277 results about "Entity model" patented technology

The invention discloses an intelligent construction method, system, equipment and medium based on a digital twin tunnel, and aims to construct a high-precision physical entity model by fusing dynamic and static data in real time through multiple types of sensors so as to improve data acquisition comprehensiveness; based on tunnel-level, soil-level and ground building-level multi-level modeling and finite element analysis, fine mechanical stability simulation is realized; multi-dimensional data features are extracted by combining a convolutional neural network algorithm, security risks are evaluated, and a reinforcement scheme is optimized through dynamic iteration; a closed-loop regulation and control mechanism of data monitoring, numerical simulation and dynamic feedback is formed by utilizing a collaborative architecture of a sensing layer, a simulation layer and a display layer, so that environmental disturbance is effectively reduced, and construction safety is guaranteed; according to the method, digital twinning, BIM, finite element analysis and deep learning are fused, real-time monitoring and intelligent optimization of the whole construction process are achieved, efficiency and safety are remarkably improved, and influences on the surrounding environment are reduced.

The invention relates to the technical field of building information modeling, and discloses a parameterized BIM modeling method, which comprises the following steps: step 1, acquiring specific design parameters of a modeling object in a project design requirement, marking key geometric parameters of the object, including length, width, height, volume and material characteristics, and defining units, physical meanings and application ranges of the parameters in a marking process, a basis is provided for subsequent entity model construction; and 2, based on the geometric parameters marked in the step 1, a solid model is constructed through a BIM modeling tool, and the solid model is a visual model with the shape, the size and the position determined through the geometric parameters in a three-dimensional space. The three-dimensional BIM model is dynamically generated and modified by modifying geometric parameters, model construction is more flexible and efficient due to introduction of parameterization logic, automatic adjustment and rapid iteration of the model are achieved, and the reusability of BIM modeling and the design efficiency of the building model are remarkably improved.

The invention discloses a scaffold steel plate net building method based on BIM, and relates to BIM modeling. The method comprises the steps that feature parameters of a scaffold steel plate net are obtained; according to the characteristic parameters, establishing a three-dimensional entity model of the scaffold steel screen by using a parametric modeling method; performing grid division on the three-dimensional solid model by adopting a self-adaptive grid division algorithm to obtain a finite element grid; identifying a stress concentration area in the finite element grid by adopting a self-adaptive grid encryption algorithm, and performing grid encryption on the stress concentration area to obtain an encrypted finite element grid; performing structure optimization on the encrypted finite element mesh by adopting a topological optimization algorithm to obtain an optimized three-dimensional entity model of the scaffold steel plate mesh; and performing component arrangement optimization on the three-dimensional entity model after structure optimization by adopting a discrete topological optimization algorithm to obtain a final scaffold steel plate net BIM model. In order to solve the problem that in the prior art, scaffold steel plate net erecting redundancy is large, the redundancy design is reduced.

The invention discloses a grid model and entity model fusion method, computer equipment and a storage medium. The method comprises the steps of data preprocessing, data conversion and data fusion. Performing data cleaning, topological repair and geometric optimization on the grid model to obtain first model data, and performing closure repair, connectivity repair and redundant element cleaning on the entity model to obtain second model data; converting the first model data and the second model data into a grid-entity hybrid model Sa and a grid-entity hybrid model Sb; and performing data fusion on the grid-entity hybrid model Sa and the grid-entity hybrid model Sb through bounding box detection, model intersection, connection of intersection edges into rings, combination of the rings into surfaces and enclosing of the surfaces into a body, and rendering the fused data to obtain the grid-entity hybrid model. The method has the advantages that the grid and the entity heterogeneous model are effectively fused, and the grid structure and the entity structure can be displayed at the same time after rendering.

The present disclosure provides systems and methods performed in a central system. An initial entity model comprising a plurality of artefacts is formed. A runtime engine determines a plurality of available agent engagements based on the initial entity model. Responsive to an input selecting one of the available agent engagements, a notification is sent to an external autonomous agent. An indication of an action to be performed is received from the external autonomous agent. Responsive thereto, a message is sent to an external service indicating the action, thereby causing the action to be performed. The entity model is updated with a new artefact corresponding to the performed action, and a further plurality of agent actions is determined based on the updated entity model.

The invention relates to the technical field of chemical enterprise production management, in particular to a chemical enterprise safety production informatization management system which comprises a sensing network layer architecture, a digital twin management platform, a risk management and control and decision center, a process closed-loop management center and an emergency cooperative processing platform. According to the chemical enterprise safety production informatization management system and method, through construction of a chemical knowledge graph, on the basis of a dynamic risk matrix and an AI prediction model library, equipment remaining service life prediction, process tiny anomaly capture and accident consequence simulation processing are realized; meanwhile, a root cause analysis module is used for associating low-level alarm and traversing a knowledge graph to automatically infer a fault root, physical equipment and a virtual model are bound through an entity-model mapping engine, the model state is dynamically updated in combination with a real-time rendering technology, and technological parameter optimization, accident deduction and scheme verification can be completed in an analogue simulation engine; and the management intuition and the decision-making scientificity are effectively improved.

An apparatus and method (200) for defining a semantic framework for a plurality of entities in a computer simulated environment. The method (200) includes receiving data from one or more data acquisition devices (104), translating, the data into one or more executable queries to extract data relating to the one or more elements from the knowledge database (106). The method (200) further includes assembling an entity model with one or more elements identified from the CNL data, each element operationalized using a model ontology and instantiating each element in the entity model using a plurality of instances for each element in the entity model to generate a semantic binding among the plurality of elements. Furthermore, the method (200) includes transforming the semantic binding into a knowledge graph using standard graph databases and translating the semantic description from the knowledge graph into an executable configuration for the metaverse.

The invention relates to the technical field of computer networks, in particular to a network risk processing method and system based on a graph. The method comprises the following steps: performing network entity model construction on a target network to obtain a target network entity model; performing network entity graph modeling on the target network based on the target network entity model to obtain a network entity relationship graph; performing dynamic graph updating on the network entity relation graph to obtain an updated network entity relation graph; carrying out risk propagation source node determination on the updated network entity relation graph to obtain a risk propagation source node set; and performing global risk assessment on the target network according to the risk propagation source node set based on the updated network entity relationship graph to obtain a network global risk assessment result. According to the invention, the efficiency and accuracy of network risk assessment are improved.

The invention relates to a method, a device and equipment for constructing a digital twin model of a physical entity system. The method comprises the following steps: receiving physical entity models sent by each computing device in the distributed system and state data of each physical entity model; the physical entity model is a simulation model of a physical entity associated with the computing device; performing fusion processing on each physical entity model and the corresponding state data to construct a digital twin model of the physical entity system; the physical entity system comprises physical entities associated with all computing devices. By adopting the method, fusion processing can be performed on each physical entity model and the corresponding state data in a centralized manner through the cloud equipment, so that the digital twin model of the physical entity system can be accurately and efficiently fused and constructed, and the problem of difficulty in constructing a plurality of physical entities in related technologies can be solved.

The invention relates to the field of computer graphics, reverse engineering and additive manufacturing, discloses a multi-modal fusion and physical constraint three-dimensional point cloud geometric modeling system and method, and aims at overcoming the defects that traditional three-dimensional reconstruction entity attributes are missing, key features are prone to being lost, semantic understanding does not exist, and process automation is low. The system comprises a point cloud preprocessing module, a semantic segmentation and recognition module, a mixed geometric reconstruction module, a multi-component assembly and physical constraint solution module and an entity model output module. The method comprises the following steps: denoising and sampling an original point cloud, realizing semantic and instance double segmentation through a Point Net + + network, endowing a geometry-function composite label, completing hybrid reconstruction through improved Poisson reconstruction, parameterized B-Rep fitting and standard component library matching, and outputting a multi-format engineering available model after physical constraint verification and automatic correction of a violation model. According to the method, automatic, high-fidelity and high-practicability conversion from the point cloud to the engineering-level entity model is realized, and the method is adaptive to multiple industrial application scenes.

The invention discloses a digital twin-driven mine hoist monitoring data field adaptive fault diagnosis method, and the method comprises the steps: building four groups of physical entity models on a test bench, and obtaining a measurement target field data set; respectively establishing an outer ring fault digital twinning model, an inner ring fault digital twinning model, a roller fault digital twinning model and a health model digital twinning model, and obtaining corresponding simulated fault data sets; constructing a fault diagnosis model based on domain adaptation; constructing a domain adversarial neural network; sending the simulation source sample and the actually measured target sample into a domain adversarial neural network at the same time, reducing the feature distribution difference between the simulated source domain data and the measured target domain data by using the domain adversarial neural network, and obtaining a fault diagnosis model based on domain adaptation; and performing real-time fault diagnosis by using the fault diagnosis model based on domain adaptation, and outputting a fault diagnosis result. According to the method, the problem of inconsistent distribution of the test data and the training data can be effectively solved, and the accuracy and timeliness of fault diagnosis can be effectively improved.

The invention discloses an entity three-dimensional model-based plate intelligent optimization typesetting method and system. The method comprises the following steps of: receiving each original plate parameter and each plate parameter corresponding to a first entity; setting a discharge forbidding area according to the vertex coordinates of the defective rectangular area of the original plate; adopting a first typesetting algorithm to sequentially fill and typeset the plurality of plates in the original plate from the reference point to obtain a preliminary typesetting of the original plate; obtaining an available gap area according to the initial typesetting of the original plate; carrying out gap filling on the remaining plates to the available gap area to obtain the final layout of the original plates; repeating the steps to obtain final typesetting of each original board, and obtaining a complete typesetting scheme according to each final typesetting; evaluating the complete typesetting scheme through a first evaluation objective function to obtain a first evaluation result; and outputting the complete typesetting scheme with the first evaluation result meeting the requirement according to the requirement. The typesetting calculation complexity is reduced, and the material utilization rate is improved.

A computing system for simulating allocation of resources to a plurality of entities is disclosed. The computing system can be configured to input an entity profile that describes a preference and / or demand of a simulated entity into a reinforcement learning agent model and receive, as an output of the reinforcement learning agent model, an allocation output that describes a resource allocation for the simulated entity. The computing system can select one or more resources based on the resource allocation described by the allocation output and provide the resource(s) to an entity model that is configured to simulate a simulated response output that describes a response of the simulated entity. The computing system can receive, as an output of the entity model, the simulated response output and update a resource profile that describes the at least one resource and / or the entity profile based on the simulated response output.

The invention relates to the technical field of geological three-dimensional modeling, and discloses a mineral reserve estimation modeling method, system and equipment for optimizing block division. The method comprises the following steps: delineating an ore body according to imported drilling data, and establishing an entity model for estimating the ore body; block division is carried out on the entity model based on earth grid division or space grid division; converting the drilling data into block data according to the size of block division, and carrying out statistics on the block data to obtain a data distribution characteristic graph; calculating a variation function based on the data distribution characteristic graph and performing cross validation; and estimating according to the variation function and the block data, and outputting a resource reserve estimation report. Earth grid division is introduced, and during block division, longitude and latitude reference earth grid division and space grid division adopting a digital storage octree index can be selected, so that the storage speed is increased, the memory space is saved, the method adapts to multi-scale index transformation, data integration sharing and hierarchical management are facilitated, and the efficiency is improved. And rapid construction of the ore body and block subdivision storage are realized.

The invention relates to a power load spatio-temporal dynamic knowledge graph construction and load prediction method, which comprises the following steps of: constructing a text and digital sequence hybrid vector coding module, providing a hierarchical entity relationship joint extraction framework oriented to power system load data, constructing a Multi-Encoder-Bi-GRU-CRF power load entity recognition model, and constructing a power load entity model. Constructing a power load spatio-temporal dynamic knowledge graph in combination with a predefined relation rule base; meanwhile, time-space sub-graphs are divided, a space-time coupling self-adaptive adjacency matrix is constructed, and the space-time dependency relationship between nodes is quantified; and finally, combining the knowledge graph node embedded vector and the adjacency relation embedded vector, and jointly extracting the spatial feature and the time feature of the power load by adopting a space-time diagram convolutional neural network. Therefore, the load prediction algorithm provided by the invention not only can give full play to the advantages of multi-modal semantic integration and space-time modeling capability of the knowledge graph, but also can improve the load prediction precision, assist in realizing refined energy management of the power system and assist in making an optimal scheduling strategy, and has a good engineering application prospect.

The invention discloses a coal mine robot cluster-oriented virtual entity synchronous mapping method. The method comprises the following steps of: constructing a virtual entity synchronous mapping system consisting of a coal mine robot cluster physical entity, a coal mine robot cluster virtual entity, coal mine robot cluster twin data, cluster service application and information interaction; a coal mine robot cluster is used as a physical entity object, an OPC UA communication protocol is used for data collection, the collected data is processed, a virtual entity is driven in a script mode based on a Unity 3D physical engine, and therefore a virtual-real mapping channel is established; converting various non-standardized data structures of the robot cluster into standardized data structures; data of the heterogeneous robot are collected and transmitted through standardization of various communication protocols, and the data are used for driving the virtual entity model. The method has the advantage of performing synchronous mapping on the virtual entities so as to facilitate intelligent management and control.

The invention relates to the technical field of experiment reuse in the field of information spreading, and provides a field scientific experiment-oriented behavior gene framework description method, which comprises the following steps of: analyzing a behavior model to obtain a behavior level description file of the behavior model; determining a behavior subject in an action layer behavior model in the behavior model from the behavior level description file based on the behavior level formalized description template; the action layer behavior model is a behavior gene of the simulation model; and constructing a behavior gene description file of the simulation model based on the behavior subject on the modeling granularity and the modeling structure of the behavior subject. According to the method, the behavior gene description file can be reasonably adjusted and constructed under the condition that new action modeling and original action adjustment requirements are continuously provided for the simulation model, flexible and dynamic adjustment of new achievements of scientific experiments is achieved, and a self-developed behavior model can directly drive a heterogeneous entity model to run.

The invention relates to the technical field of data warehouse construction, in particular to a data warehouse construction method and device based on a Data Vault model, equipment and a medium. The method comprises the following steps: firstly, acquiring metadata information of a source system, and extracting a business theme identifier through semantic analysis; intelligent matching is carried out based on a preset template library, and a corresponding Hub entity model is determined; deep analysis is carried out on the data content, and a service key and an association relationship are identified; and finally, a complete Data Vault model structure is formed through association mapping. The standardization and automation of model construction are realized through the template library and the mapping mechanism, and the quality and efficiency of data warehouse modeling are remarkably improved.

The invention provides a visualization method and system based on digital twinning, and the method comprises the steps: responding to an automatic modeling request of each planning end for planning a park, obtaining video data shot by a recording device for an entity model based on a collection visual angle, and enabling the entity model to comprise a dynamic planning area and a fixed planning area; according to the video data, determining customization elements configured for the dynamic planning area by each planning end, performing customization updating on an initial twin space corresponding to the entity model based on the customization elements, and determining the dynamic planning area which does not meet a cost planning condition as a to-be-scheduled area, calling a planning adjustment strategy to adjust and update a virtual planning area corresponding to the to-be-adjusted area in the initial twin space to obtain customized display spaces corresponding to the planning ends, and obtaining selection coefficients corresponding to the customized display spaces, and determining that the customized display space with the maximum selection coefficient is a planned selected space corresponding to the planned park.

The invention provides a method for querying geometric elements in different geometric modeling engines and a related product, and the method comprises the steps: responding to a first user operation, and determining a target positioning UV parameter point coordinate in a UV parameterization plane; determining target geometric elements from the entity model according to the coordinates of the target positioning UV parameter points; and determining a target geometric modeling engine of the currently loaded entity model, and determining target identification information of the target geometric element in the target geometric modeling engine. According to the geometric modeling method and device, a user can select the points near the geometric elements needing to be operated by operating the interactive interface and map the points to the corresponding geometric elements through the coordinates corresponding to the points, so that the situation that the geometric modeling efficiency is greatly improved due to different identification modes in different geometric modeling engines can be avoided. And the problems of narrow use case application range, non-visual query result and the like existing in querying the geometric elements by using the ID are solved.

The invention belongs to the technical field of construction scheme design, and discloses a construction scheme pre-design system and method based on an AI virtual technology. Comprising the steps of obtaining building drawing data, building engineering project requirement text data and historical construction data, and analyzing the building engineering project requirement text data to obtain building engineering construction requirements; pre-selecting a construction scheme of the constructional engineering according to the constructional engineering construction requirements, the constructional drawing data and the historical construction data, creating a three-dimensional entity model of the constructional engineering according to the constructional drawing data, and simulating the construction operation process of the constructional engineering according to the pre-selected construction scheme of the constructional engineering and the three-dimensional entity model of the constructional engineering; performing risk detection in the simulated construction operation process of the building engineering; performing optimization adjustment according to a risk detection result; and the reasonability of pre-design of the construction scheme is further improved, so that the construction speed of the building engineering is increased, and the construction cost of the building engineering is reduced.

The invention discloses a boundary event aggregation classification algorithm based on space-time correlation analysis. The algorithm comprises the following steps: constructing event classification and a named entity model; calculating association rules between border events based on the historical event topic collection data; constructing a affair graph based on association rules; performing event classification and named entity identification on the border events based on event classification and a named entity model; and based on the event classification and the named entities, classifying and sorting the border events through the event atlas to obtain a border event aggregation result. Aiming at the characteristics of border event data, the invention provides an incidence relation mining algorithm based on the border events, the event atlas of the border events is obtained and is used for incidence aggregation of the events, the border event rules can be effectively extracted, and the events are collected according to themes.

A natural language understanding (NLU) framework includes a concept system that performs concept matching of user utterances. The concept system generates a concept cluster model from sample utterances of an intent-entity model, and then trains a machine learning (ML) concept model based on the concept cluster model. Once trained, the concept model receives semantic vectors representing potential concepts extracted from utterances, and provides concept indicators to an ensemble scoring system. These concept indicators include indications of which concepts of the concept model that matched to the potential concepts, which intents of the intent-entity model are related to these concepts, and concept-relationship scores indicating a strength and / or uniqueness of the relationship between each concept-intent combination. Based on these concept-related indicators, the ensemble scoring system may determine and apply an ensemble scoring adjustment when determining an ensemble artifact score for each of the artifacts extracted from an utterance.

The invention discloses a named entity recognition model training method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining domain data, and carrying out the data cleaning processing of the domain data, and obtaining sample data; obtaining field information of the sample data, and analyzing and processing the sample data to obtain semantic information of each piece of data in the sample data; performing entity labeling on the sample data according to the set entity type, field information and semantic information to obtain labeled sample data; and training the entity naming recognition model according to the labeled sample data, and obtaining a trained named entity recognition model after the training is completed. According to the technical scheme, the data is distilled through the large-scale language model, the unlabeled data is labeled in a specific scene, then the named entity model is trained, manual labeling is not needed, and the training convenience and accuracy are improved.

The invention provides a method and equipment for creating a three-dimensional welding seam model, and relates to the technical field of rail transit equipment.The method comprises the steps that according to geometric feature data of all first-level parts in an assembly model, the positions of welding seams between the first-level parts are recognized; creating a parameterized three-dimensional welding seam entity model at each welding seam position according to the parameterized correlation formula and the welding seam feature data corresponding to the welding seam position; the parameterized correlation formula is a correlation formula between a weld size parameter and a corresponding parent part size parameter; according to the three-dimensional welding seam entity model and the welding seam feature data, generating a corresponding welding seam marking symbol in the target welding seam view; and creating and inserting a welding seam part corresponding to the three-dimensional welding seam solid model in the assembly structure tree of the assembly body model. According to the method, automatic collaborative updating during design change and unified management of welding design data are achieved through a parameterization association mechanism, and the quality and efficiency of welding seam design are effectively improved.

The invention relates to the technical field of deduction engines, in particular to a distributed joint combat deduction engine architecture based on multi-agent reinforcement learning, which comprises a data processing layer capable of acquiring target area environment data, entity historical state data and trust data, target area environment data and entity historical state data are processed through a distributed computing framework, and original trust vectors are generated through trust data; the simulation engine layer can perform environment modeling and entity modeling through an entity modeling engine and an environment simulation engine; carrying out credibility dynamic modeling based on the historical behaviors of the intelligent agent; the joint command layer can coordinate and dispatch a target environment entity and environment resources through a coordination engine according to a preset command scheme, and performs cross-domain trust conduction; and the analysis and evaluation layer can deduce and restore in real time, predict the situation of the target area and evaluate the robustness of the command scheme.

A reconstruction method and apparatus for a three-dimensional entity model, a device, a medium and a program product. The method comprises: obtaining three-dimensional space information corresponding to a three-dimensional entity model; on the basis of the three-dimensional space information, carrying out voxel division on the three-dimensional entity model, and determining voxels corresponding to the three-dimensional entity model and connected in a tree shape, wherein the voxels are distributed on the surface of the three-dimensional entity model, and used for representing the geometric shape of the surface of the three-dimensional entity model; on the basis of the voxels connected in the tree shape, constructing a three-dimensional mesh model corresponding to the three-dimensional entity model, wherein the three-dimensional mesh model is used for reconstructing a three-dimensional entity model after rendering.

The invention discloses an equipment thermal fluid simulation method and device, equipment and a medium, and the method comprises the steps that an open document submitted by a user is analyzed, the open document comprises a plurality of page units, and equipment configuration data and simulation task data are provided through the page units; updating a three-dimensional body mesh model in a simulation framework into an equipment entity model according to the equipment configuration data; calling a solver in a simulation framework according to the simulation task data to determine fluid simulation result data of the equipment entity model; and displaying corresponding simulation effect information on a graphical user interface according to the simulation result data. According to the method and the device, the open document submitted by the user is automatically analyzed, so that the dependence on professionals is reduced, and the simulation efficiency is remarkably improved.

The invention discloses an information knowledge extraction method based on a power system, a controller and a storage medium. The method comprises the following steps: reading non-structural data of an information document of the power system; performing data cleaning on the non-structural data to obtain power system data elements; preprocessing the data elements of the power system to obtain segmented words, and correcting the segmented words by adopting a reverse maximum matching algorithm; based on a standard power system metadatabase, according to the construction direction of a power system, a data meta-information and entity extraction rule is established, and device entity category candidate word extraction is achieved; identifying and filtering the equipment entity category candidate words to obtain high-frequency nouns; performing entity joint extraction on the equipment entity model candidate words to obtain confidence high-frequency vocabularies; generating equipment entity category and model labels according to the high-frequency nouns and the vocabularies with the highest confidence coefficient, and storing the equipment entity category and model labels into an index; and outputting equipment entity knowledge according to the leading rope. According to the method, the entity identification accuracy of the power system data element naming equipment is improved.

The invention relates to a CGF-oriented typical normal form behavior model conversion method and device. The method comprises the following steps: receiving a conversion instruction input by a user; when a first conversion instruction is received, adopting a preset first conversion algorithm to respectively map each task flow of the finite-state machine and a state and transfer relationship in each task flow into a sub-tree of a behavior tree and a hierarchical node structure of each sub-tree, and outputting a behavior tree description file; when a second conversion instruction is received, disassembling the tree structure of the behavior tree into a state transition network of a finite-state machine by adopting a preset second conversion algorithm, and outputting a finite-state machine description file; and according to the description file output after receiving the conversion instruction, generating a corresponding code framework and integrating the code framework to a CGF simulation platform to output a deployable CGF entity model file. By adopting the method, the efficiency, reusability and application flexibility of CGF modeling can be improved.