14 results about "Domain space" patented technology

An access point computes, for user devices in each group of a plurality of groups of user devices, a plurality of start times of future enhanced data privacy (EDP) epochs during which identifiers from the user devices in each group are to be rotated. Based on the plurality of start times, it is determined that transitory periods will occur at a same time for at least a threshold number of groups of the plurality of groups of user devices. The AP transmits a message to user devices in at least one group of the at least a threshold number of groups instructing the user devices to perform one or more actions to prevent the transitory periods from occurring at the same time.

The invention discloses a cross-domain multi-modal dynamic reasoning and generating method and system for space sensing equipment linkage, a terminal and a storage medium, and the method comprises the steps: carrying out the weighted fusion and space-time alignment of multi-source heterogeneous equipment sensing data, and forming a cross-domain space sensing data flow with a unified reference; based on real-time spatial topology and business constraints, dynamically dividing semantic collaboration areas and establishing visual mapping; for each region, fusing spatial semantics, text and visual information, and generating a region cooperative control strategy; rendering the visual content in parallel according to the mapping relation and synchronizing the equipment state; and outputting a result through area-level quality reflection evaluation, if all the data reach the standard, carrying out protocol adaptation and linkage output, otherwise, starting a local regeneration protocol for an area which does not reach the standard, re-calibrating data, updating a strategy and rendering. According to the invention, multi-device collaborative millisecond response, cross-protocol non-stop adaptation and anomaly localization repair are realized.

The present application relates to the technical field of wind turbine operation and maintenance, and particularly relates to a wind turbine defect cross-domain guidance collaborative detection method and system, comprising: acquiring global scanning data of wind turbine blades and tower drums of non-stop wind turbines after a drone is calibrated by cross-domain space-time synchronization; acquiring near-domain reference data collected by a climbing drum robot at a preset reference position of the tower drum; taking the near-domain reference data as an anchor point, splicing the global scanning data to determine a defect suspected area and a spatial position; scheduling the climbing drum robot to a target site for spot detection, and acquiring multi-modal detection data; and combining real-time wind field conditions and unit operation parameters to perform interference compensation on the multi-modal data to obtain defect characteristic information. Through the present application, space-time unification and collaboration of the detection data of the drone and the climbing drum robot are realized, and the reliability of wind turbine defect identification and positioning is improved.

The application relates to the technical field of hydrology and water resources prediction, and discloses a large model driven hydrology model parameter automatic calibration method, which comprises the following steps: calling a large language model to analyze natural language demand text and basin model metadata, constructing a topological feasible domain space of high-dimensional physical parameters and a calibration strategy configuration file; performing adaptive Box-Cox transformation on original observation data to generate a stationary data sequence and cutting the stationary data sequence into a calibration set and a verification set; screening high-sensitivity parameters, extracting constrained physical parameters, performing topological transformation based on simplex mapping to generate an initial parameter vector population, performing concurrent optimization calculation on the calibration set to output parameter posterior samples; calling a Gaussian mixture clustering algorithm to cluster the parameter posterior samples to generate a structured feedback object containing a state field; and recalculating or outputting a final delivery object of the model according to the state field. The application narrows the initial search space range and quantifies the phenomenon that different parameters have the same effect.

This application provides an asset visualization display method, device, electronic device, medium, and program product, which can be applied to the fields of big data technology, spatial information technology, and fintech. The method includes: acquiring asset information of multiple assets; obtaining asset hierarchy relationship information based on the relationships between the asset information; acquiring business identification information of multiple business domains; associating the business identification information with corresponding system service entry addresses to obtain business entry association information; acquiring asset operation relationship information; determining target assets participating in the operation of each business domain based on the business entry association information and the asset operation relationship information; associating the business identification information with the asset identification of the corresponding target asset to obtain business asset association information; and obtaining asset layered display information based on the asset hierarchy relationship information and the business asset association information.

The invention discloses a radar echo extrapolation method integrating physical guidance and a diffusion coupling mechanism, and relates to the technical field of meteorological short-term and imminent forecast. The method comprises the following steps: firstly, coding radar echo data by using a physical guidance network, capturing long-distance space-time dependence through a multi-scale gating axial block, and generating a preliminary prediction sequence with macroscopic physical consistency in combination with a multi-domain space-time evolution module and an explicit physical advection guidance mechanism; and then, adopting a channel decoupling and cascade diffusion strategy, taking the preliminary prediction sequence as a physical prior skeleton, extracting guide features by using a double-flow spatio-temporal context network, and executing reverse iteration denoising and refined texture repair through a diffusion model. According to the method, the physical guidance composite loss function is introduced, the problems of image blurring and physical evolution logic deficiency existing in a traditional method are effectively relieved, and the forecasting precision and image fidelity of severe convective weather are improved.

An access point computes, for user devices in each group of a plurality of groups of user devices, a plurality of start times of future enhanced data privacy (EDP) epochs during which identifiers from the user devices in each group are to be rotated. Based on the plurality of start times, it is determined that transitory periods will occur at a same time for at least a threshold number of groups of the plurality of groups of user devices. The AP transmits a message to user devices in at least one group of the at least a threshold number of groups instructing the user devices to perform one or more actions to prevent the transitory periods from occurring at the same time.

This application provides a method and apparatus for forwarding packets, relating to the field of communication technology. The method is applied to an ingress PE node and includes: receiving a first Internet Protocol (IP) packet, the first IP packet supporting Explicit Congestion Notification (ECN); determining a first Multiprotocol Label Switching (MPLS) packet based on the first IP packet, the first MPLS Network Action (MNA) in the first MPLS packet including a first ECN field; and forwarding the first MPLS packet. The method in this application embodiment can avoid conflicts between MPLS packets carrying ECN tags and the DiffServ domain space.

The embodiment of the invention provides a GPU cache structure, a resource allocation method and device, electronic equipment and a storage medium. The GPU cache structure comprises a private domain space associated with a specified task and a shared space of full tasks. According to the embodiment of the invention, different tasks can be isolated and mutual influence can be avoided through the private domain space associated with the specified task, and different tasks can be used and GPU resources can be utilized to the maximum extent through the shared space of the total tasks, so that resource fragmentation caused by different tasks can be reduced, and the resource utilization rate can be improved.

The embodiment of the present specification provides a secret sharing packaging method and device. A plurality of participants respectively encode vectors formed by secret sharing of k data owned by each participant in a specified domain space to obtain first domain elements owned by each participant, wherein the first domain elements have a data structure satisfying additive homomorphism. Then, through the first data interaction based on secure multi-party computation between the plurality of participants, the secret sharing addition operation is performed based on the first domain elements owned by each participant, so that the plurality of participants respectively obtain: the secret sharing of the first sum value of the first domain elements owned by each participant. The secret sharing of the first sum value is used as the secret sharing of the second domain element obtained by encoding the vector formed by k data in the specified domain space.

The application discloses a remote sensing image change detection method and device based on a Mamba-based region-space-semantic channel modeling, and the method comprises the following steps: inputting an obtained remote sensing image dataset into a constructed Mamba-based region perception, dual-domain space and semantic channel modeling network (S3Mamba) for training, obtaining a trained S3Mamba and saving the same; inputting a remote sensing image to be processed; and performing prediction on the remote sensing image to be processed by using the trained S3Mamba, so as to obtain a dual-time-phase change prediction map. The application improves the precision and performance of remote sensing image change detection by means of a three-way collaborative modeling mechanism coupling design.

The invention relates to the technical field of electric digital data processing, and discloses an infrastructure material supply and demand matching method and system based on multi-objective optimization, and the method comprises the steps: collecting and standardizing the fragmented supply and demand information of cross-domain space-time; constructing a space-time constraint and business rule model; a multi-objective optimization model with the minimum total cost, the highest time satisfaction degree and the maximum matching stability as the core is established; an improved NSGA-III algorithm is adopted to solve and obtain a Pareto optimal solution set; a decision maker is assisted in selecting and executing a final matching scheme in a man-machine interaction mode; the corresponding system comprises a data integration module, a knowledge base module, an optimization engine module, a decision support module, a scheduling feedback module and the like. Through combination of a resource optimization algorithm and an intelligent decision-making process, the problem of low matching efficiency caused by cross-region and cross-time information fragmentation is effectively solved, the matching precision can be remarkably improved by more than 30%, the matching period is shortened by more than 50%, and accurate, efficient and intelligent scheduling of capital construction materials is realized.

The application discloses a shield tunneling parameter prediction method based on multi-source domain transfer learning, comprising the following steps: obtaining real-time tunneling data of a target project, and loading pre-stored multi-source domain tunneling data set; performing geological field division and steady-state feature extraction to obtain target domain space-time feature sequence and multi-source domain space-time feature sequence; inputting the same into a pre-trained space-time attention feature extraction model to extract corresponding domain-invariant feature representation; generating a transferability evaluation weight corresponding to each sample in the multi-source domain according to a pre-constructed transferability evaluation strategy; processing the target domain space-time feature sequence by using a pre-trained regression prediction model, dynamically adjusting the space-time attention feature extraction model, and outputting a target domain tunneling parameter prediction value. The application realizes dynamic self-adaptive transfer of shield tunneling samples, effectively suppresses the negative transfer risk caused by stratum mutation, and improves the generalization prediction accuracy and construction safety of the model under complex and variable working conditions.

The application provides a multi-domain space fusion knowledge graph embedding method, system, device and medium, and relates to the field of knowledge graph embedding.The method comprises the following steps: (1) constructing a training set; (2) performing initialization processing on the training set; (3) performing sampling processing on the training set to construct a training subset; (4) importing the training subset into a knowledge graph embedding model to obtain triple scores and attention scores in different number domain spaces; (5) iteratively training the knowledge graph embedding model using the triple scores and attention scores in different number domain spaces until convergence; and (6) inputting triples of a knowledge graph into the iteratively trained knowledge graph embedding model for completion.The application combines attention mechanisms with calculations in real number domains, complex number domains and quaternion number domains to capture feature information of entities from different spaces and deeply depict spatial representations of entities and relationships, thereby improving the accuracy of triple matching in a knowledge graph completion task.