. The method comprises the steps of presenting a first task flow in a flow configuration page; in response to a test operation for the first task process, presenting a test result of the first task process; and in response to the test result representing that the first process node in the first task process generates an execution error, repairing the first process node in the first task process, and generating a second task process. In the method, the natural language processing capability of the language model is utilized to carry out targeted repair on the process node with the execution error, so that the error existing in the task process is automatically repaired, the correctness and the stability of the task process are improved, and the task process is ensured to normally execute the business task.

The invention provides an ephemeris-assisted heaven and earth fusion network arrangement method, and relates to the technical field of wireless communication, and the method comprises the steps: obtaining the orbit parameters of a satellite, and forming an ephemeris database according to the orbit parameters; outputting position matrixes of the current time window and the next time window of the satellite by using an orbit extrapolation model; predicting the network topology change through the position matrix change of the two time windows; the orchestrator triggers a process engine based on a network topology and a resource monitoring state, the process engine selects a preset strategy template rule and dynamically schedules a work process, and the VNF manager activates a satellite VNF and a ground VNF according to an orchestration instruction to complete an orchestration function defined by a strategy template. According to the method, the flow engine is triggered based on the network topology state change and the resource monitoring state to select the strategy template, services and resources of the whole system are arranged and scheduled, and the resource utilization efficiency and the robustness of coping with the network topology change are improved through reasonable task allocation.

The invention discloses a cloud resource management method and device, a medium and equipment. The method comprises the following steps: receiving a standardized resource request submitted by a user, firstly converting the standardized resource request into structured task data, then analyzing the structured task data by utilizing a preset process engine, and generating an execution process containing an atomic operation sequence. Based on a preset event-driven architecture, the execution process is distributed to the adapter cluster, the adapter cluster generates each standardized instruction according to the atomic operation sequence, adapts the instructions into an interface format which can be identified by the target platform through a preset protocol conversion module, and finally outputs the instructions to the interface of each target platform. According to the process, end-to-end automatic management from user requests to cross-platform resource operation is realized, and the efficiency and flexibility of heterogeneous cloud resource management are improved.

The invention discloses a work order processing method and device based on an artificial intelligence technology, and the method comprises the steps: receiving unstructured instruction information, extracting semantic information in the instruction information through a semantic analysis model, and building a current work order; calling a target process template from a pre-established template library according to the semantic information, and determining an execution process of the current work order according to the current work order and the target process template; calling a target scheme from a pre-established scheme library according to the current work order; executing the current work order according to the execution process and the target scheme; semantic analysis is performed through an artificial intelligence technology, so that processing of unstructured instruction information is realized; a dynamic process template is established through a process engine, and the dynamic template comprises dynamic nodes, so that custom adjustment of an execution process is realized; by analyzing the work order and selecting the target scheme from the scheme library, assistance of the execution process is realized.

The invention provides an 8D quality improvement collaboration method and device based on process engine driving and a medium, and can improve the problem solving speed, enhance the quality improvement effect, improve team collaboration and communication and enhance the continuous improvement ability, and the method comprises the steps: creating an 8D process corresponding to each production stage of the whole production process of a product; when it is determined that a quality problem is found in a first production stage, a target 8D process is automatically matched, the first production stage is any one of the production stages, and the target 8D process is an 8D process corresponding to the first production stage; the driving process engine executes the target 8D process according to a specified node sequence constraint mechanism, in the process, the driving process engine uses an experience library to automatically fill an 8D report field, and the 8D report field is a field needing to be filled in corresponding steps in the target 8D process; and the process engine is driven to uniformly store process data generated when the process engine executes the target 8D process into a specified storage device.

The invention discloses a business process construction method and system based on a process engine, belongs to the technical field of business process automation, and aims to solve the technical problem of how to realize intelligent generation, dynamic adjustment and one-key deployment of a business process. Comprising the steps of performing semantic analysis on a demand document uploaded by a user based on an AI large model, generating a process framework based on a key business entity, a business rule and a process node, and outputting a process definition file; based on a natural language interaction mechanism, calling the large model to perform semantic analysis on a natural language instruction input by a user, and correcting the process framework based on an analysis result; integrating the corrected process definition file to a process engine, and performing automatic verification and simulation operation on a process framework; and realizing version management, containerized packaging and one-key release of the process based on an automatic deployment assembly line.