4 results about "Modelling methods" patented technology

The application discloses a risk control modeling method and device based on a large model agent and equipment, comprising: receiving a natural language modeling instruction input by a user, and inputting the natural language modeling instruction into a fine-tuned intention recognition large model for analysis, and outputting a corresponding structured function call instruction sequence; inputting the structured function call instruction sequence into a risk control modeling agent to generate a corresponding task execution plan; selecting an execution path according to the task type of each function call instruction in the task execution plan through the risk control modeling agent; calling a corresponding remote tool service or a local function function to execute the current task according to the execution path, and returning an execution result; receiving and integrating the execution result of each function call instruction through the risk control modeling agent, and determining and executing subsequent operations according to the obtained integrated result, wherein the subsequent operations include continuing to execute the next function call instruction, initiating an interactive inquiry to the user or outputting a final risk control modeling result.

This invention provides an intelligent modeling method and system for steel performance prediction based on LLM (Liquidity Management Model). The system includes: receiving and parsing user instructions through a natural language understanding module to generate a standardized task description; automatically generating or matching an automated model building process based on the task description through a planning and execution module; providing decision support based on a knowledge base through a knowledge recommendation module during task planning or execution; and automatically scheduling functional modules such as data access, feature engineering, and model building to complete the modeling task and output the results, based on the recommended information, through the planning and execution module. The system accordingly includes various functional modules implementing the above method. This application achieves end-to-end automated modeling through natural language interaction, automated task planning, and intelligent knowledge recommendation, significantly improving modeling efficiency, lowering the technical threshold, and enhancing model quality and versatility.

The application relates to the technical field of production line modeling, and proposes a production line parameter change propagation evolution modeling method based on a hypergraph, which comprises the following steps: constructing production line parameters and a correlation relationship into an initial hypergraph model containing nodes, hyperedges, membership relationships, attributes and constraint functions. Then, the system receives a change operation instruction for the nodes or the hyperedges, and executes corresponding atomic or composite operations according to the instruction type, and dynamically updates the topological structure and the membership relationship of the hypergraph. After the change is executed, the system automatically locates the affected area, triggers an attribute recalculation mechanism driven by the constraint function, realizes the automatic propagation and consistency maintenance of the parameter change in the hypergraph model, and finally outputs the production line parameter model in the current state. The application solves the technical problems of high parameter coupling degree and complex change propagation link in a complex production line, and significantly improves the modeling accuracy and evolution efficiency in the parameter change process.