3 results about "Statistical cluster" patented technology

The application discloses a kind of automatic driving data processing method, system and equipment. Among them, the processing method of automatic driving data includes: for each automatic driving related data, the corresponding relationship of automatic driving collection data and event is established;Event is synchronized to work order system, to create the work order of the event by the work order system;The event is analyzed by the work order, to carry out label annotation;When the state change of work order is monitored, the structured association relationship of label and the event is established, and the structured association relationship is written in association table, to complete the label structuring of the event.Using the present application, the data processing efficiency is improved, the repetitive operation of manual participation is reduced, the speed of problem discovery to data available is accelerated, the analysis result can be accurately fed back to data through automatic mapping of data and event, so that label can directly participate in query, statistics, clustering and data mining, support large-scale analysis.

The invention relates to the technical field of civil engineering nondestructive testing, and discloses a method for detecting internal defects of a concrete structure. An excitation source and multiple sound pressure sensors are arranged on the surface of concrete, after sound velocity is calibrated in multiple paths in an intact area, a sound pressure sequence of unified sampling is obtained through unit impact excitation, a failure channel is removed, and maximum time delay is extracted from discrete cross correlation through any sensor and converted into an equivalent propagation path difference matrix. The method comprises the following steps: dispersing a volume to be detected into voxels, constructing a propagation contribution function in combination with each voxel and a sensor geometric path, establishing an optimization model with minimum residual error and sparse constraint, carrying out sparse reconstruction and statistical clustering on voxel impedance equivalent path area contribution, automatically identifying and quantifying positions, shapes and sudden change intensity of internal defects, and carrying out quantitative analysis. Errors caused by sound velocity heterogeneity are effectively suppressed, and imaging precision, reliability and automation level are improved.

The application provides a network abnormal flow intelligence construction method and device based on a knowledge graph, which comprises the following steps: constructing an initial knowledge graph based on static information, dividing features based on dynamic information to obtain statistical features and structured features; performing clustering analysis on the statistical features based on density-guided bisection splitting clustering to obtain statistical clusters, and performing clustering analysis on the structured features based on quality density projection clustering to obtain structured clusters and outliers; performing consensus fusion based on the statistical clusters, the structured clusters and the outliers to obtain feature consensus results, mapping entities corresponding to the dynamic information to the initial knowledge graph based on the feature consensus results to perform dynamic completion, and obtaining a completed knowledge graph; and converting context subgraphs retrieved in the completed knowledge graph with abnormal behavior events as the center into context information and inputting the context information into an AI model to obtain abnormal flow intelligence. The application improves the attack tracing efficiency and decision accuracy for advanced persistent threats.