14results about How to "Efficient update" patented technology

This invention relates to the field of indoor geomagnetic positioning technology, specifically to a method for dynamic maintenance of geomagnetic fingerprint maps based on mobile robots. The method includes multimodal data acquisition and spatiotemporal alignment to establish a correspondence between sensor data and global map coordinates; constructing a cross-confidence mechanism using geomagnetic anomaly factors and visual verification factors, and accurately triggering map updates using a time decay accumulation model; identifying newly added magnetic objects and extracting their parameters, calculating the radius of influence of the disturbance field using a magnetic field disturbance model; and employing a region-growing local incremental update method, introducing a boundary smoothing factor to ensure map continuity. This invention achieves autonomous and efficient maintenance of geomagnetic fingerprint maps without requiring global rescanning or additional hardware, improving the stability of geomagnetic positioning for mobile robots. Simultaneously, the accurate triggering of updates through a dual-modal cross-confidence evaluation mechanism enhances the accuracy of geomagnetic fingerprint map updates.

The invention provides a pumped storage power station 5G + BIM intelligent interaction management system, and the system comprises a sensing layer which is used for collecting earthwork vehicle transportation data, dam rolling data, underground cavern construction data and monitoring data, and achieves the dynamic data updating of a BIM model through a 5G camera, a sensor and construction data; the network layer transmits dynamic data of the BIM model through a 5G private network, and allocates communication resources according to service requirements by adopting a network slicing strategy; the data layer is used for fusing dynamic data of the BIM model, including BIM geometric data, sensor real-time parameters and construction data, and constructing a dynamic digital twinborn database; and the application layer performs construction state early warning and construction scheduling based on design parameters and sensor parameters and a BIM model, generates a decision instruction through a deep learning algorithm, and realizes data deep fusion, network resource optimization and emergency capability improvement by fusing 5G high-reliability communication, BIM dynamic modeling and AI intelligent decision.

This application provides a data processing method and electronic device. The device identifies geological information by attribute recognition, determines multiple recognition events, and filters them by confidence level, converting them into data packets carrying adjustment actions. At the same time, it calculates the difference between each data packet and the 3D geological model to determine the transmission method, prioritizing the uploading of key geological changes. After receiving the data packets, the cloud accurately locates them in the corresponding target area in the overall model using spatial anchor points and binds them. However, the bound target area may be associated with multiple data packets with inconsistent update directions. Therefore, it is necessary to construct conflict vectors and determine conflict weights for the data packets corresponding to the target area. Then, based on the adjustment actions of each data packet, the conflict vectors, and the conflict weights, the adjustment method of the target area is determined and a local update is performed. This can obtain accurate and traceable incremental update results for the model, facilitating efficient, accurate, and traceable local updates of the 3D geological model under weak network conditions.

The application provides a 4D space-time field construction method and device based on neural field reconstruction, and relates to the technical field of data processing. The 4D space-time field construction method based on neural field reconstruction comprises the following steps: performing supervision information labeling on a plurality of three-dimensional coordinates in a to-be-processed 3D model to obtain a plurality of training data samples, thereby constructing a training data set; dividing a three-dimensional space into a plurality of cubic grids of the same size, each grid corresponding to a neural network inside, thereby constructing a block neural field model; training the block neural field model based on the training data set to obtain a target 4D space-time field; and updating the target 4D space-time field in response to local data update of the to-be-processed 3D model. Through block neural field modeling and a continuous learning mechanism, the application converts dynamic update of the 4D space-time field into an incremental inference problem of the neural network, thereby realizing efficient update of the 4D space-time field.

The invention relates to the technical field of network security, in particular to an eBPF-based access control method and device and electronic equipment, and is used for improving the efficiency and accuracy of IP black and white list access control. The method comprises the following steps: receiving target network feature information of a to-be-detected network data packet; according to a preset access control rule, performing matching query on the target network feature information through an eBPF program to obtain a matching result of the to-be-detected network data packet; the access control rule is predefined by the user space and transmitted to the kernel space; the access control rule comprises at least one of the following rules: a blacklist rule used for defining a first network feature information set forbidden to access, and a white list rule used for defining a second network feature information set allowed to access; the matching result represents a matching relationship between the network feature information and the access control rule; and performing corresponding access control on the to-be-detected network data packet through the eBPF program according to a matching result.

This invention relates to the field of network digital twin technology, specifically to a method for dynamic incremental update of network digital twin topology based on heterogeneous graph neural networks. The method includes the following steps: constructing a corresponding heterogeneous topology base graph based on the physical network; mapping devices and connections in the network to nodes and edges with type identifiers according to a preset node and edge type system; writing a feature field for each node; obtaining the current network digital twin topology graph; performing topology change event perception based on the heterogeneous topology base graph; mapping the collected topology change events to incremental change units; and obtaining the corresponding set of nodes in the affected domain according to the category and scope of the change events. This invention, by grouping by edge type and aggregating neighbor node information, can efficiently update a specific part of the network topology when the topology structure changes, without reconstructing the entire topology, thereby significantly improving the efficiency of network management.

The invention discloses an implementation method of sensor array wave beam response side lobe arbitrary null accurate control. The method comprises the following steps: firstly, constructing an array manifold according to related parameters of a sensor array, and selecting an expected null region; constructing an iterative formula of a beam pattern weighted vector in combination with the idea of accurate control of sensor array beam response; and finally, carrying out iterative solution on the weighted vector of the beam pattern to realize the design of the beam pattern. According to the method, an autocorrelation matrix formed by array manifolds corresponding to an expected null region is introduced into a target function of a CAPN beam former, so that effective minimization of beam output power of the region is realized; meanwhile, in combination with the design thought of sensor array beam response accurate control, beam response control and null region control are organically fused, and the precision of null region control is remarkably improved.

The present disclosure relates to a virtual resource updating method, device, equipment and storage medium. The method comprises: when a virtual resource transfer request in an asynchronous message queue meets a preset condition, sending the virtual resource transfer request to a hot message queue; obtaining a first to-be-transferred resource record and a second to-be-transferred resource record corresponding to a target account identifier; the first to-be-transferred resource record is generated based on a target virtual resource; the second to-be-transferred resource record is an unprocessed resource record in a historical period; based on the hot message queue, updating the virtual resource corresponding to the target account identifier according to the first to-be-transferred resource record and the second to-be-transferred resource record. The present disclosure realizes fast and efficient updating of the virtual resource of a hot account, reduces the updating delay of the virtual resource of the hot account, and also reduces the updating delay of the virtual resource of a non-hot account.

One or more embodiments of the present specification provide a data processing method, system, device and storage medium, the method is applied to a computing platform; a user-defined function corresponding to a machine learning task is deployed in the computing platform; wherein the user-defined function contains initialization logic and data processing logic corresponding to the machine learning task; the method comprises: obtaining to-be-processed data corresponding to the machine learning task; calling the initialization logic in the user-defined function to obtain a machine learning model corresponding to the machine learning task stored in a storage platform connected to the computing platform; further calling the data processing logic in the user-defined function to use the machine learning model to process the to-be-processed data, and storing the data processing result to a database connected to the computing platform.

The invention discloses a low-altitude networking of intelligence fine-grained group communication method and system based on predicate encryption, and belongs to the technical field of network security communication. The method comprises the four steps of system initialization, entity registration, secure communication and key updating. In a registration stage, a predicate key is split into two parts, a first key component is stored in an unmanned aerial vehicle, and a second key component containing a complex attribute coupling item is stored in a ground base station. And during communication, decryption is realized by utilizing a preset matching relationship between the attribute vector and the predicate vector, and point-to-point communication based on the anonymous attribute vector and group communication based on public attribute filling are supported. During key updating or cross-domain switching, the ground base station uses the stored components to undertake the first type of operation with relatively high calculation complexity, and the unmanned aerial vehicle can synthesize a new key only by executing the second type of operation with relatively low calculation complexity. According to the method, the calculation overhead of the unmanned aerial vehicle is effectively reduced, and the problems of difficulty in fine-grained group division and key management under dynamic networking are solved.

This invention belongs to the field of digital twin technology, specifically providing a bridge digital twin modeling and updating system and method driven by cluster learning and Kriging. The system includes: a data acquisition and processing module for obtaining performance characteristic information of the actual bridge structure; a digital twin model construction module for constructing a bridge digital twin model and processing the performance characteristic information of the simulated bridge structure; an objective function construction module for constructing a residual objective function and obtaining optimization variables and their parameter space based on the residual objective function; an optimization module for guiding the Kriging surrogate model to search for optimal parameters in the parameter space using a cluster optimization mechanism driven by multiple learning functions in parallel; and a model update module for updating the bridge digital twin model using the optimal parameters. This invention effectively improves the accuracy of bridge structure state identification and reduces model update costs, making it suitable for bridge performance prediction and operation and maintenance management under complex working conditions.

The invention discloses a database construction method and device, a database processing method and device, an information reporting method and device, a storage medium, a program product and computer equipment. A main table corresponding to a queried object is determined; obtaining a plurality of intermediate tables based on identification information related to the inquired object; performing association processing on the plurality of intermediate tables to obtain at least one service intermediate table; and configuring a preset distributed file system into an intermediate database model based on the main table and the at least one service intermediate table, thereby improving the efficiency of subsequent updating and / or query of the constructed database, and realizing efficient updating and / or output of data.

This invention provides a virtual terminal incremental interface rendering system, method, and terminal based on the ISOBUS standard. It first calculates the new hash value of each attribute based on interface object attribute update data extracted from ISOBUS messages, and compares this new hash value with the corresponding attribute hash value cached by the object cache management module to accurately identify the actual changed attributes. Based on this, it determines the update method and generates an update data packet embedding the current version number. Then, considering the visibility of each interface object, user attention, and update frequency, it calculates the rendering priority, combines the target frame rate and rendering time budget, selects the set of objects to be rendered in the current frame, and performs incremental rendering. This invention achieves efficient incremental updates through hash change detection, differential data packet generation, and intelligent rendering scheduling technologies, effectively reducing data transmission volume, improving frame rate, and reducing latency, demonstrating significant performance advantages and broad application prospects.