6 results about "Confidence set" patented technology

The present application relates to the field of artificial intelligence tracking technology, and discloses a pedestrian trajectory tracking method based on artificial intelligence.The method comprises collecting multi-source sensor pedestrian movement feature data stream, extracting initial trajectory key points as tracking reference points;dividing associated historical position data into a high-confidence trajectory segment set and a to-be-verified trajectory segment set, and discarding the to-be-verified set;arranging the high-confidence set in descending order according to the number of trajectory points, selecting the first several segments as optimal trajectory segments, and calculating the proportion;comparing the proportion with a dynamic screening threshold, outputting the high-confidence set as an initial tracking result, or outputting a trajectory checking instruction generated by comparing trajectory data;in response to the checking instruction, dividing the space grid of the optimal trajectory segment, and outputting an optimization instruction in combination with historical trajectory features;updating the reference points based on the optimization instruction, and screening and outputting secondary divided trajectory data;finally, obtaining parameters to generate a tracking efficiency evaluation coefficient, and starting a parameter correction strategy when the coefficient is lower than an optimization threshold.

This invention discloses an intelligent warehouse automated inventory management method and system, relating to the field of warehouse management technology. The method includes: deploying automatic identification tags at each storage location in the warehouse and constructing a digital map of the warehouse; a mobile inventory device collecting tag signals from the automatically identified tags at the current location and the real-time positioning coordinates of the inventory device itself; filtering all storage locations within a preset radius centered on the current location of the inventory device; determining the spatial association and attribution of the candidate storage location set based on the tag signals and real-time positioning coordinates to obtain a storage location attribution confidence set; performing optimal matching based on the storage location attribution confidence set to obtain the tag identification result; and updating the inventory data based on the tag identification result. This invention effectively suppresses interference caused by multipath reflection of radio frequency signals and coupling of signals from adjacent storage locations in dense metal environments through multi-constraint verification in the spatial dimension, significantly improving the accuracy of storage location identification and the reliability of inventory data while ensuring real-time performance.

The embodiment of the application provides a device safety risk identification method and system based on continuous interaction of mine agents, after the mine agent receives and analyzes device abnormal natural language description, calls analysis multi-source time sequence signal flow, outputs an initial fault hypothesis set and an initial fault confidence set, according to the confidence deviation of the initial fault confidence set relative to a preset confidence threshold, constructs a fault hypothesis space convergence strategy of the initial fault hypothesis set to call multi-source compensation signal flow and iteratively update fault root cause, until the updated fault confidence set meets the confidence threshold, and outputs a structured device fault diagnosis report. The problems that the existing mine device fault diagnosis exists cross-monitoring system data island and relies on artificial experience, which leads to deviation of fault diagnosis and delay of diagnosis result feedback response are solved. The mine device fault diagnosis achieves a second-level response, completely eliminates the artificial experience blind area and cross-system data island, and greatly reduces the operation and maintenance cost.

The present application relates to the field of computer information processing, and particularly relates to a multi-source heterogeneous knowledge graph construction method and system. The method comprises the following steps: accessing ancient books, clinical literature, and data of traditional Chinese medicine, drugs and disease databases, and forming an entity candidate set after field mapping extraction; calculating the name similarity, attribute similarity and semantic vector similarity of the entity candidate set, and inputting the multiple types of similarity into a fusion network to generate an entity alignment mapping table; constructing a remote supervision annotation set and training a relationship classification model, driving expert annotation incremental update by model uncertainty, and outputting a relationship triple set and a corresponding relationship confidence set; finally forming a three-layer heterogeneous graph structure connected by syndrome type, disease, prescription and drug components, and writing into a graph database to generate a knowledge graph database. The present application realizes unified modeling of entity alignment, relationship extraction and relationship strength quantification in multi-source heterogeneous data, and improves the structural consistency of the knowledge graph construction process.

This invention discloses a lane line tracking method, apparatus, terminal device, and storage medium. The method includes: acquiring a current set of lane lines and a set of historical lane lines corresponding to each current lane line; performing a lane line confidence subset acquisition action on each historical lane line set to obtain a lane line confidence set; and obtaining a lane line tracking result by combining the current set of lane lines with the historical set of lane lines based on the lane line confidence set. The lane line confidence subset acquisition action includes: for any current lane line, acquiring a set of distances between matching sampling points and a set of angles between matching sampling points for each historical lane line, based on the current lane line and each historical lane line; obtaining a lane line distance confidence based on the set of distances between matching sampling points; obtaining a lane line angle confidence based on the set of angles between matching sampling points; and obtaining a lane line confidence subset based on the lane line distance confidence and the lane line angle confidence to improve the accuracy of lane line tracking.

The application discloses a vehicle longitudinal interaction intention estimation method, an electronic device and a storage medium, and belongs to the technical field of intelligent driving. The method comprises the following steps: acquiring original observation data of surrounding traffic participants of a vehicle, and fusing state information of each traffic participant; screening a target traffic participant having a longitudinal interaction relationship with the vehicle; constructing a target intention prior distribution matched with a current traffic scene based on historical longitudinal behavior data of the target traffic participant; determining an observation likelihood for each type of longitudinal interaction intention based on the state information of the target traffic participant; determining a target posterior probability corresponding to each type of longitudinal interaction intention through a hierarchical Bayesian model based on the target intention prior distribution and the observation likelihood; and generating an intention confidence set based on the target posterior probability corresponding to each type of longitudinal interaction intention, so as to be used for vehicle behavior decision. The application improves the stability and reliability of the vehicle in estimating the intention of the surrounding traffic participants in the longitudinal interaction scene.