185 results about "Workflow engine" patented technology

The invention discloses a large-model-driven intelligent calculation method and system for a water conservancy mechanism model. According to the method, natural language input, structured conversion and intelligent optimization calculation of a scheduling target are realized by integrating a field-enhanced large language model and a water conservancy professional mechanism model. The method comprises the steps of receiving a calculation target expressed by a user in a natural language, and analyzing and converting the calculation target into a constraint condition and a target function which can be recognized by a water conservancy mechanism model; a hydrological model, a hydraulic model, a hydrodynamic model and other models are called based on a workflow engine, and reverse calculation is carried out by adopting a hybrid optimization strategy of'coarse adjustment-fine adjustment-verification '; synchronously and visually displaying the parameter change and the result convergence state in the calculation process; and outputting a calculation result including parameter adjustment logic, standard conformity analysis and multi-scheme comparison. The system comprises a natural language interaction module, a target conversion module, an intelligent calculation engine module, a visualization module and a result generation module, and supports multiple application scenes such as multi-target scheduling, emergency decision making and ecological guarantee. Compared with a traditional scheme, the method has the advantages that the model use threshold is lowered, the dispatching efficiency and calculation transparency are improved, and the method is suitable for complex hydraulic engineering calculation tasks such as reservoir dispatching, cross-basin water transfer and flood control emergency.

The invention discloses an intelligent operation and maintenance method for modular data acquisition and analysis sewage treatment equipment, which comprises the following steps: designing a modular data acquisition unit, configuring an acquisition module with a standardized interface, and realizing quick access of multi-source equipment; protocol conversion, data compression and timestamp completion are completed by using an edge computing gateway, and stable data reporting under a complex network is realized by combining an MQTT protocol; a time sequence database is adopted to store and fuse OA / ERP system data, and an information island is broken; remote diagnosis, intelligent early warning and visual decision making are realized by means of a remote fault analysis interface, a user-defined rule engine and a configurable billboard; and operation and maintenance closed-loop management is achieved in cooperation with a workflow engine. The method effectively solves the problems of low data acquisition integration level, unstable communication, weak analysis capability and the like in traditional operation and maintenance, has the characteristics of modularization, intelligence, high efficiency and the like, remarkably improves the operation and maintenance management level of the sewage treatment equipment, reduces the operation and maintenance cost, and has a wide application prospect.

The invention relates to a large model business logic processing method and system based on workflow engine and domain knowledge fusion, and is suitable for automatic processing of complex multi-node and multi-branch business processes. According to the method, natural language input of a user is analyzed through a large language model, a service intention is recognized, and the service intention is converted into an executable task process through a workflow engine. And the workflow engine dynamically adjusts an execution path according to rules and data in the domain knowledge graph to realize efficient parallel processing of tasks. The system integrates a workflow engine, a domain knowledge graph and a large language model, supports real-time data processing, rule matching, conflict resolution and decision optimization, is suitable for the fields of water conservancy, medical treatment, finance and the like, automatically generates and executes a complex business process, and optimizes a decision process. The system improves the accuracy and execution efficiency of business decision through deep fusion of domain knowledge.

The invention relates to the technical field of equipment management, in particular to an equipment full-life-cycle digital twinborn decision-making system enabling a large model. Comprising a digital twin modeling unit; a large model enabling analysis unit, wherein the large model enabling analysis unit adopts a hydroelectric equipment multi-modal causal constraint analysis model; a whole-process closed-loop management and control unit; and an intelligent decision output unit. According to the method, the multi-modal causal constraint analysis model adaptive to the working condition of the hydroelectric equipment is constructed, and a causal chain verification backtracking mechanism is introduced, so that the problem that the reasoning result lacks logic verification is effectively solved, the logic consistency of a fault reasoning conclusion is guaranteed, and the reliability of decision output is improved; through a scene adaptation mode of'pre-training + fine tuning 'of a large model, multi-modal feature fusion processing and deep linkage of a workflow engine and a digital twinborn body, full-life-cycle management requirements of equipment are fully covered, and the refinement and intelligence level of hydroelectric equipment management is further improved.

The invention relates to a field information analysis method and system based on RAG and a knowledge graph, and belongs to the technical field of artificial intelligence, and the system comprises a multi-source heterogeneous data collection module which is used for collecting field-related original data; the intelligent document processing engine is used for carrying out cleaning and structured processing on the data and extracting entities, relationships and events; the multi-source knowledge graph construction and management module is used for constructing and fusing multi-sub-field knowledge graphs to form a unified knowledge graph; the RAG retrieval enhancement generation dynamic fusion sequencing module is used for receiving user query, performing multi-channel information retrieval by querying a text vector index and a knowledge graph, performing fusion resequencing on a result, and generating an analysis result by utilizing a large language model; and the agent workflow engine is used for decomposing query into subtasks and scheduling professional agents to cooperatively complete analysis and report generation. Deep semantic understanding, intelligent retrieval and automatic analysis of domain information are realized, and the accuracy and efficiency of information processing are improved.

The invention relates to the technical field of artificial intelligence and decision support, and discloses a large model agent-based strategic decision generation method, which comprises the following steps of: performing semantic analysis and multi-target game balance on a strategic instruction by a main control agent, and decomposing to generate subtasks; a corresponding domain agent calls an RAG enhancement module to retrieve related multi-modal data, and a preliminary strategy of embedded compliance verification is generated based on the data; and finally, dynamically arranging and coordinating the preliminary strategy by a hierarchical workflow engine, and generating a comprehensive decision report after receiving strategy correction information of a commander. According to the invention, through multi-agent cooperation and multi-target game balance, the decision-making globality and strategic depth are realized; by fusing dynamic multi-modal data, the adaptive capacity of the decision to the external environment is improved; through workflow arrangement and man-machine cooperation, logic self-consistency, execution feasibility and safety of a final scheme are ensured.

The invention provides a hypercomputing cluster-oriented workflow engine system and task scheduling method, and the system comprises a drag-and-drop arrangement design module which is used for providing a visual workflow arrangement environment so as to respond to a drag-and-drop arrangement operation of a user to obtain a target workflow; the target workflow comprises a plurality of tasks and a dependency relationship among the plurality of tasks; the virtualization task packaging and adaptation module is used for packaging a plurality of tasks in the target workflow by utilizing a unified packaging mechanism to obtain a plurality of target containers; and the workflow automatic execution module is used for managing and distributing hardware resources in the super computing cluster so as to schedule and execute tasks in the target containers according to the dependency relationship. Through the system provided by the invention, the complex workflow can be efficiently executed and managed in a super computing cluster environment.

The invention discloses a dynamic coupling modeling method and system for an electric power information physical system, and belongs to the technical field of electric power dispatching automation, and the method comprises the steps: analyzing an AGC control process business data flow, and constructing a workflow engine; performing node classification, generating an information node model and an information branch model of the information system, and constructing a rule engine; constructing an information system network matrix model based on the rule engine, and establishing a preset service strategy based on the information system network matrix model; constructing an information physical coupling model of the AGC control process; and according to the AGC actual service, loading a preset service strategy established by the information system network matrix model based on the synergistic effect of the workflow engine and the rule engine, and updating the information physical coupling model. According to the method, a basic model is provided for cross-level closed-loop simulation verification in the AGC process, the problems of unclear information physical dynamic coupling mechanism, insufficient service logic adaptive mapping and model iteration self-updating are solved, and a guarantee is provided for safe and stable operation of a large power grid.

The invention discloses an electronic medical record intelligent coding method, device and system, and a storage medium. The method comprises the following steps: respectively carrying out entity extraction, feature coding and homomorphic encryption transmission on an electronic medical record text, a medical image and structured inspection data; according to the preprocessed data, performing multi-modal feature alignment, ICD semantic mapping and real-time medical insurance rule injection through a dynamic knowledge fusion coding engine; generating a three-dimensional visual evidence chain of the text evidence, the image evidence and the policy evidence through the interpretable traceability matrix; through a multi-role cooperative workflow engine, generating a code according to a confidence threshold routing AI, and auditing the code to a clinician or a professional coder; rare disease data are synthesized through an adversarial training enhancement module, and policy mutation is simulated for model adaptability training. By adopting the technical scheme of the invention, the problems of multi-modal data splitting, policy lag and non-traceability in the prior art are solved.

The invention discloses a cross-system data collaborative driving workflow full-link approval method and system, belongs to the technical field of workflow management, and aims to solve the technical problem of how to realize cross-system data collaborative driving and cover a workflow full-link approval method and process. Comprising the steps that a system architecture composed of a unified workflow engine, data collaboration middleware and a plurality of service systems is built; drawing a cross-system workflow full-link approval flow chart in the unified workflow engine; by means of data collaboration middleware, a collaboration mapping relation of all service systems is established, and data format conversion, extraction and integration operations are automatically executed in process execution; and the unified workflow engine generates a process instance, notifies a service system of a subsequent approval node through the data collaboration middleware, sends an approval task to the corresponding approval node, transmits related data through the data collaboration middleware, notifies related personnel, and records various information in a full-link approval process execution process in real time.

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 the technical field of informatization, in particular to a workflow engine implementation method based on event traceability and decentralized monitoring, which is based on the design of recording node operation and deducing a process state on the basis of an immutable event sequence, thoroughly relieves the constraint of traditional state table storage on dynamic adjustment, and improves the working efficiency. Operation such as node insertion, skipping or rollback can take effect in real time through runtime metadata reconstruction, meanwhile, a completely stored operation event chain naturally supports full-process audit tracing, and a log system does not need to be additionally developed; a power proportion algorithm decomposes distributed node decisions into three layers of logics of role allocation, predefined result verification and secondary monitoring triggering, cross-service consistency is guaranteed through a post weight adjustment and historical behavior voting dual mechanism, and an online voting mechanism dynamically calculates and processes human weights by using event logs, so that the decision accuracy is improved. Therefore, the technical bottlenecks of rigidity, redundancy and weak consistency of the traditional scheme are overcome.

The invention relates to the technical field of process orchestration, and discloses an automatic orchestration system and implementation method based on event driving and context management, and the system comprises a model orchestration module which receives an external request through an OpenAPI, carries out the model packaging based on namespace attributes, and abstracts the workflow execution capability into a configurable model entity; the workflow engine module is used for providing a dynamic arrangement and execution mechanism based on a directed graph structure and carrying out unified context management; the parameter configuration module is used for constructing a global data constraint and management mechanism of a parameter-result double-layer model, and establishing a data mapping relation between an execution layer and a display layer of the process; and the data source management module uniformly manages and configures the external service capability units which can be called by the nodes in the workflow. According to the method, asynchronous, self-driven and distributed parallel execution of the workflow nodes can be realized, the operation efficiency in a high-concurrency scene is improved, and organic unification of performance, stability and expansibility is realized.

The invention relates to the technical field of engineering project management, and discloses an engineering project supply chain collaborative management system, which comprises a unified data interface module used for acquiring multi-source business data from heterogeneous information systems of an engineering project general package party, a sub-package party, a material supplier and a logistics service provider, processing the multi-source business data into a standardized business data model; and a business process management module. By adopting the technical scheme that a unified data interface module and a workflow engine cooperatively work, the technical effects of connecting information systems of all participants of a supply chain and realizing automatic synchronization of purchasing, inventory and construction progress data and linkage of a business process are achieved; compared with the technical scheme that each party adopts an incompatible information system and depends on manual information transmission in the prior art, the defect that the accuracy of a project plan is damaged due to difficulty in collaborative operation caused by data obstruction is overcome.

The invention provides an online interactive programming education system based on a micro-service architecture, and the system comprises an infrastructure layer which serves as a bottom layer computing power and provides an elastic computing power through a cross-cloud deployment technology and a dynamic resource scheduling technology; the platform core layer constructs a stateless micro-service cluster through a service registration discovery module, a load balancing module and a fusing mechanism module depending on elastic resources of the infrastructure layer, and the infrastructure layer provides physical resource guarantee for operation of the micro-service cluster of the platform core layer; the platform support layer is used for integrating an authority management component, a workflow engine component and a general service component based on a stateless micro-service cluster constructed on the platform core layer, and providing resource isolation and high-concurrency task scheduling support in a multi-tenant environment for the programming education system; the platform core layer is combined with distributed transaction management to provide stable service scheduling and communication capability for an authority management component, a workflow engine component and a general service component of the platform support layer; and the platform application layer combines service scheduling and communication capabilities, realizes teaching functions such as multi-language development, code debugging visualization, AI personalized suggestion and collaborative learning, and directly serves programming learning of students and teaching management requirements of teachers.

The invention relates to a gouty arthritis patient pain management method and system based on an MDT management mode, and the method comprises the steps: automatically collecting the multivariate clinical data of a patient through integrating an existing information system of a hospital, carrying out the cleaning, standardization and structural processing through a special data preprocessing module, and carrying out the cleaning, standardization and structural processing. A machine learning prediction model trained by historical data is utilized to automatically generate a personalized MDT nursing plan, tasks are intelligently distributed to corresponding team members by means of a workflow engine, the execution condition is continuously monitored in the intervention process, and the nursing scheme is dynamically adjusted based on clinical data and prediction results which are periodically updated. And a complete'monitoring-prediction-intervention-reevaluation 'closed-loop management process is formed. The problems that a traditional MDT mode depends on manpower, efficiency is low, and decision-making lacks data support are effectively solved, and the accuracy, the collaboration and the continuity of pain management and wound surface nursing of the gouty calculus combined infection patient are improved.

The invention provides a truss structure autonomous design system and method based on multiple agents. A layered multi-agent architecture is adopted, a general control agent is taken as a core, and a high-level design intention is analyzed and a plurality of downstream special agents are arranged for cooperative work; the whole design process realizes automatic closed loop through a graph-based workflow engine; the core innovation of the method is a hybrid intelligent optimization algorithm of LLM heuristic exploration and genetic algorithm accurate fine tuning, and the algorithm is driven by an original and quantifiable design quality scoring system to efficiently carry out analysis-diagnosis-optimization iteration so as to cooperatively improve the safety and economy of the design. The design time can be shortened from several hours to several minutes, about 7.0% of material consumption is saved on average, it is ensured that the scheme completely conforms to industry specifications, the design efficiency, economy and reliability are greatly improved, and meanwhile the use threshold of professional design software is remarkably reduced through natural language interaction.

The invention discloses an industry operation permission intelligent approval system based on Java and an implementation method, and belongs to the technical field of computer application. The system adopts a four-layer architecture including a presentation layer, a business logic layer, a data access layer and a data storage layer. The core of the system is that the business logic layer integrates an intelligent auditing engine, a rule engine and a workflow engine; the intelligent auditing engine automatically analyzes and extracts key information in the application material through NLP and OCR technologies; a rule system based on industry classification is built in the rule engine, three-dimensional automatic verification of subject qualification, material integrity and condition conformity is executed, and regulatory terms can be mapped into executable logic; and the workflow engine automatically triggers and manages the approval process according to the verification result. According to the invention, full-process automation and intellectualization of industry operation permission approval are realized, the approval efficiency, accuracy and dynamic adaptation capability to policies and regulations are greatly improved, and the problems of low efficiency, different standards, lagging and the like existing in a traditional manual approval mode are effectively solved.

The embodiment of the invention provides a forecasting and early warning method and device based on a workflow engine technology. The method is applied to the technical field of data processing and comprises the steps that codes are uploaded and verified through an algorithm registration interface, authorization is managed based on permission identification, and an algorithm library is constructed; monitoring a data source according to the algorithm feature index, and generating a DI trigger signal and task description when new data is acquired; analyzing data by using a language model and optimizing resource allocation; arranging task nodes by using a workflow engine; executing pre-verification to generate a task sequence; and analyzing the abnormity through the EI message and feeding back an optimization scheduling scheme. According to the invention, the task execution strategy is automatically adjusted according to the change of the real-time meteorological data, and the timeliness and accuracy of the forecasting and early warning information are ensured.

The invention discloses a code reconstruction method and system based on multi-agent collaboration. The method comprises the steps that a collaborative workflow engine obtains a source code to be reconstructed; the scheduling structure analysis agent analyzes the source code to obtain code structure information of the source code; scheduling an odor analysis agent to analyze the source code based on the code structure information and a preset index to obtain odor code information in the source code; the scheduling reconstruction strategy intelligent agent analyzes the code structure information and the peculiar smell code information to obtain a code reconstruction strategy; scheduling a reconstruction execution agent to execute the code reconstruction strategy to obtain a reconstruction code; and outputting the reconstructed code. The technical problems that a traditional code reconstruction tool has limitation of single-point decision making, rule stiffness and the like, and the quality of reconstructed codes is poor are solved.

The invention belongs to the technical field of artificial intelligence, provides a workflow generation method and device fusing a large language model and a knowledge base, and aims to solve the problem of low accuracy of automatic workflow generation based on the large language model in the traditional technology. Identifying multi-dimensional context information contained in the multi-dimensional context information; retrieving an enterprise private knowledge base according to the multi-dimensional context information to obtain domain knowledge fragments related to workflow generation; the workflow requirement description, the multi-dimensional context information and the domain knowledge fragments are used as cue words to guide and constrain the large language model, and a workflow definition model is generated; and finally, a workflow engine is adopted to create the target workflow based on the workflow definition model, so that the processing accuracy of a natural language automatically generated by the workflow can be improved, the workflow is highly matched with actual business requirements of an enterprise, and the method can be applied to the technical field of business process intelligent management.

The invention discloses a multi-role collaborative transportation safety management and responsibility tracing method and system. The method comprises the following steps: S1, reporting an event, collecting travel data, identifying a security event through AI, and generating a unique event number for associated storage; s2, role and flow distribution: grading based on event information, determining participation roles by means of a built-in rule engine, and generating a processing flow and a task list containing logic association through a workflow engine; s3, multi-role cooperative processing and recording are carried out, the roles are operated according to a list, and the system automatically records the operation and forms a corresponding event processing chain; and S4, automatic responsibility tracing: based on the processing chain, generating a responsibility chain and a responsibility affiliation result through a hybrid mechanism. The system comprises a database, an event report and other functional modules for supporting the method. According to the invention, full-process closed-loop management from event grading and role allocation to cooperative processing and automatic tracing is realized, and the problems of low efficiency and difficult responsibility determination of multi-role cooperation are solved.

The invention discloses a machine learning platform and method based on workflow, electronic equipment and a storage medium, and the platform comprises a management scheduling system, a workflow engine system and an operator runtime system. A user is allowed to construct a visual business process in a dragging and connecting mode, and each component corresponds to a specific AI algorithm processing unit written by Python; the platform supports the realization of multi-node business logic by using an operator concept by referring to a BPMN specification, automatically analyzes a flow chart designed by a user into a directed acyclic graph, converts the directed acyclic graph into an API calling sequence for a Python runtime system, disassembles a complex business system into a multi-branch and multi-step configurable process, and executes local logic by each node to realize multi-node business logic. The whole process is visually arranged, the development threshold is remarkably reduced, and the execution efficiency and the system flexibility are improved.

A system for bidirectional two-factor remote user authentication includes a workflow engine comprising one or more processors and at least one memory element for storing instructions. The system further includes a client device with one or more processors, a display, and a user login interface. The workflow engine generates and encrypts one or more login identifiers, which is visually encoded as an authentication image and displayed on the terminal's display. An electronic device, also connected to the workflow engine, includes a password, a display with a graphical user interface, one or more processors, and at least one memory element. The device's authentication identifier reader decrypts the one or more login identifiers from the authentication image and compares it with the password to determine a match. Upon a match, the device transmits an authorization for the login request to the workflow engine.

The invention discloses an owner service AI workflow construction method and system based on a Dify platform, belongs to the field of automobile service, and aims to solve the problems of low efficiency, inaccurate reply, dependence on foreign technologies and inconvenience in access in traditional owner service. The method comprises the following steps: constructing a structured knowledge graph fusing data such as a vehicle specification and a maintenance manual; a special AI workflow integrating intention classification, key information extraction, knowledge graph query and logic decision nodes is configured on the Dify platform; deploying the workflow on a domestic cloud platform and packaging the workflow into an API; the development responsive web page front end provides lightweight access. The system correspondingly comprises a knowledge base management module, a workflow engine module, a model service module and the like. According to the method, full-link safety and controllability are achieved through the domestic platform and the autonomous model, the service accuracy and efficiency are improved through the knowledge graph and the fine tuning model, and convenient instant intelligent services are provided through the webpage side.

The invention relates to the cross technical field of artificial intelligence operation and maintenance and cloud native computing, in particular to an AI model full life cycle management method and system based on cloud native, and the method comprises the steps: constructing a containerized interactive development environment, and generating an invariable OCI mirror image containing a model code and a dependency library; a versioning model registration center of a three-layer storage architecture is adopted, and strong consistency management of model files and metadata is achieved; an automatic CI / CD assembly line is driven through a declarative workflow engine, and event triggering and timing scheduling are supported; the reasoning service deployment module based on the service grid realizes gray release and elastic capacity expansion and contraction; a multi-dimensional monitoring index system is established, and model performance attenuation and data drift are detected in real time; and designing an adaptive resource scheduling algorithm, and dynamically optimizing heterogeneous computing resource allocation. The resources can be dynamically adjusted according to the actual load, and high performance and high availability of the model service are ensured.

The invention discloses a task decomposition and arrangement and exception retry method and system for a workflow engine, and relates to the technical field of task decomposition and arrangement management. According to the method, a service request received by a workflow engine is acquired, structured analysis is performed on the service request, the service request is decomposed into one or more groups of associated interaction subtasks, and an execution-oriented task arrangement relationship is dynamically constructed according to a data dependency relationship among the interaction subtasks. And generating a task graph containing nodes, edges and trigger conditions according to the task arrangement relationship, thereby generating a workflow which can be scheduled and executed in the workflow engine, monitoring the execution state of each interaction subtask in real time in the workflow execution process, and when the execution state is monitored to be abnormal, executing the task according to the task graph. And retry arrangement and rescheduling execution are carried out on the corresponding interactive subtasks, and validity verification is carried out in the execution process, so that the matching degree between the task decomposition arrangement process and the abnormal subtask self-adaptive retry strategy is improved.

The invention discloses a data verification method and system, a product, equipment and a storage medium. The method comprises the steps of obtaining a data verification rule configured for a target business process; in a scheduling workflow engine, based on the node association relationship of the target business process, embedding a check node corresponding to the data check rule, and in the execution process of the target business process, calling the corresponding data check rule through the check node to check the process data; if the verification result is not abnormal, continuing to execute the original business process; and if the verification result is abnormal, storing abnormal data into a preset abnormal information table, and giving an alarm according to a preset verification result notification mode. Based on the scheduling workflow engine, the data verification work of each business process is visually configured in the scheduling workflow engine, meanwhile, decoupling with the original business process logic can be realized, and the requirement of a newly added business logic scene can be quickly adapted.

The invention discloses an architectural drawing management method and system based on multi-modal AI recognition, and relates to the technical field of data management, and the method comprises the steps: extracting drawing frame information of a drawing file through a preset image recognition large model when the drawing file is received; based on a preset field mapping relation, converting the drawing frame information into database fields and storing the database fields into a preset drawing database; when a query instruction is received, the query instruction is converted into a library query statement, and retrieval is performed in a preset drawing database based on the library query statement; and determining a target drawing file according to the retrieval result, and sending the target drawing file to a permission user corresponding to the query instruction. According to the method, three core technologies of dynamic drawing frame positioning, natural language processing and an intelligent workflow engine are fused, so that full-process digital reconstruction from drawing analysis and structured storage to intelligent retrieval and multi-user collaboration is realized, and the building drawing management efficiency is improved.

The invention relates to the technical field of data processing. The natural resource right confirmation service intelligent collaboration method, device and equipment and the medium are provided, and the method comprises the following steps: analyzing a cross-department right confirmation service through a process modeling technology, and generating a visual flow chart comprising a responsibility boundary and a collaboration node; performing packaging processing on the right confirmation link through a micro-service packaging technology, generating an independent micro-service unit, and constructing a template library associated with resource types and policy labels; sorting the independent micro-service units to generate an optimized execution path; performing visual monitoring processing on the execution state through a workflow engine to generate a blocking point report; triggering resource allocation processing based on the blocking point report, and generating a dynamic resource allocation scheme; and updating the template library and the rule library to generate the adaptive collaborative system, so as to achieve the technical effects of improving the dynamic adaptive capacity of the process, reducing the rule conflict rate, optimizing the resource scheduling efficiency and enhancing the collaborative consistency of the template library and the rule library.