174 results about "Process engine" patented technology

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 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 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 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 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 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 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 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.

The invention discloses a construction method of a single-cell multi-omics data analysis system based on a containerization technology, and the construction method of the single-cell multi-omics data analysis system based on the containerization technology comprises the following steps: constructing a single-cell multi-omics analysis modular toolkit; a production mirror image is constructed on the high-performance cluster through a Single container engine, and deployment of a production environment is completed; a single-cell multi-omics automatic analysis platform is built through a snakemake process engine; and a JupyterLab interactive analysis platform for exploratory analysis of the single-cell multi-omics data is constructed. According to the single-cell multi-omics data analysis system construction method based on the containerization technology, the data acquisition link in the analysis process is accelerated, an automatic working process is formed to solve the problem of complex process, and the actual requirements of multiple users on a high-performance computing cluster for scientific exploration and analysis of single-cell data are met.

The invention discloses a dynamic self-verification method based on service flow-test flow homologous heterogeneous execution. The method comprises the following steps: uniformly describing service logic and a corresponding interface test contract through a strong type of domain specific language (DSL); the method comprises the following steps: simultaneously compiling homologous DSL descriptions into stateful business workflows executed by a process engine and stateless and combinable atomic test contract sets called by a test executor by utilizing a double-path compiling engine; during operation, loose coupling synchronous triggering and execution of a service flow and a test flow are realized based on a high-throughput event bus, and real-time and high-fidelity contract verification, performance monitoring and chaos probe testing are performed on cross-system interface calling in a production environment. According to the invention, the traditional post-event and off-line integration test is converted into the in-event, on-line and continuous system endogenous capability, and the industrial problems that the complex enterprise system group integration test is difficult and the operation and maintenance monitoring is passive are effectively solved.

The invention relates to a mixed collaborative approval method and system based on a process engine and a large model, and relates to the technical field of intelligent approval, and the method comprises the steps: obtaining an approval request, and extracting approval content and approval metadata; based on the rule cluster, performing regularized screening discrimination on the approval metadata, and dividing the approval request into a first alternative request set and a second alternative request set; performing partial normal analysis on the approval content corresponding to the first alternative request set, and extracting a third alternative request set; and performing automatic routing examination and approval according to the first, second and third alternative request sets, sending an automatic routing examination and approval result and the examination and approval request to the user terminal for verification decision, and outputting an examination and approval result according to a verification decision result. According to the method and the system, the problems of low complex service approval efficiency, inaccurate risk identification and insufficient intelligent level caused by the fact that a traditional approval system cannot effectively process unstructured complex tasks are solved.

The invention discloses a multi-source heterogeneous data task arrangement method and system based on a process engine, and the method comprises the steps: accessing multi-source heterogeneous data through a pluggable data source adaption assembly, and converting the data into a unified internal data model; process modeling and task arrangement, wherein a process model comprises a start event node, a batch processing task node, a stream processing task node, a gateway node and an end event node; the limitation of a traditional static FGA model is broken through, and mixed arrangement of batch processing and stream processing in the same process model and complex process control based on parallel and containing gateways are supported; task whole-process tracking is realized through a traceId mechanism, so that fault positioning and operation monitoring are facilitated; flexible self-definition of processing logic is realized through SDK plug-in and Groomy script support, and developers do not need to write codes on a large scale; and any task process result can be quickly packaged into REST API, so that the data service reusability is improved.

The invention provides an intelligent process task allocation method and system based on combination of Activiti and machine learning, and relates to the technical field of machine learning, and the method comprises the steps: collecting multi-dimensional road conference process data, and carrying out the data cleaning; processing and calculating the multi-dimensional road conference flow data, and extracting road conference type features, task emergency degree features and compliance approver task load features; a task allocation model is constructed, the task allocation model is trained based on the extracted features, and the model is used for predicting task approval time of different approvers; integrating the trained task allocation model to an Activiti process engine, and when a process task reaches an approval node, calling the model to calculate predicted approval time of candidate approvers; according to the predicted approval time dynamic allocation task, selecting the compliance approver with the shortest predicted approval time to execute the current approval task; newly added approval data are collected regularly, and the task distribution model is retrained to iteratively optimize the prediction effect.

The invention discloses a low-code self-defined work order design method and system and a storage medium, and belongs to the technical field of work order self-defined design, and the method comprises the steps: carrying out the analysis and business modeling of a business scene, and obtaining a new business work order; performing work order process configuration on the newly-built business work order based on a process engine; configuring a form for each link of the configured work order process based on a form engine; performing scheduling rule configuration on the form of each process node based on a middle table rule engine; and starting the configured form based on the scheduling module, and completing the creation and processing of the new business work order. According to the method, the work order is configured in a low-code or code-free mode, a newly-added business scene is quickly supported in a form process customizing mode, the flexibility of the system is improved, and the customization capability is enhanced. The service rule is stripped from the service code by docking the middle station rule engine, so that the scheduling rule is flexible and configurable, automatic arrangement, scheduling and execution of the rule are realized, and the efficiency is improved.

The invention discloses a method for automatically processing a business process embedded with a man-machine interaction node, and relates to the technical field of business process processing. Modeling is carried out according to BPMN2.0, node logic and data formats are defined, visual modeling is carried out through a tool, and version control is carried out; identifying a manual intervention scene, embedding an interaction node, configuring a multi-trigger condition, and adapting to multiple terminals and an interaction template; deploying a process engine, configuring parameters and mapping a system interface; the task is pushed when the interaction node is triggered, and the engine drives the process after user operation; abnormal and operation logs are recorded, stored and analyzed; and generating an execution report, regularly analyzing the bottleneck, and optimizing the process and parameters. According to the method, the man-machine interaction node is flexibly embedded, and the process execution flexibility and stability are improved; priority and response time efficiency are optimized, and risk management and control are enhanced; authority is refined, data are integrated, the operation and maintenance and iteration efficiency is improved, and the multi-service scene requirement is met.

The application discloses a lithology identification active learning method and system based on BPMN, and the system comprises a BPMN process front-end module, a data set labeling module, a lithology identification active learning task module, a dynamic form module, a camunda process engine module, a model deployment module and a storage module. The application automatically trains a target on a server side based on a BPMN2.0 specification to realize a lithology identification function. The lithology identification active learning method based on the BPMN is used to increase the calculation of the credibility, the labeling candidate set extraction module and the labeling module on the original machine learning steps, improve the parameter learning, the model training and the complexity through the active learning mode of the machine, improve the model effect, and improve the work efficiency.

The invention provides an iron tower operation management method and device based on process engine driving, and the method comprises the steps: calling a business process management engine, constructing a business process instance according to an iron tower construction process, and operating the business process instance; dividing the target area into a plurality of grid units in response to the situation that the business process instance flows to the site selection node, and determining the score of each grid unit; determining the position information of the target grid unit with the highest score as the site of the to-be-built iron tower; and returning the site to the business process instance, and driving the business process instance to flow to the next node. The business process instance of the iron tower business is constructed and operated based on the business process management engine, automatic circulation of the whole life cycle of iron tower construction is realized, and the overall efficiency and response speed of iron tower operation management are improved. In a site selection link, grid processing is performed on a target area of the iron tower, quantitative scoring is performed in combination with population thermodynamic information and stock site information, and the accuracy of site selection is ensured.

The application discloses a kind of based on intelligent service handling process management and control platform, specifically related to computer technology field, management and control platform is built-in dynamic process engine module, dynamic process engine module is used to parse third-party platform service process structure, support visual configuration process node and rule, realize the automatic execution and scheduling of process, and monitor feedback is carried out to process execution process.The application is adapted to the dynamic change of third-party platform by automatic analysis, strengthens learning dynamic scheduling resource, whole-link monitoring and intelligent diagnosis, systematically solves the problem of high adaptation cost, inefficient resource scheduling, insufficient monitoring capacity in traditional process control, and comprehensively improves the automation rate, execution efficiency and stability of service handling process.

The invention discloses a business process engine scheduling method and device, equipment, a storage medium and a product. The method comprises the following steps: scheduling a flow chart model of a business process; based on the flow chart model, starting a first thread for executing the business process instance; if it is determined that the first thread is executed to the system task node of the business process instance, generating task record information of the to-do task; and starting a second thread for scheduling the system task based on the task record information, and executing the to-do task based on the second thread. Thus, when the first thread used for executing the business process instance is executed to the system task node, only the task record information of the to-do task is generated; according to the method, the second thread used for scheduling the system task is started based on the task record information, and the to-do task is executed based on the second thread, so that decoupling of the process scheduling thread and the task scheduling thread is realized, the load of the process scheduling thread is reduced, and the flexibility of process scheduling and the independence of task scheduling are improved.

The invention relates to the technical field of after-sales process scheduling, in particular to a clock after-sales task assignment method and system based on a process engine, and the method comprises the following steps: obtaining a request extraction time identifier state, replacing a path to adjust a node update sequence after a transfer instruction is generated, completing task assignment, and generating a record. According to the method, the response time node is generated by extracting the task request time to realize accurate definition of the task response period, whether the task is overtime or not is dynamically judged to construct a delay identification mechanism, and path reconstruction is carried out in combination with a delay identifier to realize self-adaptive replacement and priority redefinition of a task flow path. The method comprises the following steps: establishing a task, identifying and executing redundant nodes, dynamically applying an acceleration node template to optimize an execution link, constructing automatic mapping between the task and a terminal to complete final task assignment, realizing unification of task response control, exception handling, adaptive path optimization and efficient task delivery, and improving clock after-sales task processing efficiency and service response quality.