33 results about "Business process modeling" patented technology

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 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 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 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 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 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 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 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.

The invention relates to a semantic business process anomaly detection method based on a large language model, which comprises the following steps of: performing semantic understanding on event logs in a business process by using a fine-tuned large language model, and detecting abnormal behaviors from a semantic level: firstly, generating a normal track based on a large number of real business process models by using a DABL method; generating an abnormal track containing sequence abnormity and mutual exclusion abnormity through disturbance; then, the tracks and the abnormal reasons are converted into question and answer forms, and efficient fine adjustment is conducted on a large language model of the open source code through the QLoRA technology; the fine-tuned model can be directly used for zero sample semantic anomaly detection, and extra training or clean logs are not needed. The DABL can automatically explain the abnormal reason, and provides interpretable support for process optimization and service monitoring.

The invention discloses a service process-oriented adaptive data security and authority management method, and particularly relates to the technical field of data security and authority management.The method comprises the following steps of: firstly, modeling a target service process, acquiring nodes, a main body, an environment and data attributes, forming an access event, and constructing a dynamic trust chain network with a trust state; secondly, a collaborative behavior path is generated around the sensitive data in a sliding time window, a risk score is calculated in combination with path frequency, a topological structure and cross-organization and cross-role characteristics, and a high-risk collaborative behavior path is recognized. And then multi-granularity candidate permission intervention measures are generated for a high-risk path, risk benefits and service influences are comprehensively evaluated, and subject-level, session-level, resource-level and path-level permission adjustment strategies are automatically generated, issued and executed. And finally, the trust state and the feature weight are dynamically updated based on a strategy execution result and auditing feedback, and continuous and accurate interception of abnormal cooperative behaviors and minimization of influence on services are realized.

The invention provides a low-yield monitoring management system, which comprises a business process modeling unit for constructing a digital process model comprising production link input parameters, output parameters and operation logic; the anomaly detection unit is used for monitoring production links in real time based on the process model, and identifying abnormal nodes deviating from a preset standard through a dynamic threshold algorithm; the root cause analysis unit is used for associating historical data with real-time data and carrying out weight sorting on influence factors of abnormal nodes by adopting a decision tree algorithm; and the automatic execution unit is used for realizing automatic execution of operation steps corresponding to the abnormal nodes through an RPA technology and sending an optimization instruction to an operation terminal. According to the method, the input, output and operation steps of each link can be found conveniently, and the problems of complexity, repetition and unreasonability in the process are optimized and improved; personnel skill training is enhanced, a reasonable incentive mechanism is established, and low yield caused by manual misoperation is reduced; and aiming at different products and technical characteristics of the DDR4 and the DDR5, the method conforms to the low-yield service of the current product.

The invention discloses a full life cycle process management system and method based on Flowable 7, the system comprises five modules of process modeling, process operation, process operation and maintenance, process analysis and process portal, the process modeling module provides a visual design based on a BPMN 2.0 standard and is used for creating a business process model; the process operation module depends on a Flowable7 process engine and drives process execution according to a business process model; the process operation and maintenance module monitors a process instance state in real time and supports manual intervention and abnormal recording; the process analysis module collects process operation data, and supports process optimization through multi-dimensional data statistical analysis; the process portal module serves as an entrance of interaction between a user and the system, intensively displays task information and provides process visual tracking. The system provided by the invention realizes comprehensive management of the whole life cycle of the business process from design and execution to monitoring and optimization.

The application is a hospital operation process optimization and abnormality detection system and method, belonging to the technical field of hospital informationization and operation management. The technical problem to be solved is that the existing hospital operation management has the problems of serious data island, static process modeling, lagging abnormality discovery, lack of data support for optimization and insufficient real-time monitoring capability, resulting in invisible process execution, untimely problem handling and difficult quantification of optimization effect. The technical solution points are: non-intrusive collection of full operation logs of each business system of the hospital to build a unified process event model; multi-level primary key association is adopted to form a complete process event sequence, and an improved Alpha++ algorithm is used to automatically discover the actual business process model; multi-dimensional identification of process bottlenecks is adopted, and an algorithm combining cosine similarity and edit distance is used to detect abnormalities in real time and give graded early warnings; case-based reasoning and discrete event simulation are used to generate implementable optimization suggestions, forming a closed-loop operation management system.

The application discloses a business process model query method based on a feature model, and belongs to the technical field of business process model search, and the method comprises the following steps: classifying all business process models in a business process model library to obtain a feature model; optimizing the feature model to obtain an optimized feature model; obtaining an input model, and performing query according to the optimized feature model to obtain a query result. The method can improve the accuracy and efficiency of business process model query.

The invention discloses a collaborative monitoring system and method for a digital transformation process, and the method comprises the steps: obtaining all data, needing digital transformation, of an enterprise, and dividing the data into production data, operation data and support data; constructing a'relation model 'reflecting real business logic; generating a quantitative'digital verification score 'for evaluating the matching degree of the model and actual operation; when the digital verification score exceeds a preset threshold value, judging that the business process model passes verification; at the moment, the system enters a collaborative monitoring stage, and starts to calculate the collaborative degree between the business activities so as to quantify the collaborative closeness degree between the activities; the system carries out continuous anomaly analysis on real-time service data flow, and carries out accurate positioning and diffusion early warning on potential risks. The method has the advantages that the crossing from passive alarm to active risk management is realized, and the control force and the anti-risk capability of an enterprise on a digital transformation process are greatly enhanced.

The application discloses a kind of dynamic knowledge calculation and reasoning system and method for digital twin, it is related to digital twin technical field, including: knowledge point is defined as six tuple, knowledge logic diagram is defined as directed graph;Establish multi-modal knowledge label system, carry out label similarity calculation;Process modeling is carried out using modeling language, and business logic is visualized as knowledge calculation flow chart;Based on knowledge label and knowledge calculation process, execute reasoning mode on knowledge logic diagram;Optimization algorithm is used to filter and recommend the reasoning result, and the online optimization knowledge calculation process is carried out using the feedback data of digital twin platform.The application is combined by knowledge logic diagram and business process modeling, solves the problem that traditional knowledge graph cannot effectively process process knowledge, utilizes multi-modal knowledge label system, realizes flexible, semantic rich knowledge retrieval and association, utilizes machine learning model to continuously optimize the effect of knowledge calculation, so that the system has growth.

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.

The application discloses a grey warehouse vehicle factory access intelligent verification method for license plate recognition, which comprises the following steps: reconstructing original images containing dust and mud stains through a generative network, extracting character features by using a double attention mechanism, and decoding license plate numbers as identity primary keys; a dynamic probability model is established based on the license plate, and a particle filtering algorithm is used to calculate the credibility state representing vehicle cheating suspicion in real time; at the same time, a business work order is parsed into a directed business process model, and the consistency of Internet of Things time sequence events triggered by the vehicle in the factory area is checked in real time; the probability value of the credibility state and the deterministic result of the consistency check are taken as double input sources, and are substituted into a preset response matrix for matching, so that differentiated traffic control of the vehicle is performed, such as non-susceptible release, early warning, secondary verification or fuse locking. The application effectively solves the recognition degradation problem in the grey warehouse under the bad environment, and builds a factory full-link intelligent verification system for preventing dynamic hidden cheating.

A framework and an agent loop for automatically generating tools and / or building artificial intelligence (AI) agents that use tools are disclosed. The agent loop can be expressed in business process modeling and notation (BPMN) or any other desired workflow language. These tools can be implemented as static, invocation-specific, or dynamic caller-side or server-side tools. The tools can be defined at all, only abstractly, or fully within the AI agent definition. The implementation of these tools can be injected as part of the agent process. The AI agents that implement these tools can also build other AI agents that can utilize caller-side and server-side tools.

The embodiment of the application provides a kind of business process chart construction method, device, equipment and storage medium, the business process chart construction method includes: obtaining the approval flow direction information corresponding to each organization level;According to the approval flow direction information, the business process modeling symbol is connected by directed edge, and the business process graph corresponding to the approval of same-level organization and cross-level organization is constructed;Business process modeling symbol includes multiple approval nodes.The embodiment of the application can solve the technical problem that the existing business process chart is difficult to meet the changing use demand of business system.

The application discloses a business process compliance checking method, a terminal and a platform based on natural language processing. The method can extract semantic information from regulatory documents and perform compliance checking on a business process model from multiple angles. This method can evaluate the existence of non-compliant patterns in the process model during the design phase, helping enterprises detect violations at an early stage and prevent potential violations during subsequent process execution, thereby saving the enterprise's energy, time and financial resources.