113 results about "Resource distribution" patented technology

A method and a device for allocating radio resources in in-band full duplex communication are disclosed. The method of a terminal comprises the steps of: receiving slot format information from a base station; confirming a DL section, an FL section, and an UL section on the basis of the slot format information; receiving UL subband information from the base station; and regarding a DL resource area as an UL resource area if an UL subband indicated by the UL subband information overlaps the DL resource area in the DL section.

Method and apparatus for TBS adjustment and adaptation for multiple and repeated transmissions in full duplex networks. The apparatus receives an allocation of resources across multiple slots scheduling multiple transmissions or multiple receptions. The apparatus determines a TBS adjustment based on the multiple transmissions or the multiple receptions. The multiple receptions comprise repetitions across different slot types. The TBS adjustment is based on half duplex slots and is maintained for all slots.

The application provides a digital plan execution optimization method for generating an optimal disaster relief task execution sequence of a current emergency plan when a disaster occurs in a park, and the method comprises the following steps: acquiring a current emergency plan and various resources in the current park; disassembling the current emergency plan to generate a task list containing at least two execution tasks; and generating an optimal execution path of the current emergency plan based on the task list and the various resources, wherein the optimal execution path is the current optimal disaster relief task execution sequence. When a disaster occurs in the park, the application disassembles the emergency plan matched with the current situation into an executable task list, then allocates resources in combination with the existing resources in the park, so that the resources required by each task during task execution are the most suitable resources at present, and then the optimal task execution path is obtained according to the currently allocated resources and the task execution path, thereby improving the response time and efficiency of disaster relief.

This invention discloses a method and system for optimizing game resources in a virtual game. The invention relates to the technical field of virtual games. It loads the current load of the virtual game based on a target resource demand sequence and constructs the resource distribution of the virtual game. Then, it performs topological clustering based on the content to be loaded in the virtual game, generating a resource topology map containing multiple game resource clusters, thus improving the accuracy of the resource topology map. The node dependencies in the resource topology map are marked, and flexible scheduling is performed based on the resource content allocated to each resource cluster, thereby outputting a multi-level flexible scheduling strategy. The high-speed video memory area and low-speed memory area of ​​the virtual game are optimized along this flexible scheduling strategy. Resource optimization events of the virtual game are determined based on the smooth constraints of the virtual game. Furthermore, resource anomaly signals of the virtual game are used to determine optimization configuration measures for the high-speed video memory area and low-speed memory area in terms of resource dimensions, improving the accuracy of the optimization configuration measures.

This invention provides a method for generating and distributing inspection tasks for coal mine inspection robots, comprising: constructing an inspection space mapping model; analyzing the correlation between inspection nodes; clustering inspection nodes using a multi-density clustering algorithm to form multiple inspection node clusters; optimizing the multiple inspection node clusters using a multi-objective ant colony algorithm to obtain multiple inspection path task combinations; calculating the task adaptation analysis results between the inspection robot and the inspection path task combinations; and assigning inspection path task combinations to the coal mine inspection robot using a convex resource allocation algorithm to generate coal mine inspection task distribution results. This invention uses a multi-density clustering algorithm to cluster inspection nodes and generate node clusters, which can accurately adapt to the scene characteristics of large differences in the density and uneven spatial distribution of inspection nodes in underground coal mines; and by using a convex resource allocation algorithm to assign the optimal inspection robot to each inspection path task combination, it can achieve precise optimization of inspection resources.

This invention proposes a method for continuously optimizing the efficiency of garden maintenance processes. The method includes: real-time data acquisition via handheld ground-based data acquisition devices and drones equipped with various data acquisition devices, including: hyperspectral data, multispectral data, laser point cloud data, and ground orthophoto maps of plants; preprocessing the real-time acquired data and then fusing it into multidimensional data, constructing a garden maintenance process intelligent analysis model based on the fused data; optimizing the scheduling and resource allocation of garden maintenance plans based on the intelligent analysis model; optimizing the intelligent analysis model based on the real-time data collected during the garden maintenance process according to the garden maintenance plan in step S3, combined with the data continuously collected in real-time in step S1; automatically optimizing the garden maintenance plan based on the optimized intelligent analysis model, thereby improving garden maintenance efficiency, reducing maintenance costs, and improving garden maintenance quality.

This invention discloses a method for congestion warning and access control of a satellite trunking common signaling channel. A State Service (STS) server uses statistical information on random satellite access and radio resource management (RRM) allocation from the terminal as a traffic status report, which is broadcast to users in real time via the common signaling channel. The satellite trunking terminal adjusts its access based on the user priority assigned at activation and the current system broadcast, forming a congestion warning and flow control mechanism. Based on the random access RACH information, users can obtain the uplink access traffic on the common channel of their respective beam within a unit of time. Based on the satellite resource management (RRM) information, users can obtain the probability of successfully requesting access beam resources within a unit of time. According to a predetermined access control strategy, the terminal initiates uplink traffic tiered restrictions before beam congestion, ensuring that users with different priorities receive corresponding communication connection rates. This provides users with better tiered satellite trunking access services and effectively prevents systemic traffic paralysis due to channel resource exhaustion.

This invention belongs to the field of resource allocation and discloses an emergency resource demand prediction method and apparatus based on WGAN-Stacking. The method includes: acquiring meteorological, geographical, and power grid data; generating fault samples using a Wasserstein generative adversarial network; quantifying the distribution difference between the generated fault samples and real samples based on FID distance and kernel Inception distance to screen target samples whose sample quality reaches a preset threshold, with the quantified distribution difference used to characterize the sample quality of the fault samples; inputting the target samples into a pre-constructed resource demand prediction model to predict the emergency resource demand in different regions; the resource demand prediction model adopts a Stacking ensemble learning framework, using RF, GBDT, and SVM as heterogeneous base learners and FNN as a meta-learner, learning the optimal nonlinear combination strategy between the prediction results of each base learner; and allocating emergency resources according to the prediction results output by the resource demand prediction model.

The application discloses a resource distribution method of a storage system and an electronic device, relates to the technical field of electric digital data processing, and can perform leaf node resource retrieval in a resource model tree according to a retrieval order determined according to the structure of the resource model tree of the storage system, to determine a target leaf node. After the resource distribution retrieval of any user is completed, the target leaf node is occupied first, so that other users jump over the occupied target leaf node when performing retrieval, and continue to perform retrieval according to the retrieval order, until the resource distribution request responses of all users are completed. The technical problem that, in the related art, when multiple allocation requests are parallel, the retrieval efficiency is relatively low, resource occupation waiting exists, and only the current demand is considered when allocating resources, and the overall resource planning cannot provide a reference is solved, the effect of avoiding full resource scanning, optimizing a retrieval path, improving retrieval efficiency and concurrent processing capability, and facilitating overall resource planning is achieved.

The disclosed embodiments, collectively referred to as the “Message Ordering Buffer” or “MOB”, relate to an improved messaging platform, or processing system, which may also be referred to as a message processing architecture or platform, which routes messages from a publisher to a subscriber ensuring related messages, e.g., ordered messages, are conveyed to a single recipient, e.g., processing thread, without unnecessarily committing resources of the architecture to that recipient or otherwise preventing message transmission to other recipients. The disclosed embodiments further include additional features which improve efficient and facilitate deployment in different application environments. The disclosed embodiments may be deployed as a message oriented middleware component directly installed, or accessed as a service, and accessed by publishers and subscribers, as described herein, so as to electronically exchange messages therebetween.

The present disclosure provides a timing method, device, resource distribution system, computer device and storage medium. The method comprises: in response to a triggered timing event, in each timing period, performing the following process: determining a current target timing duration corresponding to the current timing period; wherein the current target timing duration is determined based on a pre-designed timing duration or a timing result of a previous timing period corresponding to the current timing period; timing based on the current target timing duration; in response to the timing reaching the current target timing duration, determining rendering state change information of the terminal device in the current timing period, and determining a timing result of the current timing period based on the rendering state change information, and entering a next timing period.

An allocation search device includes a resource data acquisition unit that acquires resource data including a latest resource position and dispatch availability, an allocation plan creation unit that creates a plurality of allocation plans of a resource corresponding to an occurring event, using the resource data, an allocation evaluation unit that assigns an evaluation value to each of the plurality of allocation plans, using the resource data, and an allocation plan selection unit that selects an effective allocation plan from the plurality of allocation plans on the basis of the evaluation value.

The application discloses a flight confidence calculation method and system based on multidimensional sensing data, and the method comprises the following steps: data acquisition, multidimensional feature extraction, establishment of safety value mapping, multidimensional confidence fusion calculation and decision feedback. The application belongs to the technical field of data processing, and specifically refers to a flight confidence calculation method and system based on multidimensional sensing data. According to the scheme, dynamic resource allocation is adopted to guarantee the quality of core data acquisition, dynamic Kalman filtering is adopted to reduce noise, high-value historical data is screened, and the double mechanisms of multi-sensor cross calibration and Bayesian inference verification are adopted to output an optimal spatial parameter estimation set and a corresponding confidence interval, so that the accuracy of confidence evaluation is improved. The safety value target is defined, the cause-and-effect chain is constructed, the cause-and-effect contribution degree of features to the safety value is quantified, the direct correlation between the features and the safety value is established, the multidimensional confidence is dynamically fused to generate the final flight confidence, and the problem that the confidence is high but the decision is unsafe is avoided.

This invention relates to an adaptive learning-based crop growth prediction system and method for arid regions, encompassing the field of crop growth prediction. It generates environmental baseline features and physiological representation vectors by simultaneously acquiring ground environmental data, remote sensing physiological images, and historical yields, thereby constructing a multi-dimensional state-space model. The model is then input into a dynamic model containing physiological response sensitivity parameters, and a set of expected growth trajectories under various water supply conditions is generated through difference equations. Based on this, a marginal yield loss matrix is ​​constructed, and differential resource allocation vectors for each sub-region are output under total water resource constraints. Furthermore, the crop growth model is dynamically corrected and the marginal yield loss matrix adjusted using the residual discrepancy between real-time physiological feature values ​​and predicted trajectories. This invention achieves accurate simulation of crop growth status and optimized water resource allocation, possessing adaptive learning and disaster mitigation capabilities.

This invention relates to an adaptive log processing method, system, and storage medium based on a large model. The method includes: acquiring log samples; performing semantic structure analysis and format feature recognition on the log samples to generate structured extraction templates; associating the original log messages with the structured extraction templates and injecting template identifiers into the messages, writing them into a message middleware; reading messages from the message middleware and distributing them to corresponding processing pipelines for parallel stream processing according to the template identifiers; collecting log processing process data; constructing a multi-dimensional analysis model based on the process data to allocate resources to the processing pipelines; performing alarm matching on the processed logs; and combining alarm content with a local operation and maintenance knowledge graph to generate diagnostic suggestions, which are sent together with the alarm information. This invention can reduce log processing latency, optimize storage costs, reduce manual intervention, improve alarm accuracy, and achieve intelligent allocation of processing resources.

This disclosure provides a method, apparatus, and device for allocating large-scale model resources based on blockchain. The method includes: receiving first source data sent by a data provider; cleaning and processing the first source data to obtain second source data and determining data digest information for the second source data; batch inputting the data digest information into a target model and determining the indicator data for each data digest information under multiple evaluation metrics; sending the indicator data of the data digest information to a smart contract; and allocating first resources to the data provider corresponding to the data digest information when the model performance improvement attribute reaches a preset attribute threshold; and storing the data digest information, the data provider, the first resource, and the sending address and time information of the data digest information on the blockchain. The technical solution of this disclosure, through multi-metric evaluation and smart contracts, achieves accurate and fair allocation of large-scale model resources, thereby improving resource utilization and incentive effects.

The application relates to the technical field of construction risk early warning, in particular to a building construction risk early warning method and system based on BIM, which comprises the following steps: constructing a correlation matrix between risk nodes based on time and space dimensions for risk factors of each node in a construction process, calculating risk propagation intensity values between nodes, judging the risk correlation relationship between nodes, classifying the risk coupling degree according to the propagation rate, and outputting the risk coupling matrix value. In the application, a high-risk area is extracted by combining spatial distribution data to realize dynamic partition management, the dynamic influence of environmental variables such as temperature, humidity and vibration is quantified, the complex relationship between environmental conditions and risk states is revealed, the accuracy and real-time performance of risk assessment are optimized, the node priority and resource allocation are dynamically adjusted by analyzing the risk transfer trend and the change of the propagation path, the influence of the newly-added risk signal is updated in real time, and the whole-process dynamic optimization of construction risk early warning is realized.

This invention relates to the field of task scheduling technology, specifically to a multi-task processing method and system based on a large model, comprising the following steps: extracting resource parameters using a large model to generate a conflict intensity matrix, screening resource-overlapping node pairs, determining structural conflicts, constructing a dependency graph to calculate complexity scores and prune dense regions, extracting high-frequency paths to divide scheduling units, and generating a task priority sequence. In this invention, by constructing a conflict intensity matrix and combining node clustering features to identify task resource conflict relationships, the sensitivity and accuracy of task partitioning to resource distribution are improved. Nodes are divided into upper and lower bounds based on median deviation, and structural optimization and reorganization are achieved by combining resource type dissimilarity rates. Path depth and branch factors constitute the basis for complexity scoring. Weights are dynamically adjusted based on occupancy time to identify pruning dense regions. The most frequently called paths constitute the main path set. Non-main path tasks are divided according to node coverage relationships, enhancing the clarity of scheduling boundaries and resource isolation capabilities.

This application provides a method for dynamic collaborative allocation of airspace resources based on multi-agent reinforcement learning, belonging to the field of airspace resource allocation technology. The method includes: constructing a low-altitude airspace simulation environment and determining the environmental state space; constructing a set of perception state spaces and combining it with an action space set to construct a multi-objective reward mechanism; performing policy optimization analysis on the agent set to obtain a set of regulating action spaces and a set of regulating perception state spaces; performing conflict detection and resolution on the regulating action space set; converting the target action space set into control command execution, updating the environmental state space, and returning to construct the perception state space set. This application addresses the technical problem in existing technologies where the inability of multiple agents to form spatiotemporally integrated collaborative cognition during policy optimization restricts the efficiency and security of dynamic collaborative allocation of airspace resources, thus achieving the technical effect of improving the efficiency and security of dynamic collaborative allocation of airspace resources.

This application relates to a baseband carrier resource configuration method, apparatus, baseband processing unit, and system. The baseband carrier resource configuration apparatus includes: a first storage module, a second storage module, an allocation module, a first interface, and a second interface. The first storage module is connected to a central processing unit (CPU) via the first interface. The allocation module is connected to both the first and second storage modules. The second storage module is connected to an optical port via the second interface. The optical port is connected to a radio frequency (RF) processing unit. The CPU stores baseband resources. The allocation module determines a target resource in either the first or second storage module based on data distributed via the optical port, and extracts antenna carrier data from the target resource. The allocation module then sends the antenna carrier data to either the first or second interface. This application solves the problem of inflexible configuration of baseband carrier resources and achieves flexible configuration of baseband carrier resources.

This invention discloses a port communication system and method for a power router, relating to the field of power communication technology. The system includes a data acquisition module, an intelligent communication decision engine, a communication execution module, and a storage module. This invention utilizes an intelligent communication decision engine that integrates artificial intelligence technology to perform deep analysis and learning of data, predicting system operation trends and communication needs. This solves the problem that traditional fixed-rule decision-making cannot adapt to dynamic system changes, achieving accurate prediction of communication needs. When an anomaly is detected, the intelligent communication decision engine automatically generates the optimal communication decision scheme, which is then executed by the communication execution module. This addresses the problems of delayed response and unreasonable allocation of communication resources in existing technologies when dealing with faults or anomalies, enabling rapid handling of abnormal situations. Ultimately, this improves the intelligence and adaptability of the power router port communication system, ensures timely transmission and processing of critical data, and improves the operating efficiency of the power system.

The application discloses a kind of dual-target collaborative multi-satellite resource allocation methods based on spatial dispersion, effectively solve the problem of inconsistent specification in capability description, difficult calculation in multi-satellite resource allocation under large-scale remote sensing satellite scene.The method comprises the following steps: first, the earth surface is dispersed into grid, precalculates satellite coverage capability and is mapped to grid, realizes uniform description of coverage capability;Second, a satellite coverage capability master table is constructed with grid code as the primary key, for efficient retrieval;Finally, based on the master table, with optimal task completion time as the main target, the lowest energy consumption as the secondary target, the task completion time is compressed through time optimization stage, the total energy consumption is reduced under time constraint in energy consumption optimization stage, and the conflict of dual targets is balanced by means of dynamic relaxation mechanism, to generate multiple optimization schemes, realize the efficient allocation of large-scale remote sensing satellite resources.

The application discloses a kind of based on deep learning model chain's regional high-resolution horizontal irradiance prediction method, the method includes: remote sensing data and GHI ground measured data are matched in time and space;According to the geographical time information where site is located, astronomical characteristic parameters are calculated;The input feature set including GHI ground measured data and corresponding remote sensing data, astronomical characteristic parameters and geographical time information is constructed, and the input feature set is used to train the preset improved TabNet model;Based on the improved TabNet model trained, input the data set to be inverted to generate GHI inversion image data set;The preset improved Earthformer model is trained using GHI inversion image data set;The data set to be predicted is input to the improved Earthformer model trained, and the accurate prediction of regional horizontal irradiance is realized.The GHI resource distribution map predicted by the application has a spatial resolution of 4KM, and supports fine prediction of solar photovoltaic power generation resources in any region.

The present invention relates to methods, systems, and computer readable media for mitigating unauthorized message relay attacks. According to one method, the method is performed at a network node configured to relay network message information or derivative information to avoid resource contention between user equipments (UEs). The method includes receiving a first temporary UE identifier (TUEI) associated with a first UE for requesting radio resources within a serving cell; allocating the radio resources to the first UE using the first TUEI; generating a second value based on the first TUEI using at least a conversion algorithm, wherein the second value has a higher entropy characteristic than the first TUEI, thereby reducing a likelihood that the second value includes an encoded message that can be decoded by a second UE when relayed by the network node; and broadcasting a message including the second value to a plurality of UEs including the second UE.

The invention discloses a wireless intercommunication method, and relates to the technical field of communication, and the method comprises the steps: scanning a current working channel and a peripheral interference channel through a radio frequency module, obtaining the intensity distribution of adjacent signals and the interference level of the channel, judging the dynamic characteristics of a network, and estimating the macroscopic scene characteristics of the current network; a network operation mode is decided through a preset condition; if it is judged that the complexity of the current network scene exceeds a preset threshold value, a clustering mode is triggered; when the decision is a clustering mode, the extension sets elect cluster heads based on a distributed weight election mechanism to construct clusters, a prediction algorithm is adopted to predict relative position changes of adjacent extension sets, and a topology maintenance strategy is adjusted according to a prediction result; and constructing a global adjacency list, carrying out connection stability verification on the adjacency relation, carrying out resource allocation through a dynamic negotiation protocol, carrying out value evaluation on the transmitted voice frame, and selecting a coding scheme for transmission based on an evaluation result.

A method for managing data protection includes monitoring, by a data protection service, data protection requests issued by a set of client devices to obtain telemetry data, wherein the set of client devices are associated with a geographic location, performing a resource analysis on the telemetry data to determine a centralized backup system (CBS) instance allocation for a CBS instance in the geographic location, making a determination, based on the resource analysis, that the CBS instance is to be instantiated in the geographic location, based on the determination, deploying the CBS instance in a production environment located in the geographic location, and initiating a replication of backup data from a CBS to the CBS instance.

The application relates to the technical field of edge computing storage, and discloses a distributed data storage dynamic optimization method based on edge computing. The method acquires data storage state data and data access request data of distributed edge nodes, and constructs a data resource distribution model according to the data; the method combines preset optimization conditions with the model to determine a system resource early warning state, enters a dynamic optimization mode when the early warning is triggered, and generates a data migration priority queue, and executes a data migration operation according to the queue; the method updates the data resource distribution model according to a migration result, determines a system resource exit state based on the updated model, exits the dynamic optimization mode when the exit state is triggered, and transmits the optimized storage state data to a central management system. The method dynamically adjusts data distribution by real-time sensing of node states and access demands, adapts to edge node heterogeneity and data access dynamics, and improves distributed data storage efficiency.

The application provides a power distribution room dynamic temperature control method and system based on heat tracing, a fine thermodynamic model of the power distribution room is constructed, and inverse problem solving is performed on multi-point temperature monitoring data based on a total variation regularization algorithm, so that accurate tracing and visual positioning of hidden and non-uniformly distributed heat sources are realized; on this basis, the system dynamically solves an optimal control strategy according to the heat source distribution obtained through real-time inversion, in combination with a preset cooling efficiency matrix, so as to drive each cooling device to perform directional, quantitative and collaborative precise cooling. The method and system effectively overcome the inherent defects of the traditional feedback regulation mode based on average temperature, such as difficulty in identifying local hot spots and mismatch of cooling resource allocation, achieve the technical effects of significantly improving temperature control accuracy and equipment operation reliability while greatly reducing the energy consumption of the cooling system, and provide an innovative solution for intelligent and efficient temperature management of closed electrical spaces such as power distribution rooms.