1310 results about "Digitality" patented technology

The invention relates to the technical field of digital factory production management, and discloses a digital factory-oriented multi-target production plan optimization method and system, and the method comprises the steps: decomposing an enterprise order into a plurality of subtasks through a production task decomposition module, and extracting related information; the resource dynamic evaluation module collects data in real time to generate a resource state matrix; the multi-objective optimization algorithm module constructs a model and adopts an improved non-dominated sorting genetic algorithm to solve; the dynamic priority distribution module adjusts the priorities of the sub-tasks according to the real-time data; and the conflict resolution unit is used for solving resource allocation conflicts. The method can accurately decompose tasks, evaluate resources in real time, collaboratively optimize multiple targets, flexibly deal with abnormities, efficiently resolve conflicts, comprehensively improve the production efficiency and benefits of the digital factory, and effectively solve the complex problems in the production plan making and optimizing process of the digital factory.

The invention relates to the technical field of power distribution, in particular to a construction method and system for a digital twinborn model of a power distribution network. Establishing a digital element of the multi-physical field coupling characteristic of the power distribution network equipment based on quantum state space mapping, and simulating a collaborative degradation process of insulation aging and electromagnetic interference of the equipment; constructing a dynamic energy flow entanglement relationship among the nodes of the power distribution network according to the equipment degradation characteristic tensor; based on the quantum entanglement relationship between the device degradation feature tensor and the topology connection hypergraph, establishing a time-space coupling eigenmode of the device multi-physical field state and network energy flow distribution, and generating a quantum topology covariant tensor of a twin model; and carrying out dynamic fusion on real-time characteristic data and the quantum topology covariant tensor to form the digital twin model of the power distribution network. According to the method, the digital twin model capable of accurately reflecting the power distribution network equipment aging and energy transmission spatio-temporal evolution law is constructed, and a high-fidelity simulation platform is provided for power distribution network state evaluation, fault early warning and optimization regulation and control.

The invention discloses an industrial MBSE model generation and evaluation method based on a large language model, and the method comprises the steps: collecting and sorting an aerodynamic model, assembly design rules and related basic design parameters, and carrying out the formatted expression of the rules applied in MBSE, so as to form a special enhanced knowledge base in the industrial field; the method comprises the following steps: converting a demand described by a natural language of a user into a standard MBSE model code based on a large language model through a cue word engineering technology, selecting an optimization algorithm and a simulation algorithm through a function call technology, performing real-time optimization on the model according to a design target, and applying the generated MBSE model to propulsion device design and verification test. And determining availability and model consistency. Reconstruction and acceleration of digital design are realized through automatic configuration based on requirements and components. The method has remarkable advantages in the aspects of reliability, effectiveness and adaptability.

The invention relates to a digital finance and taxation auditing method based on artificial intelligence, and the method comprises the following steps: S1, obtaining electric finance and taxation multi-source data, and carrying out the preprocessing of the data, and obtaining the preprocessed electric finance and taxation multi-source data; s2, constructing a finance and taxation knowledge graph according to the preprocessed power finance and taxation multi-source data; s3, constructing a multi-modal risk detection model, and obtaining a risk event list and a whole-course data traceability path according to the finance and taxation knowledge graph and the real-time electric finance and taxation multi-source data; s4, according to the risk event and traceability, based on a rule model, generating a structured decision instruction set including all key information and traceability links; and S5, converting the structured decision instruction set and the finance and tax knowledge graph into a standard relation graph for input, and dynamically displaying fund flow, risk events, abnormal aggregation and traceability paths among enterprises through D3. Js rendering. According to the invention, the efficiency and reliability of electric power digital finance and taxation auditing are significantly improved.

A system and method for providing a digital financial advisor using fine-tuned large language models is disclosed. The system includes a data advisor application, data fusion suite advisor engine, human advising engine, a knowledge base and large language model (LLM) fine-tuning engine to create specialized language models (SLMs) that mimic specific human financial advisors. Multiple digital avatars embodying the appearance and communication style of human advisors are generated. The system processes user and client profile data, along with advisor-specific information, to provide personalized financial advice. It handles client queries, escalating complex issues to human advisors when necessary. The digital advisor system communicates with profile datastores, user devices, and external data sources for comprehensive financial analysis. Continuous learning capabilities allow the system to improve its performance based on interactions and feedback, combining AI efficiency with personalized human-like advisory.

The invention relates to the technical field of digital factories, in particular to a full-process collaboration method and system for a digital factory. The method comprises the following steps: obtaining production decision data, and carrying out process parameter analysis according to the production decision data to obtain process parameter data; according to the process parameter data, building a factory resource agent through a preset digital factory model to obtain factory resource agent data; performing multi-agent negotiation according to the factory resource agent data to obtain digital workshop task allocation data; and carrying out industrial Internet of Things monitoring according to the digital workshop task allocation data to obtain industrial Internet of Things real-time data so as to carry out digital factory whole-process collaborative auxiliary operation. By constructing a task allocation mechanism based on semantic comprehension and multi-agent cooperation, intelligent matching and flexible scheduling among various resources in a digital factory are realized, and the task execution efficiency and the resource utilization rate of the system are effectively improved.

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention relates to a power grid construction management and control method based on three-dimensional digital twinning, and relates to the technical field of power grid construction management and control, and the construction management and control method comprises the following steps: S1, a three-dimensional digital twinning model construction stage: constructing a power grid project high-precision three-dimensional model based on BIM, and superposing GIS geographic data to generate a construction scene three-dimensional digital twinning model; s2, in a construction process dynamic mapping stage, processing data of the multi-source data acquisition module in real time through an edge computing node; s3, optimizing a construction management and control decision; s4, a dynamic risk management and control stage; and S5, an execution feedback stage: forming a closed loop of three-dimensional digital twinborn model construction-construction rehearsal analysis-decision-execution-model updating. According to the power grid construction management and control method based on the three-dimensional digital twinning, the construction management and control process can be transformed from extensive experience driving to data intelligent driving, and high-reliability and high-adaptability digital infrastructure support is provided for novel power system construction.

The invention discloses a multi-granularity multi-dimensional power transmission and transformation equipment digital twinning mechanism method and system, and relates to the technical field of power transmission and transformation equipment digital modeling, and the method comprises the steps: collecting multi-dimensional physical field data, and carrying out the preprocessing; constructing a layered multi-physics field coupling model; carrying out integration and parameter adjustment on the output of the layered multi-physics field coupling model to form a unified multi-physics field coupling model; and performing simultaneous analysis on multiple physical fields to complete dynamic simulation and fault prediction. By improving the finite element analysis method and the hierarchical multi-physics field modeling technology, the technical problem that the operation state of the power transmission and transformation equipment in a complex multi-physics field coupling environment is difficult to accurately monitor and predict the fault in real time is technically solved, and the effects of improving the monitoring precision and enhancing the fault diagnosis real-time performance and the prediction accuracy are achieved.

The invention relates to the technical field of building design and digitization, and discloses an automatic design method for a special-shaped facing structure based on parametric modeling. The method comprises the following steps: firstly, acquiring a geometrical characteristic parameter set of the special-shaped facing structure, wherein the geometrical characteristic parameter set comprises curved surface curvature distribution, boundary constraint conditions and a material attribute threshold value; thirdly, according to the curved surface curvature distribution, generating an initial geometric topological grid by using a dynamic subdivision algorithm, adjusting node positions according to boundary constraint conditions to obtain an optimized structural framework, and performing layered mapping on material attribute thresholds to generate a material distribution map; then, the input parametric modeling engine generates a three-dimensional parametric model, finally, a self-adaptive adjustment strategy graph is constructed through a multi-objective optimization algorithm, and a final design scheme is output. By means of the method, automation of design of the special-shaped facing structure is achieved, design efficiency and accuracy are improved, material utilization is optimized, scheme adaptability is enhanced, and design process collaboration is improved.

The invention relates to the technical field of digital quality management, in particular to a light-weight glass bottle quality digital traceability method and system. The method comprises the following steps: acquiring glass bottle design data, and constructing a lightweight glass bottle model; detecting the structural strength of the bottle body based on the lightweight glass bottle model; carrying out bottle body surface defect detection based on the bottle body structural strength to generate bottle body surface defect data; performing defect tracing based on the bottle body surface defect data to obtain bottle body production defect process data; carrying out wall thickness non-uniformity anomaly detection based on the structural strength of the bottle body to obtain wall thickness non-uniformity data; the alignment offset of the mold core and the mold cavity is evaluated based on the wall thickness non-uniformity data; and carrying out positioning pin fracture detection according to the alignment offset of the mold core and the mold cavity to obtain positioning pin fracture data. The glass bottle production process is optimized based on the digital quality management technology, and the quality recognition rate, the abnormal response speed and the production process transparency are effectively improved.

The invention relates to the technical field of digital manufacturing, and discloses a digital twin middle station and self-healing decision system for oil and gas equipment management, which comprises a multi-source sensing terminal, a twin optimization module, a fault topology diagnosis module and an early warning execution terminal, a multi-modal synchronous fusion mechanism is constructed, and when the state of oil and gas equipment is monitored, a heterogeneous data alignment standard is formulated, and a dynamic frequency normalization rule is set for different equipment types, so that the definiteness of multi-source sensing data fusion is ensured; meanwhile, vibration, temperature, pressure and sound wave data are synchronously collected in real time, millisecond-level detection can be achieved, the data time difference problem can be eliminated, the accuracy of equipment state feature extraction is guaranteed, and the feature fusion error is further reduced; and generating a self-adaptive correction coefficient in real time by calculating the dynamic deviation of the physical model and the data model.

The invention discloses a high and large formwork engineering supporting system construction method, and belongs to the technical field of building engineering. Comprising the following steps: step 1, arranging intelligent nodes in a high and large template support system to realize information sharing and group cooperative regulation and control among the nodes; step 2, dividing the support system into a plurality of mutually associated load control areas, and setting differentiated load control parameters; step 3, automatically optimizing a pouring path; 4, when the concrete strength reaches a preset threshold value, the supporting rigidity or the reserved deformation amount is automatically adjusted according to a preset program, and the concrete structure bears the dead weight step by step; 5, the temporary load is automatically compensated, when the load exceeds a safety threshold value, a load redistribution mechanism and a reinforcing device are triggered, meanwhile, an alarm is started, and abnormal data are pushed; and step 6, continuously optimizing control parameters, accumulating construction data, constructing a digital construction record and a knowledge base, and realizing intelligent iterative upgrading of the construction method.

The invention discloses a digital intelligent service system for enterprise services, which belongs to the field of enterprise digital services and comprises a user demand analysis module, an intelligent data adaptation module, a service resource matching module, a service efficiency evaluation module and a user-friendly interface. The user demand analysis module is used for semantic analysis and classification decision making; the intelligent data adaptation module identifies and analyzes the protocol type, and establishes an intelligent data transmission channel; the service resource matching module carries out resource pre-screening and accurate matching; the service efficiency evaluation module tracks an identifier and captures a four-dimensional index system in real time, and the dynamic evaluation unit realizes service state grading early warning through a sliding window algorithm; according to the invention, accurate demand identification is realized, the response speed and the data transmission efficiency are improved, the user satisfaction is improved, the service matching accuracy is enhanced, the resource utilization efficiency is optimized, the service capability and the customer experience are improved, and maximization of economic benefits and social values is realized.

The invention discloses a hydraulic engineering digital design method based on digital twinning, and relates to the technical field of hydraulic engineering design. According to the digital twin-based hydraulic engineering digital design method, design demand information of a to-be-designed diversion tunnel is obtained and input into a pre-trained building recognition model for comprehensive analysis, a spatial layout map of the to-be-designed diversion tunnel is obtained, and a tunnel design digital twin model is constructed; simulation data of the tunnel design digital twinborn model are obtained, simulation analysis is carried out respectively, a tunnel construction risk index and a hydraulic action risk comprehensive index of the tunnel design digital twinborn model are obtained, comprehensive analysis is carried out, and a tunnel feasibility index of the tunnel design digital twinborn model is obtained; according to the method, the tunnel design digital twin model is subjected to design optimization based on the feasibility index, so that a lagging mode of re-evaluation after building is effectively avoided, later frequent reinforcement and reworking are prevented, and the engineering safety coefficient is improved.

The invention provides a dynamic exhibition system for digital museum exhibits, and relates to the technical field of digital exhibition, and the system comprises a database building module which is used for obtaining an exhibit multi-angle image set to generate an exhibit three-dimensional model set, and building a digital database; the dynamic scene construction module is used for setting a display scene and constructing a dynamic scene to obtain a dynamic scene layout library; the exhibition platform building module is used for carrying out association mapping exhibition and virtual interactive visiting on the digital database and the dynamic scene layout library and building a virtual exhibition platform; and the dynamic exhibition module is used for calling the virtual exhibition platform to the target user to carry out exhibition interaction service and scene dynamic adjustment. According to the method and the device, the technical problems of single exhibition form and insufficient immersion and interactivity of the digital museum due to the fact that the exhibition scene is statically set and the exhibit and the exhibition environment are lack of linkage coupling in the prior art are solved, and the technical effects of improving the exhibition flexibility, richness and immersion experience are achieved.

The invention discloses an electrical work ticket intelligent generation method and device, a medium and equipment in the technical field of power systems, and aims to solve the problems of serious module decoupling, dependence on manual connection and insufficient intelligent generation capability in the prior art. The method comprises the following steps: generating a required digital knowledge base and an electrical work task description generation work ticket based on a pre-constructed work ticket by utilizing a multi-model collaborative generation architecture; the multi-model collaborative generation architecture comprises a rule driving module used for calling a corresponding template based on task element matching; the task execution unit is used for executing a specific subtask according to a pre-deployed lightweight model or rule engine; and the large language model is used for performing semantic understanding and reasoning according to the electrical work task description, calling the rule driving module and the task execution unit according to a semantic understanding and reasoning result, and generating a work ticket in combination with a digital knowledge base required by work ticket generation. The method has both the accuracy of structured knowledge recognition and the flexibility of natural language generation.

The invention discloses an intelligent logistics digital warehouse management method based on deep learning, and relates to the technical field of warehouse management, and the method comprises the steps: calculating the correlation of SKUs through Graph SAGE, constructing an SKU incidence matrix, optimizing an SKU combination based on an SKU co-occurrence frequency, calculating an SKU storage optimization strategy through Transform, analyzing the storage relation between the SKUs through an attention mechanism, and optimizing a storage layout in combination with GNN. A high-frequency SKU can be located in an optimal storage area, in a sorting task scheduling link, a sorting robot is trained by adopting reinforcement learning, an optimal sorting path is autonomously learned in a warehouse environment, optimal distribution of AGVs and manual tasks is calculated in combination with GNN, collaborative operation of automatic equipment and manual operation is balanced, and path conflicts and invalid movement are effectively reduced; and after the task is executed, recording the sorting time and a path optimization result, and applying feedback data to self-supervised learning to optimize a warehouse management strategy, so that SKU storage, a sorting path and task scheduling can be dynamically adjusted.

The invention relates to the technical field of construction stage management, in particular to a BIM-based road construction digital management system, which comprises a component parameter acquisition module, a process topology construction module, a state trigger mapping module, a logic conflict judgment module and a scheduling path adjustment module. According to the method, through continuous collection and analysis of the component state, dynamic monitoring of the connection state, geometric intersection and contact time is achieved, the construction change sensing capacity is improved, the dependency relationship is constructed in combination with component space adjacency and time overlapping, the dispatching path and field matching degree is enhanced, and through linkage updating of the component state and model attributes, the construction efficiency is improved. According to the method, the execution state is visual and controllable, scheduling reconstruction is carried out after time dependence conflicts are recognized, synchronous updating of model views is completed, a closed-loop dynamic scheduling mechanism is formed, the task allocation accuracy, the flow connection efficiency and the field scheduling response capability are integrally improved, and the real-time performance and the intelligent level of construction management are enhanced.

The invention relates to a digital life individuation implementation method and device, equipment and a medium. The method comprises the steps of obtaining user interaction information in response to an obtained user input instruction; preprocessing the user interaction information according to a set mode to obtain a user interaction text; inputting the user interaction text into the digital life entity to obtain a personalized reply; the personalized reply comprises a target person and audio data; and generating an interactive video corresponding to the personalized reply based on digital human rendering. By adopting the method, personalized digital cloned construction, cross-space-time emotional interaction and cultural heritage digital inheritance can be realized through emotional analysis, behavior pattern learning and the like, and the method is suitable for scenes of emotional science and technology, digital immortality, family archive management and the like.

The invention discloses a digital intelligent management early warning system based on power grid construction, and relates to the technical field of power grid early warning management. The intelligent management early warning center is in communication connection with a data acquisition module, a fault feature analysis module, a fault monitoring module, a fault evaluation module, an early warning grading module, an early warning generation and release module and an emergency response module. According to the method, the electrical parameters and the environmental parameters in the operation of the power grid are monitored in real time, abnormal conditions in the power grid are rapidly identified, fault features are extracted from a large number of historical fault cases and real-time data, the design parameters and the operation specifications of the power grid are combined, the fault evaluation standard is formulated, the coping capacity for the power grid faults is improved, and the fault diagnosis accuracy is improved. When a fault occurs, a response is quickly made, and through timely issuing of early warning information, it is ensured that related personnel can take actions quickly, so that the power failure time is shortened, and the reliability of a power grid and the satisfaction degree of users are improved.

The invention discloses a surface mine digital safety production management method and device and a medium, and relates to the technical field of intelligent mines, and the method comprises the steps: collecting rock mass physical and mechanical parameters of a gold mine mining area and three-dimensional geometric morphology data of a blasting working face, and taking the parameters as physical constraint conditions to construct a digital twinborn body; a preset target blasting scheme is called to be input into the element reinforcement learning agent, multi-round simulation deduction is carried out through a blasting scheme evaluation strategy, and a simulation deduction result is generated; when the peak particle vibration velocity in the simulation deduction result exceeds a preset peak particle vibration velocity threshold value, generating a parameter adjustment suggestion; and the parameter adjustment suggestion is fed back to the element reinforcement learning agent for iterative optimization until the peak particle vibration velocity does not exceed a preset peak particle vibration velocity threshold, and a blasting scheme is generated. Through autonomous exploration of the meta-reinforcement learning agent in the blasting parameter space, the blasting scheme evaluation strategy with adaptability and reliability can be efficiently generated.

The invention discloses an interactive access method, device and equipment of an intelligent agent and a storage medium, and relates to the technical field of artificial intelligence, and the interactive access method of the intelligent agent comprises the following steps: receiving an initial service session request initiated by a user, carrying out request interception on the initial service session request based on session request information, determining a target service session request; and determining a service scene to which the target service session request belongs according to a preset intention recognition model, calling an intelligent agent in the service scene to respond to the target service session request, and returning a standard service answer corresponding to the target service session request. According to the technical scheme, the threshold of accessing the intelligent agent by the user is reduced, and the processing efficiency of the digitization capability of each service scene is improved.

The invention relates to the technical field of building construction, in particular to a construction method of a variable-curvature super-depth fusiform skylight in a steel structure, and solves the construction problem of a complex space curved surface through digital design, factory prefabrication, intelligent installation and real-time monitoring and compensation. Through a digital twin-driven construction technology system, the worldwide problems of the variable-curvature ultra-deep steel structure in the aspects of form precision, mechanical stability and construction efficiency are solved, a technical normal form capable of being popularized is provided for the ultra-deep and variable-curvature steel structure, and building form innovation is promoted. And meanwhile, the dependence on manpower is reduced through modular and mechanical operation, the construction period is shortened, the safety is improved, and the cost is reduced by combining prefabricated unit components with dynamic monitoring.

The invention relates to the technical field of digital public services, in particular to a digital public service integration platform and device based on intelligent recommendation and a medium. The method comprises the following steps: firstly, collecting and analyzing basic information and behavior data of a user in real time through a user portrait construction module, and constructing a multi-dimensional user feature vector; secondly, performing structured processing on the government affair service data by using a service feature extraction module, and extracting a service association relationship and scene features; then realizing accurate matching of the user feature vector and the service feature matrix based on an intelligent recommendation engine; and finally, continuously collecting user feedback and dynamically adjusting a recommendation strategy through a real-time feedback optimization module. According to the method, scene-based precise pushing of the government affair service is realized, a continuous optimization mechanism of the recommendation effect is established, the recommendation strategy can be dynamically adjusted according to the user characteristics and behaviors, and the intelligent level and user experience of the government affair service are remarkably improved.

The invention relates to the technical field of Internet of Things, in particular to a digital marketing management system and method for telecommunication services, and the system comprises a user behavior monitoring module, a path track extraction module, a dynamic work and rest modeling module, a behavior cycle analysis module and a user portrait generation module. According to the method, through group feature modeling of cellular communication data, accurate calculation of a behavior trend change rate, dynamic description of group behavior features and extraction of a high-frequency region node sequence, analysis of a behavior track is converted from a single-point discrete state to a path association mode, and recognition of a group activity mode is realized; based on group residence duration statistics and cross analysis of multi-dimensional behavior indexes, a time distribution model is constructed, a stable behavior interval and a typical mode are identified, the analysis capability of group behavior characteristics is improved, and in combination with holiday and festival characteristic identification and hot spot area distribution characteristics, marketing strategy matching is optimized, and the accuracy of a grouping recommendation strategy is improved.

The invention relates to the technical field of logistics transportation management, and discloses a vehicle transportation management method based on a digital technology, and the method comprises the following steps: collecting the energy state data of a vehicle in real time through a vehicle monitoring module; transmitting the collected vehicle data to a big data platform by using an Internet of Things technology, analyzing the data, and generating an early warning signal of an energy state; when the early warning signal is triggered, determining an optimal supply path according to the current position of the vehicle and traffic information, and arranging an energy supply service in advance; and through an intelligent scheduling module, according to real-time traffic information, vehicle load and destination distance factors, a transportation route and task distribution of the vehicle are dynamically adjusted. Through real-time monitoring and analysis, the system can automatically trigger a supply early warning signal when the energy state is lower than a safety threshold value, so that non-planned parking caused by energy exhaustion is avoided, and the accuracy of energy management and the operation reliability are remarkably improved.

An industrial information hub (IDH) serves as a single industrial ecosystem platform where multiple participants can deliver repeatable and standardized services relevant to their core competencies. The IIH system is centered around the development of an ecosystem that creates and delivers value to users—including industrial enterprises, OEMs, system integrators, vendors, etc.—through the aggregation of digital content and domain expertise. The IIH system serves as a trusted information broker between the ecosystem and the OT environments of plant facilities, and provides a platform for connecting assets, contextualizing asset data and providing secure access to the ecosystem. Additionally, the IIH system provides tools and support to OEMs and other subject matter experts, allowing those experts to enable their digital assets for use in the ecosystem. The IIH system reduces the cost and risks for digital transformation of industrial assets.

The invention discloses a flow field video generation method based on a policy value architecture and online physical exploration, and belongs to the technical field of crossing of artificial intelligence and computational fluid dynamics (CFD), and the method comprises the following steps: step 1, constructing an unsteady flow field multi-modal training data set, step 2, constructing a generative network system based on an Actor-Critic architecture, step 3, constructing an unsteady flow field multi-modal training data set, and step 4, constructing an unsteady flow field multi-modal training data set. Step 4, supervised fine tuning training is carried out in the first stage; step 5, online physical exploration of a generator is carried out in the second stage; step 6, feedback co-evolution of a physical encoder is carried out in the third stage; and step 7, reasoning generation of an unsteady flow field video is carried out. According to the method, a reinforcement learning architecture containing an Actor and a Critic is constructed, a physical equation is packaged into a digital environment, and a training strategy of basic supervision fine tuning, online physical exploration of a generator and coevolution feedback of an encoder is adopted.

The invention relates to a visual narrative generation method oriented to a Chinese ancient time sequence image. Coherent creation under a historical context is realized through multi-modal collaboration and knowledge guidance. According to the algorithm, a culture-enhanced CLIP-ct model is adopted to carry out multi-modal feature fusion, an ornamentation semantic layer is expanded in a traditional CLIP architecture, and visual culture symbols such as traditional painting features and clothing patterns are accurately decoded; constructing a KG-Transform hybrid generation framework, and fusing a knowledge graph through a dynamic knowledge gating mechanism; meanwhile, culture conflict detection is designed to ensure time consistency, and finally plot development is optimized through Monte Carlo tree search to ensure rationality and creativity of plots. According to the method, an extensible technical normal form is provided for the field of cultural computing, the method can be applied to scenes such as cultural relic digital narration and non-cultural skill inheritance, and intelligent decoding and innovative expression of traditional cultural resources are promoted.