4 results about "Applying knowledge" patented technology

The application discloses a kind of based on IC level EMC data assets measure quantification evaluation method, comprising: constructing read-only measure sensitivity database, extracting the quantification contribution value of target IC from IC level EMC data assets as measure sensitivity data;According to design mode or diagnosis mode, measure sensitivity data is called to predict measure effect and generate optimization scheme;Verification data is stored to user local application knowledge base, and local correction coefficient is generated for subsequent secondary correction.The present application converts EMC optimization from experience trial and error to quantitative calculation, supports pre-design reference and diagnosis rectification, and realizes user EMC design knowledge self-growth.

This invention discloses a method, apparatus, electronic device, and storage medium for content detection of a model-associated knowledge base. The method includes: responding to a content detection request for the associated knowledge base of a target model, acquiring a target associated knowledge base for the target model, wherein the target associated knowledge base includes at least a test knowledge base and a scenario application knowledge base, the test knowledge base storing preset security detection knowledge, and the scenario application knowledge base storing industry security content; determining candidate risk content in the target associated knowledge base based on target prompt information and the target model, and generating test data based on the candidate risk content; testing the target associated knowledge base based on the test data, candidate risk content, and the target model, and calibrating the corresponding target risk content in the target associated knowledge base based on the test results, thereby achieving accurate risk mining across industry scenarios and dynamic optimization of knowledge base content, significantly improving the security detection capability and generalization of the target model.

The application discloses a large model-based financial data analysis method and system and a medium, mainly relates to the technical field of financial data analysis, and is used to solve the problem of the isolation of each module in the prior art architecture, that is, the lack of a cooperative mechanism among the three links of data query, rule application and knowledge calling. The method comprises the following steps: acquiring initial financial problem data, disassembling the initial financial problem data into a financial problem string, a rule problem string and a query problem string; obtaining corresponding financial knowledge; obtaining corresponding financial early warning rules; integrating all corresponding query sub-SQL into a final query SQL by a large model; executing the final query SQL by an execution engine to obtain a query result; taking the financial knowledge, the financial early warning rules and the query result as input parameters of a financial data summary function, and then obtaining a prompt word composed of the financial knowledge, the financial early warning rules and the query result; inputting the prompt word into the large model to obtain a returned summary string.

This invention discloses a few-sample dynamic modeling method for composite material composite structures of electric aircraft based on attention meta-learning, including the following steps: Step 1: The dataset used comes from vibration experiments conducted on composite laminated wing box structures, composite laminated air beam structures, and composite conical-cylindrical composite shells under different temperature conditions. Given limited data, various composite material structures and ambient temperatures are divided into independent task samples. Each task includes vibration test data of the structure at its respective temperature. The data is divided into a meta-training set and a meta-test set. This invention relates to the field of dynamic modeling technology, innovatively integrating meta-learning with dynamic modeling of composite material composite structures of electric aircraft. The AMLT model can utilize MAML's rapid task adaptability and multi-task learning capabilities to quickly transfer and apply knowledge to new tasks, resulting in higher adaptability and generalization ability when facing new tasks.