11 results about "Conceptual model" patented technology

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.

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.

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.

The invention discloses a stratigraphic analysis method based on tectonic landform dynamics and stratigraphic forward modeling, and the method comprises the steps: obtaining geological information of a target region, constructing a regional geological conceptual model, and determining key input parameters through the regional geological conceptual model; dynamic forward modeling simulation of the tectonic landform is executed, a basin-mountain ancient landform quantitative model is established based on the key input parameters, and rationality analysis is carried out; exporting quantitative geological parameters based on the pot-mountain ancient landform quantitative model; stratum deposition process quantitative simulation is executed, the quantitative geological parameters serve as quantitative input parameters, a sedimentary stratum quantitative model is established, and rationality analysis is carried out; and based on the sedimentary strata quantitative model, quantitatively representing sedimentary strata development characteristics, and predicting dominant sand body distribution in the target area. The method has the effect of improving the accuracy and applicability of the stratum analysis process.

This invention discloses a dynamic prediction method for tunnel water inflow, belonging to the fields of tunnel engineering and hydrogeology. The method first constructs an initial hydrogeological conceptual model; then establishes a dynamic database integrating geological, geophysical, monitoring, and meteorological data; furthermore, it establishes a dynamically coupled prediction model that combines a physical numerical model and a machine learning proxy model; utilizing newly revealed data during construction, it dynamically inverts and updates model parameters through a data assimilation algorithm; the updated model is then used for probabilistic water inflow prediction and risk level classification; finally, the results are visualized and a feedback loop is formed. This invention, through a dynamic update mechanism, enables the prediction model to continuously approximate real geological conditions, solving the problems of low accuracy and poor adaptability of traditional static prediction methods, and significantly improving the ability of tunnel construction to cope with water inflow risks.

The application discloses a task meta-model construction method for general combat process, comprising the following steps: S1, constructing a combat concept model by using combat scene logical entities, data and models; S2, constructing a capability concept model; S3, constructing a mission task-capability matrix model; S4, constructing a combat activity resolution tree and a combat activity model; S5, constructing a mapping matrix model of capabilities and combat activities; and S6, integrating the combat concept model, the capability concept model, the mission task-capability matrix model, the combat activity model and the mapping matrix model established in steps S1-S5 to generate a global digital dictionary, i.e., obtaining a task meta-model. The application further discloses a task meta-model database and a construction device. The application can solve the problems that the existing combat system is difficult to model and describe, the combat task model construction efficiency is low, and the combat task model is difficult to verify and reuse, and realizes the rapid combination, verification and reuse of the combat task model architecture.

This invention discloses a ternary fusion knowledge processing system and method based on ontology, graph database, and large language model, comprising: an ontology construction module constructing a formal conceptual model; a knowledge graph construction module extracting instance data from multi-source heterogeneous data and storing it in a graph database based on the conceptual model to form knowledge graph instances; a large language model interaction module receiving natural language queries and parsing user intent; a hybrid reasoning engine invoking rule-based reasoning, graph algorithm mining, and large language model reasoning in parallel according to user intent, processing the conceptual model, knowledge graph instances, and queries, and fusion results to output a comprehensive conclusion; an interpretable report generation module recording the reasoning basis and generating an interpretable report; and a dynamic evolution module updating the conceptual model and knowledge graph instances based on newly accessed event data. This invention integrates symbolic reasoning and neural networks, improving the interpretability, accuracy, and dynamic evolution capability of reasoning.

This invention discloses an automatic identification method for carbonate reservoir patterns, comprising the following steps: establishing typical reservoir patterns; establishing a numerical simulation conceptual model based on the typical reservoir patterns; simulating the development process of different conceptual models and extracting production dynamic information; and constructing a fractured-vuggy reservoir pattern inversion model using a deep learning algorithm. This invention employs the aforementioned automatic identification method for carbonate reservoir patterns, using a deep learning algorithm to quickly and accurately identify fractured-vuggy reservoir patterns. It overcomes the shortcomings of time-consuming, costly, and highly specialized geostatistical inversion methods, avoids the influence of subjective human factors, significantly improves economic efficiency, and greatly reduces testing time costs.

The present disclosure discloses systems and methods for generating application programming interface (API) schema by using ontological constructs. The system may receive an ontology file comprising a domain-specific conceptual model, wherein the domain-specific conceptual model comprises ontological entities and corresponding relationship between ontological entities. Further, a schema generation strategy may be determined from at least one of a simple strategy, a nearest neighbor strategy, and a shortest path strategy for the received ontology file based on a user requirement and the received ontology file. Moreover, the system may generate an ontological data structure for the received ontology file based on the determined schema generation strategy. Thereafter, the system may transform the generated ontological data structure into a graphical schema structure by mapping each of the ontological entities to corresponding graphical entities. Furthermore, the transformed graphical schema structure may be serialized output the generated graphical schema file as an API.

The invention discloses a basin stand and a design optimization method thereof, and relates to the technical field of electro-acoustic conversion. The design optimization method of the basin stand comprises the following steps: creating a conceptual model of an assembly component, wherein the assembly component comprises the basin stand in an assembly state, a magnetic circuit unit and a fastener; carrying out differentiated gridding division on the assembly component to obtain a gridding model; taking the design area of the basin stand as a topological optimization area, and carrying out primary topological optimization on the topological optimization area in the gridding model to obtain a primary optimization model; creating a three-dimensional model for the assembly component to obtain a preliminary model of the assembly component; performing secondary topological optimization on the topological optimization region, and combining the topological optimization region with a non-design region in the conceptual model to obtain a secondary optimization model of the assembly component; and performing structure simulation on the secondary optimization model to obtain a simulation result. According to the method, the optimal optimization balance scheme of the weight and the rigidity of the basin stand can be effectively, quickly and accurately found, and the design efficiency is improved.