4 results about "Automatic inference" patented technology

The application discloses a low-code platform variable type automatic inference method and device. The method comprises the following steps: screening a variable with an automatic type identifier in a low-code platform to obtain a target variable; obtaining a default value inference result based on a type inference rule; traversing a structured model corresponding to a business logic and declaration information to obtain a node assignment inference result; obtaining a dependency relationship inference result through a multi-round iteration strategy recursive derivation; integrating the default value inference result, the node assignment inference result and the dependency relationship inference result to determine an initial type of the target variable; storing the initial type based on inference trace information and realizing change notification to finally obtain a target type. Through multi-stage inference, expression type calculation, chain dependency processing and other designs, the application does not need to manually specify the type, supports complex scene inference, maintains type safety, reduces use and maintenance costs, and improves the development efficiency and ease of use of the low-code platform.

This invention belongs to the field of indoor positioning technology and discloses a method and system for constructing and maintaining a long-term WiFi fingerprint map. The method includes: deploying reference points at intervals indoors and collecting WiFi signal strength (RSS) data, coordinates, and timestamps; automatically inferring access point (AP) coordinates based on signal backpropagation and maximum a posteriori probability (MAP) estimation, combined with a path loss model; decomposing the RSS into the mean path loss and residual terms, and modeling the residuals using spatiotemporal Gaussian process regression (GPR); incrementally updating the fingerprint map using an induced point set based on a sparse variational Gaussian process (SVGP); and performing terminal positioning based on the updated map. The system includes five functional units. This invention achieves automatic AP location inference, resistance to dynamic environmental interference, and low-cost long-term map maintenance, improving positioning accuracy and stability.

An operating system state root cause inference method, device, equipment, medium and product are provided. The operating system state root cause inference method comprises: obtaining a structured event with a predefined format in an operating system kernel; determining whether the operating system is abnormally stopped; in response to determining that the operating system is abnormally stopped, obtaining, by a user state service, state information of the operating system based on the structured event obtained in an operating system running cycle before abnormal stop through a predetermined state machine; and obtaining, by the user state service, an abnormal stop root cause based on the state information of the operating system through the predetermined state machine. Through the present disclosure, the structured degree and machine analyzability of operating system abnormal stop analysis can be significantly improved, different fault types can be more accurately distinguished, kernel invasiveness and maintenance costs can be reduced, the implementability of rule iteration and product deployment can be improved, and automatic inference and large-scale review can be realized.

This invention discloses an automatic inference code generation method and system for model deployment, belonging to the field of model deployment technology. The method includes: extracting model information from intermediate files of the model to be deployed; defining variables for each operator; generating an output variable name index table and a weight variable name index table; determining the input variable names for each operator and generating an input variable name index table according to the order of the operators; generating a pad value index table, an input size index table, and an output size index table for actual inference; for each operator, extracting the corresponding API from an API library; filling the API parameters according to the output variable name index table, weight variable name index table, input size index table, output size index table, input variable name index table, and pad value index table to generate the corresponding operator's API call; and combining the API calls of each operator to obtain the required inference code. This solution provides an automatic inference code generation method for AI chips, simplifying the model deployment process.