52 results about "Business process modeling" patented technology

The invention discloses a business and financial integrated management system, which constructs a high-elasticity and easy-to-expand business and financial integrated management system through deep fusion of cloud native and micro-service architecture. The system realizes real-time acquisition and cleaning of business and financial data through a standardized data interface and an ETL technology, and data islands are thoroughly broken; a business process modeling tool cooperates with a workflow engine, financial management and control nodes are embedded into the whole business process, and the real-time performance of budget execution and cost collection is ensured; the intelligent analysis module combines OLAP and machine learning, provides multi-dimensional data insight and risk prediction, and significantly improves decision scientificity. In addition, due to the distributed log and role grading permission design, the safety and auditing performance of the system are enhanced. The system not only reduces the manual operation error rate and IT operation and maintenance cost, but also assists an enterprise in realizing refined operation and agile decision making through an automatic process and an intelligent early warning mechanism.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The invention discloses an intelligent tracking analysis system for business, and particularly relates to the field of data intelligent analysis and business process modeling, the system accesses an enterprise internal multi-source heterogeneous system, collects structured and unstructured data related to the process, and constructs a behavior map model; and compressing and extracting key nodes and behavior fragments in the multi-role cooperation path. Simulating a future process trend by using a shadow business body, predicting a possible path and an accompanying risk thereof, and introducing a multi-agent strategy game mechanism to realize dynamic game and consensus formation of each role in path selection; and correcting the deviation behavior in the process by combining real-time path monitoring and an abnormal intervention mechanism. According to the method, dynamic modeling, prediction and intervention of a complex process can be realized, and the problems of approval lag, path conflict and the like are effectively avoided. Compared with a traditional control mode, the method has higher adaptability, flexibility and evolutionary ability, and is suitable for various high-collaboration scenes such as finance, government affairs and engineering.

The invention provides a port logistics intelligent simulation and decision optimization platform based on a digital twin technology, and the platform comprises a basic layer which provides calculation, storage, network and basic software support; the resource layer integrates data resources, model resources and algorithm resources and is used for managing port multi-source data, business process models and intelligent algorithms; the digital twinborn layer is used for constructing and maintaining a high-fidelity digital twinborn body synchronous with a physical port and realizing virtual-real mapping, dynamic data fusion and model self-evolution; the simulation layer is used for deducing based on the digital twin and comprises a simulation engine and an event driving and data interaction module; and the application layer is used for providing a user interface, analyzing decision and optimizing functions and supporting scheme simulation, evaluation and closed-loop optimization. According to the method, the high-fidelity digital twinborn body of the port can be constructed, real-time mapping, accurate simulation, prospective prediction and intelligent decision making of the whole process of port logistics are achieved, and a technical closed loop of data acquisition, digital twinborn, intelligent decision making and virtual-real linkage is formed.

The invention relates to the technical field of data processing, in particular to a complex semantic-oriented business process multi-agent modeling and intelligent error correction method and system. The method comprises the following steps: firstly, based on a BPMN meta-model, disassembling business process elements, analyzing BPMN specifications, forming a structured framework of business process modeling, processing unstructured texts in parallel through an intelligent agent group, identifying business process key concepts, mapping the business process key concepts into semi-structured information, and generating a preliminary extraction result; verifying the integrity of the preliminary extraction result based on a BPMN specification, and generating an information integrity verification report; based on an information integrity verification report, missing information of the preliminary extraction result is retrieved through a knowledge base and complemented; performing secondary verification on the complemented extraction result, and correcting the complemented extraction result based on business logic and user requirements; and generating an XML code and a visual flow chart conforming to the BPMN specification based on the corrected extraction result. According to the method, the problems of semantic fracture and structure deficiency of the complex semantic text in business process modeling can be effectively solved.

The invention provides a business process model instance construction method and device based on a data structure, and the method comprises the steps: carrying out the assembly according to a JSON structure and a business process drawn by a user, and generating a business process JSON data structure; performing data serialization on the business process JSON data structure to generate a database process draft basic information extension table; in response to a release process instruction input by a user, performing data deserialization according to the database process draft basic information extension table, generating business process series information and updating a business process series table; in response to a process starting instruction input by a user, determining a business process series information instance from the business process series table; according to the business process model architecture, the business process series information instances are spliced, and the business process model instance is generated, so that expansibility, maintainability and flexibility can be improved, front-end load work is reduced, complexity and error risks are reduced, and response speed is increased.

The invention discloses an enterprise business process reconstruction model realized through cloud service, which belongs to the field of cloud computing and business processes and comprises a space-time alignment data lake module, a self-evolution model reasoning module, a process optimization engine module, a real-time dynamic adjustment module and a digital twinning deployment module. By means of the model, multi-source heterogeneous business data can be effectively processed and integrated, and automatic optimization and reconstruction of the business process are achieved on the basis. Meanwhile, the optimized business process model can be executed in real time by realizing synchronization with a physical execution terminal. In the execution process of the business process, the stability and reliability of the business process are ensured by monitoring and processing abnormal conditions in real time. According to the model, the advantages of cloud services are fully utilized, the efficiency and quality of enterprise business process reconstruction are effectively improved, and a remarkable optimization effect is brought to business management of enterprises.

The invention discloses a business process automatic modeling method and device, electronic equipment and a medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: receiving and analyzing current multi-modal input description data in real time in a business process automatic modeling system architecture to obtain current multi-modal input intermediate representation description data; carrying out extraction through an entity relationship process extraction method, and generating a current process topological knowledge graph in combination with a process modeling standard adaptation method; verifying through a business rule atlas verification and identification method, and generating a current intermediate representation parameter with a semantic role; and through a dynamic model generation method, describing a current intermediate representation parameter with a semantic role, and generating and feeding back a current automatic modeling business process in combination with a historical business process modeling template. The problems that manual operation is highly relied on, and static characteristics and data input forms are rigid are solved, the flexibility and automation of business process modeling are improved, and the burden of manual processing is relieved.

The invention discloses an enterprise business process-oriented rapid modeling generation method, which relates to the technical field of business process modeling, and comprises the following steps of: after receiving a business process modeling request, executing structural similarity analysis, comparing a current process structure input with path vectors of a plurality of process templates, and generating a business process model; judging the structure coincidence degree and the condition node semantic consistency, and identifying whether the condition belongs to the condition of a multi-template combination generation process or not; and under the condition that a plurality of template merging generation processes are identified, extracting each path triggering frequency original value, a frequency sampling time range, a sample number, an acquisition strategy label and a path triggering distribution density corresponding to the condition judgment node, constructing a normalized offset vector, and outputting a normalized difference result. According to the method, the problem of inconsistent path frequency statistical calibers in multi-template process merging modeling is solved, and normalized evaluation and dynamic optimization setting of the default path are realized.

The invention relates to the technical field of business process modeling, in particular to a meta-model-driven interactive business process intelligent modeling method and system. The method comprises the following steps: constructing a meta-model framework containing core elements such as activities, events and gateways, and establishing a meta-model constraint rule base to define a structure legality rule of a BPMN2.0 specification; based on a domain ontology Schema and the domain exclusive large language model after instruction fine tuning, extracting a business entity and a process relationship thereof from the unstructured text; carrying out information integrity verification and logic consistency detection on the extracted BPMN elements by utilizing a constraint satisfaction algorithm and Petri net reachability analysis; displaying a difference label of the process sketch through an interactive verification interface, and realizing semantic correction and model iteration of a user on the process elements based on a natural language feedback mechanism; an XML code is generated by adopting a template-driven code generation strategy, and a flow chart is generated through a BPMN parser. According to the method, the business process modeling efficiency can be remarkably improved, and the manual intervention proportion in the modeling process is reduced.

The invention provides a maritime business standard operation program intelligent construction method and system based on multi-source knowledge fusion, and relates to the technical field of maritime business intelligent construction. Multi-source knowledge and multi-modal data of maritime business are collected firstly and then processed through a Transform technology to obtain a business knowledge graph and scene interaction data; a business process model is established based on the two, a business association network is constructed through a graph neural network to generate an operation program conforming to international and domestic dual standards, and then a standard operation program is formed after test optimization of an application test terminal integrating AR and a voice module, so that actual maritime affair requirements can be accurately met; and standardized and intelligent development of maritime affairs is facilitated.

The invention relates to the technical field of process automation, and discloses a process automation analysis method and device based on a structured document and a medium, and the method comprises the steps: generating the structured document of a target business based on the process logic and business rules of the target business; performing semantic analysis on document content in the structured document to obtain business semantics, and generating an abstract syntax tree corresponding to the target business according to the business semantics; acquiring an external dynamic parameter of the target business in real time, and mapping the target node and the external dynamic parameter in the abstract syntax tree into a label event in the business process model; generating a standardized process file corresponding to the target business according to the tag event and an extended tag event in the business process model; monitoring the service flow of the service platform in real time, and deploying the standardized process file into a publishing engine according to the service flow; and executing the business process of the target business through the standardized process file deployed in the release engine. According to the invention, the efficiency of process automatic construction can be improved.

The invention belongs to the technical field of image processing, and particularly discloses a subway security business approval method, system and device and a storage medium. Business process model matching and business process node judgment are carried out by obtaining business application data submitted by an applicant; and determining an OA docking approval mode, an OA docking data protocol and an OA docking execution condition according to the node information, generating an OA service data message, transmitting the OA service data message to an OA system end for approval to obtain a corresponding approval result, and then repeatedly executing service approval of a next node in this way until services corresponding to all nodes of the service process model are approved. The method can be applied to a corresponding subway security area platform to replace a traditional business approval mode of manually receiving and sending official documents and repeatedly inputting related application data, compatible connection and data circulation between the subway security area platform and an OA system are achieved, automatic process processing of official document approval operation is completed, and the service approval efficiency is improved. And the metro security business office examination and approval efficiency is improved.

This application relates to a method and related system for processing cross-domain heterogeneous data of a digital twin of an enterprise management building, including: acquiring a standard semantic library of the digital twin of the enterprise management building; receiving cross-domain heterogeneous process data from different management systems; acquiring system prompt words of a large language model; inputting the system prompt words and cross-domain heterogeneous process data into the large language model to obtain a business process model file output by the large language model; parsing the business process model file and extracting the node attributes of each process node from the business process model file; mapping the node attributes of each process node to the standard definitions and standard expressions corresponding to each management atom in the standard semantic library, so as to complete the semantic fusion of cross-domain heterogeneous process data from different management systems. The above method can automatically parse and transform cross-domain heterogeneous process data from different management systems into a unified standard format, thereby realizing the semantic fusion of cross-domain heterogeneous process data from different management systems.

The invention provides an information processing system. The information processing system comprises a device used for shooting a business process through an image acquisition device; means for collecting audio data and text data; the analysis device is used for analyzing the collected data and generating a business process model; the program generation device is used for generating an automatic program according to the business process model; and means for distributing the generated automation program to the terminal.

The invention relates to the technical field of computer software, and discloses an intelligent inspection system and method for an insurance business process based on a domain-specific language, and the system comprises a business process modeling and DSL module which carries out the unified abstraction and executable modeling of the insurance business process through the domain-specific language, and obtains a process model which can be executed by a machine; the intelligent inspection execution and data acquisition module drives the operation of the insurance business process through an execution process model, and acquires full-link business data of the insurance business process in the operation process; the service attribution analysis module is used for positioning an abnormal root cause in an insurance service process through an attribution algorithm based on the full-link service data; and the intelligent report generation module is used for generating a natural language inspection report through an AI large model based on the insurance business process context provided by the abnormal root cause and the process model. According to the invention, end-to-end monitoring, accurate root cause positioning and automatic intelligent report generation of the insurance service process can be realized, and the operation and maintenance efficiency of the insurance service is improved.

The invention relates to a modeling method and device for a power business process, computer equipment and a storage medium. The method comprises the following steps: acquiring graphical power business process data; converting the power business process data into a formal semantic model based on a token; determining a model state space scale of the formal semantic model, and performing process verification on the formal semantic model by adopting a verification mode matched with the model state space scale to obtain a verification result; and adjusting the formal semantic model according to the verification result, and taking the adjusted formal semantic model as the power business process model. By adopting the method, the modeling operation difficulty of the power business process model can be reduced, and the modeling efficiency can be improved.

The application belongs to the field of safety engineering in chemical industry production, and discloses a chemical process control system network risk analysis method based on multi-layer business process modeling and application, which comprises the following steps: analyzing the business process and data interaction relationship of the chemical process, and constructing a multi-layer business process model based on the BPMN2.0 standard; replacing the original device-centered method, an improved failure mode and consequence analysis centered on the basic business unit is proposed, the potential failure mode of the task is identified, the failure cause and consequence under different attack intentions are clarified, and the attack fault tree model is generated; finally, the risk analysis of the business activity is carried out. The application considers the role and importance of assets in the task execution process, can comprehensively cover the entire complete failure path under the integration of information security and functional safety, can more comprehensively identify the safety risks in each task link, and further improves the accuracy of risk analysis.

The invention relates to the technical field of process management, in particular to a technical supervision dynamic management and control system applied to a thermal power-new energy scene, and the system comprises a data receiving module which collects the equipment operation data of thermal power, wind power and photovoltaic business units in real time; performing hierarchical management on high-frequency process data and low-frequency historical data by using a multi-level data lake architecture; the data processing module constructs a thermal power, wind power and photovoltaic business process model to perform sequential analysis on the operation data of each business unit; the scheduling management and control module is fused with the trend error dynamic amplification factor to predict deviation of the operation states of the thermal power, wind power and photovoltaic service units; and the feedback optimization module carries out dynamic management and control on the business process based on fuzzy logic control and multi-condition comprehensive evaluation. According to the invention, intelligent management of the whole process of technical supervision of thermal power and new energy equipment is realized through flow behavior portraits based on prediction deviation and scheduling optimization.

The invention discloses a process execution method and system, relates to the technical field of business process management, and mainly aims to improve the flexibility of process execution. According to the main technical scheme, a process execution engine executes a preset business process according to a business process model. And when executing to the target decision node, generating a corresponding decision request event and issuing the decision request event to the event bus. And the rule evaluation engine monitors the event through a preset subscription mechanism, and determines a business rule which corresponds to the target decision node and is defined by a domain-specific language model in a preset rule base. Then, the engine obtains target real-time service data corresponding to the event from an external system, generates a decision suggestion of a target decision node according to the data and rules, and publishes the suggestion to an event bus, and the decision suggestion comprises an approval result, a next to-be-executed node or a node adjustment condition; and finally, the process execution engine executes an operation corresponding to the decision suggestion according to the execution interface.

The invention discloses a total element-based dynamic business process intelligent arrangement and execution method and system, a medium and a product, and relates to the field of business process management, and the method comprises the steps: carrying out the version selection and instantiation of each tool element in a tool element set; according to the input and output contract of each tool element in the instantiated tool set, constructing a preliminary directed acyclic graph; performing iterative optimization by adopting a structure quality function according to the preliminary directed acyclic graph structure; performing dynamic configuration and training on the model component of each tool element in the business flow chart; performing global business logic verification on the dynamic business flow chart; dynamically operating the executable business process model by utilizing an execution engine; constructing a runtime data set according to the runtime data in the execution process; and generating an incremental training set for feedback based on the runtime data set. According to the application, the business process can be automatically constructed, dynamically executed and continuously optimized.

The invention discloses a to-do task generation method based on an Activity workflow. The task generation method comprises the following steps: constructing and managing a business process model based on the Activity workflow; defining a generation rule of a to-do task according to the business demand; the method is implemented on the basis of an activity workflow engine and is responsible for loading and executing a business process model. Judging whether to-do tasks are generated or not according to the process operation information and task generation rules, and if conditions are met, generating the to-do tasks; pushing the generated task to be handled to a specified executor; and after the executor processes the to-be-handled task, obtaining a processing result, and continuing to promote the process according to the processing result. The commission task is automatically, accurately and efficiently generated, and the automation degree and the management efficiency of the business process are improved.

The application discloses a production business process node vector representation method fusing structure and behavior characteristics. The method comprises the following steps: firstly, structure characteristics of a production business process are extracted by using a random walk algorithm and a Skip-gram model; then, behavior characteristics of the production business process are extracted by using the Skip-gram model; finally, a deep Boltzmann machine is introduced to fuse the structure characteristics and the behavior characteristics of the production business process, thereby automatically performing vector representation on nodes of the production business process, extracting and fusing various characteristics to improve the accuracy of the node vector representation, and further improving the accuracy of subsequent production business process recommendation, optimization and the like. The application has the advantages that the graph structure characteristics of the production business process itself and the behavior characteristics based on historical execution logs are fused, deep learning technology is used to strengthen the production business process model, the node vector representation which simply depends on the historical execution logs is supplemented and improved, and the accuracy of the node vector representation is improved.

The present disclosure generally relates to the field of data structures and in particular, a loop-aware footprint matrix data structure adapted for data process traversal. The proposed approach is directed to a computer-based analytic system and corresponding method that uses a specific data structure and processing thereof, in some embodiments, adapted to computationally estimate predictions of next events by first generating a data structure based on business process models obtained using process mining techniques, and then using the improved data structure for generating predictions, which can then be encapsulated in the form of computer instructions or machine instruction sets, having a specific sequence for execution.

Systems and methods for configuration driven integration of services in business process models agnostic of a workflow system are disclosed. An exemplary method includes receiving, at a service executor, a generic service call from a business process management notation (BPMN), wherein the generic service call includes a service name parameter, wherein the service name parameter is associated with a service task of the BPMN, and wherein the service name parameter is associated with a service. The service executor can construct a call to the service including required data from a transient data store. The service executor can then receive return data from the service, store the data in the transient data store and respond to the BPMN that the service task has been completed.

The invention relates to a service simulation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an event log of a business process; performing event dependency relationship analysis on the business process based on the event log to obtain a direct successor graph corresponding to the business process; nodes in the direct successor graph are used for representing events; a directed edge connecting the two events in the direct successor graph is used for representing a dependency relationship between the two events; aiming at a plurality of event paths between a starting node and an ending node in the direct successor graph, determining the path capacity of each event path based on the occurrence frequency of the dependency relationship represented by each directed edge; constructing a business process model corresponding to the business process according to the event path of which the path capacity is greater than or equal to the set capacity; and performing servitization packaging on the business process model to generate a test code for performing service simulation on the business process. By adopting the method, the service simulation accuracy can be improved.

The application discloses a quick modeling generation method for enterprise business processes, relates to the technical field of business process modeling, and comprises the following steps: after receiving a business process modeling request, performing structure similarity analysis, comparing a current process structure input with path vectors of a plurality of process templates, judging structure coincidence degree and conditional node semantic consistency, and identifying whether the case belongs to a plurality of template combined process generation; in the case of identifying the plurality of template combined process generation, extracting each path trigger frequency original value corresponding to a conditional judgment node, a frequency sampling time range, a sample quantity, a collection strategy label and a path trigger distribution density, constructing a normalized offset vector, and outputting a normalized difference result. The application solves the problem of inconsistent path frequency statistics caliber in the multi-template process combined modeling, and realizes the normalized evaluation and dynamic optimization setting of a default path.

The application discloses an automatic process modeling method for complex scene description, first, using a method based on shared representation learning and structured prediction, synchronously realizing two important basic works of event discovery and event relationship extraction. Secondly, through the process model construction method, events and event relationships are integrated to obtain the process model extracted from the complex scene description. Finally, in order to detect the effectiveness of the process model extraction, the application obtains the graph similarity score between the extracted process model and the real process model through a process model similarity calculation method based on a graph neural network. The application can automatically extract a business process model from a description text of a complex scene through technologies such as event discovery, event relationship extraction and process model construction. The application uses a novel process model consistency detection method combined with deep learning, which can quickly and objectively evaluate the accuracy of the result after automatic process modeling.

The invention discloses a process data simulation method and device, electronic equipment and a readable storage medium, and relates to the technical field of data simulation, and the specific implementation scheme is as follows: obtaining initial log data; determining a business process model based on the initial log data; based on the initial log data and the business process model, simulation parameters are obtained; and on the basis of the simulation parameters and the simulation demand data, the business process simulator is configured and operated to obtain the target simulation data output by the business process simulator, so that the process data simulation efficiency is improved.

The application discloses a cross-organization process model evolution method on a blockchain, a medium and an electronic device. The method models frequent process dynamic changes based on a time assignment diagram, and adopts a model version control strategy based on a voting mechanism to realize process model evolution. The method introduces instance execution compliance and migration compliance, and realizes state compliance checking of instances in the evolution process. Through the method, the problems of difficult actual cross-organization business process model evolution and inefficient instance migration can be effectively solved.