33 results about "Conceptual model" patented technology

The invention discloses a cutterhead structure design method combining topological optimization and finite element analysis, and belongs to the technical field of aerospace high-performance cutting tool design and manufacturing. The technical problems that a traditional cutter head depends on experience design, and rigidity, chip removal and heat stability are difficult to balance are solved. According to the method, a parameterized model is established, multi-working-condition loads including cutting loads, dynamic excitation and thermal-mechanical coupling are defined, a topological optimization technology with multi-working-condition weighted flexibility minimization as a target and a material volume fraction as a constraint is adopted, and a material optimal distribution cloud picture is generated based on a variable density method; geometric reconstruction and engineering semantic interpretation are carried out on an optimization result, and a material enrichment region is converted into engineering characteristics such as an internal reinforcing rib and a variable spiral transition structure, so that a lightweight high-performance conceptual model is formed; finally, through multi-working-condition finite element verification and manufacturing manufacturability analysis, a final design scheme meeting the requirements for strength, rigidity, dynamic characteristics and thermal stability is obtained through iteration.

The invention belongs to the technical field of system simulation, and relates to a joint simulation model integration method and tool and a medium. The method comprises the following steps: firstly, analyzing semantics of a model, including meta-model data analysis, conceptual model description analysis, static semantic analysis and dynamic semantic analysis; then performing interface function event association mapping to obtain a mapping relationship between a model interface and a standard interface; next, configuring a model integration environment, including a running environment, model assembly and scheduling parameters, a generation directory file, an agent model / model scheduling file and the like; and finally, integrating and packaging the packaged proxy model / model scheduling file and the like, and sending the packaged file to a model resource library. According to the method, automatic integration of most types of models (including components, entities, semi-physical models and systems) in the technical field of system simulation can be realized, the integrated polymorphic models can be expanded and reused, the simulation efficiency is greatly improved, and various existing model resources are fully utilized to shorten the integration period.

The invention relates to a multi-agent-based bionic domain knowledge graph automatic construction method and system. The method comprises the following steps: constructing a bionic domain conceptual model; establishing a multi-agent system, and automatically extracting bionic entities and semantic relationships between the entities from an unstructured text; carrying out multi-dimensional collaborative verification on the extracted knowledge; based on a Delphi method consultation mechanism, collaborative decision making is carried out on verification results; and performing alignment and fusion on the verified knowledge to form a structured bionic domain knowledge graph. According to the method, three core technologies of a field fine-tuning multi-agent system, a multi-dimensional collaborative verification mechanism and Delphi method consultation decision are fused, so that automatic and high-efficiency construction of the bionic field knowledge graph is realized, and the generated knowledge graph has accuracy and comprehensiveness; the technical problems that a traditional construction method is low in automation degree and the knowledge accuracy is difficult to guarantee are effectively solved, and key knowledge infrastructure support can be provided for bionic theoretical research and technical innovation.

The present invention discloses a mine disaster tracing method based on a knowledge graph, applied in coal mine safety. First, a mine disaster-related knowledge graph is built, involving three main steps: constructing a conceptual model, extracting entities from relational databases and geological maps, and establishing entity relationships based on location and process logic. Next, characteristic indexes and transmission rules for entity objects are set, categorizing entities into four types: discrete reporting, continuous monitoring, geological structure, and geological continuity. When an early warning occurs, disaster tracing is performed using the entity transmission rules and a graph traversal algorithm, identifying direct and root causes. This invention offers systematic and timely disaster tracing by utilizing a specialized knowledge graph and graph algorithms.

The invention relates to the technical field of construction of pollution site models, and particularly discloses a construction method and system of a conceptual model of a pollution site, an initial conceptual model of the pollution site is constructed by integrating multi-source heterogeneous data of the pollution site, a space-time coupling relation of pollution source-migration path-acceptor is described in a parameter matrix form, and the conceptual model of the pollution site is constructed. Then, further decomposing the field prior information model parameter matrix into independent units, taking feedback information of a benefit related party as a constraint condition, and performing panoramic semantic scanning query on the field prior information by utilizing a natural language processing technology and a semantic query algorithm; and key information gaps such as uncovered exposure paths in the site prior information are identified, so that the conceptual model of the polluted site is iteratively optimized. By means of the mode, intelligent recognition of key information gaps of the conceptual model of the polluted site can be achieved, dynamic adjustment and improvement of the conceptual model are guided, and the conceptual model better meets the actual situation and the requirements of interested parties.

The invention provides a data persistence layer design method and system, a storage medium and electronic equipment, and relates to the technical field of electric digital data processing.The data persistence layer design method based on an ontology comprises the steps that a conceptual model is constructed based on the ontology, and an SQL syntax device is created in combination with an SQL semantic graph; obtaining object data; generating an SQL statement of the object data according to the definition of the ontology and an SQL syntax device; executing the SQL statement, and storing the object data into a database; and deserializing the SQL statement to generate a class object, and assembling the class object according to the object data to generate class object data. Storage and application of the object-relational data are more convenient and efficient through meta-model modeling, developers can understand the logic relation between the object-relational data more easily, the development efficiency is improved, SQL statements are generated through an SQL syntax device, the code amount is reduced, and the maintenance difficulty of persistent layer codes is lowered.

This invention relates to the fields of tunnel engineering and 3D geological modeling technology, specifically to an intelligent modeling method and system for 3D geological uncertainty in tunnels based on transition probability geostatistics and sparse boreholes. The method includes: S1, integrating multi-source data to construct a 3D geological conceptual model; S2, statistically characterizing a one-dimensional transition probability matrix, calculating and fitting a spatial continuity and 3D anisotropic variability function model; S3, calculating the prior spatial probabilities and transition adjustment factors for various lithologies, obtaining the posterior lithology distribution of nodes through Bayesian intelligent updating, and initially assigning lithology categories to nodes through random sampling; S4, assigning the most probable lithology category to each grid node, calculating the variance of lithology values ​​across all implementations, and measuring model uncertainty; S5, outputting the optimal 3D uncertainty model for the tunnel; and S6, verification and evaluation. This invention can effectively achieve 3D heterogeneous modeling and explicit quantification of uncertainty under strong geological constraints.

A system is disclosed to build and store a conceptual model and queries for a graph database. In various embodiments, data defining one or more aspects of a conceptual model associated with a graph database is received. A logical model of the conceptual model is created based at least in part on the conceptual model. The logical model includes information defining how data is physically stored. A set of data that represents the conceptual model is stored as a graph that includes one or more nodes to represent each of the following: conceptual model metadata, one or more node labels comprising the graph database, one or more relationship types of the graph database, and one or more property definitions each associated with a property of at least one of a node label and a relationship type of the graph database.

The invention discloses an ontology-based emergency modeling method, and relates to the technical field of data science and artificial intelligence, an emergency handling conceptual model is established, the emergency handling conceptual model is a business model, a general information model is described according to domain terms, the top-layer information demand of business is defined, and the top-layer information demand of the business is established; the main elements include place, time, subject, subject, cause, process, consequence, influence, treatment guidance, treatment mechanism, treatment strength and response action. The elements comprise three relations of entities, entities and events, and events and events. According to the ontology-based emergency modeling method, the general information model answers concerned and concerned questions of field scenes and indicates required entity concepts and key attributes.

The application relates to a kind of operation and maintenance fault monitoring system modeling method based on knowledge graph and OPC UA protocol. First, the knowledge and previous processing rules in the operation and maintenance field are summarized, the previous operation and maintenance fault event knowledge of workshop is extracted, the fault data in production is sorted out, the corresponding knowledge base is established, and the concept model of workshop operation and maintenance fault entity and relationship is constructed. Then, the operation and maintenance fault model data source is acquired, the data layer is built, and then the ontology, entity, relationship and attribute are perfected from bottom to top, and the knowledge graph is constructed. Further, based on the OPC UA protocol, the information model is abstracted into the software system, and the operation and maintenance fault information model is instantiated. The whole step is simple and clear, can be applied to various discrete manufacturing production systems, solves the fault handling problem in operation and maintenance scheduling, can express the whole content of operation and maintenance fault monitoring at the same time, and does not affect the subsequent production, and has great application value in the operation and maintenance field.

The application discloses a software application recommendation method based on user behavior information and speech information, and the method establishes a concept model by fusing the behavior information and the speech information, constructs a knowledge graph by combining heterogeneous user behavior and user speech, designs a meta-graph based on the concept model, connects the concepts in the concept model in the meta-graph, and finally performs meaningful walking on the nodes in the knowledge graph in the form of random walking guided by the meta-graph, so that a sequence capable of better representing the nodes is obtained. Through multiple walking, multiple meaningful sequences of the starting point of the node can be obtained, so that the neighborhood of the node is obtained. Through embedding of the walking result, the vector of the node can be obtained to represent the information of the node. Finally, through calculation on the vector, similar nodes can be recommended. The method is suitable for an application recommendation process considering the behavior information and the speech information of the user.

Improved methods and systems are provided for generating concept-based interpretations for a target model. Some embodiments relate to calculating metrics that quantify effects of concepts defined by a conceptual model on classification of a target model. This may include calculating an output of a similarity function applied to an output of the target model and an output of the conceptual model for sensor data in the evaluation set.

The invention relates to the field of teaching resource libraries, in particular to a multi-dimensional digital resource library of an intelligent teaching space and a construction method of the multi-dimensional digital resource library. The method comprises the steps of implanting a current management process and a current system situation of an application unit into an online virtual space; selecting a team cooperation mode with corresponding intensity; the management basis of the entity course space and the virtual course space is cooperatively optimized and adjusted; constructing a conceptual model and a composition domain model of the smart course space; constructing a digital resource model of the smart course space; the project party carries out delivery according to the digital resource model; carrying out curriculum team intelligent teaching maturity evaluation and selecting to start cooperation according to the maturity; and a multi-dimensional digital course teaching resource library is formed. By adopting the multi-dimensional digital resource library construction method of the intelligent teaching space, the intelligent course space can meet the differentiated requirements of content abundance and management flexibility of college courses and college teaching.