5 results about "The Map Library" patented technology

This invention relates to user data management technology in the financial industry, and discloses a method for predicting the permanent residence of customers. The method includes: extracting latitude and longitude information and corresponding time-series information from the customer's embedded data; performing address matching on the latitude and longitude information using a pre-set map library to obtain address information, and extracting location features from the address information; classifying the address information according to the time-series information and location features to obtain a first address dataset; performing clustering operations on the latitude and longitude information based on the first address dataset to obtain a second address dataset, and filtering out location center data from the second address dataset; updating historical location data based on the location center data to obtain the customer's permanent residence. Furthermore, this invention also relates to blockchain technology, where customer historical data can be stored on blockchain nodes. This invention also proposes a device, electronic device, and storage medium for predicting the permanent residence of customers. This invention can improve the accuracy of predicting the permanent residence of financial and insurance users.

The invention relates to a dangerous key scene generation method and system based on big language model retrieval enhancement, and belongs to the technical field of automatic driving simulation testing, and the method comprises the following steps: constructing a scene knowledge base and a trigger condition base based on real traffic accident data; receiving a natural language function test requirement, extracting matched real accident features by using a retrieval enhancement technology, and generating a structured hierarchical scene description; comparing the scene static elements with a pre-labeled map library by adopting a mixed thinking chain compiling strategy with map matching priority; and according to a comparison result, adaptively selecting and multiplexing an existing map file and only generating a dynamic script, or simultaneously generating a static map file and the dynamic script, and finally outputting an executable simulation code. According to the method, a hybrid compiling framework with dynamic and static separation is provided, grammar errors generated by complex road network codes are effectively avoided, and the compilable rate and simulation fidelity of OpenDRIVE and OpenSCENARIO codes are greatly improved.

The invention relates to the technical field of cartoon material library construction, and discloses a method and system for realizing cartoon material atlas library construction based on big data, and the method comprises the steps: collecting multi-element cartoon materials based on a big data technology, the multi-element cartoon materials comprise an image sequence, a structured text and unstructured audio data, and extracting image features; performing triple structure conversion on the structured text, and performing animation semantic assignment to extract text features; performing feature alignment on the audio features, the image features and the text features to construct a three-dimensional incidence matrix; and decomposing the three-dimensional incidence matrix into a multi-factor matrix, calculating the scene co-occurrence frequency of each factor in the multi-factor matrix to analyze the correlation weight of the factors in the multi-factor matrix, and constructing the map library of the multi-element animation material based on the multi-factor matrix and the correlation weight. According to the invention, the material collaboration degree of the animation map library can be improved.

The present invention relates to a screen door control method supporting both coupling and a baggage carriage, a device, and a medium. The method includes: S1, calculating data of a safe passenger boarding and alighting area in an onboard electronic map library based on train running rules and train formations allowed for online running; S2, merging, by an interlocking system based on the train running rules and the train formations allowed for online running, same opening codes for actually opening screen doors in data logic; S3, calculating, by an onboard controller, a screen door opening code based on a current actual train formation, a baggage carriage condition, and data of a safe passenger boarding and alighting area in which the current train formation is located; and S4, driving, by the interlocking system, a corresponding screen door to be opened. Compared with the prior art, the present invention has advantages of supporting an operation manner of replacing a first carriage at a head or tail of different train formations with a baggage carriage, and the like.

Embodiments of the present specification provide a map matching method and device and a storage medium. The method comprises: acquiring a to-be-matched map; inputting the to-be-matched map into an image segmentation model to obtain a plurality of image segmentation mask graphs; determining, from the plurality of image segmentation mask graphs, a plurality of target mask graphs greater than a threshold value; performing positive and negative binaryzation processing on each target mask graph to obtain a positive and negative binaryzation mask graph; for each standard map in a preset standard map library, acquiring a standard map mask graph and a size of the standard map mask graph; generating a new positive and negative binaryzation mask graph of each target mask graph according to the standard map mask graph and the size; matching the generated new positive and negative binaryzation mask graph with the standard map mask graph based on an image matching model to respectively output a point pair of each target mask graph and the standard map mask graph; and determining a standard map matched with the to-be-matched map according to the most point pairs. The present application can realize intelligent matching of maps.