15 results about "Resource analysis" patented technology

This application provides a method, apparatus, and electronic device for determining satellites used for storing and forwarding data, relating to the field of communication technology. The method is applied to a satellite resource analysis network element and includes: acquiring demand information, wherein the demand information includes: data transmission requirements of the transmitting end, the location information of the transmitting end, resource usage information of the satellite network, ephemeris information, and the location information of the receiving end; determining, based on the demand information, a set of target satellites from the satellite network for storing and forwarding data transmitted by the transmitting end; and transmitting information carrying the target satellite set to the transmitting end. Based on the above method, satellites that meet the actual data transmission requirements of the data transmitting end can be accurately determined, improving the space utilization rate of satellite storage and avoiding situations where satellites cannot provide services due to insufficient space, even though there are actually idle satellites in the satellite network.

The present application relates to the technical field of dynamic load balancing. The present application relates to a unified scheduling and monitoring system for computer room computing power resources based on dynamic load balancing. It includes a computing power node setting module, a running prediction analysis module, a demand resource updating module, a demand resource analysis module, a standby resource setting module and a resource scheduling module. The computing power node setting module is used to collect computer room computing power resources, which are divided into to-be-allocated computing power resources and used computing power resources. The present application builds a bounded computing power node state prediction system, taking the latest running state of the computing power node as the prediction center, setting the upper and lower limit boundaries of the prediction in combination with the total available computing power of the computing power resource pool, avoiding the invalid results caused by boundaryless prediction, and based on the change trend and fluctuation law of the historical running state sequence, the prediction result is more in line with the actual running characteristics of the computing power node, providing a reliable state basis for the analysis of subsequent demand computing power resources.

This invention belongs to the field of enterprise resource planning (ERP) technology and discloses an intelligent matching method and system for policy application conditions based on enterprise resource analysis. By constructing a dedicated extraction model for policy application elements, it performs structured parsing and industry-customized four-level hierarchical decomposition of policy texts, transforming natural language application conditions into executable logical expressions. It accurately handles complex rules such as AND, OR, non-nested logic, numerical thresholds, and temporal constraints. A four-level progressive matching and verification mechanism is adopted, prioritizing matching according to the order of prohibition (one-vote veto), rigid access, core scoring, and auxiliary bonus points. It incorporates industry-specific rules and enterprise lifecycle adaptation logic to avoid invalid matching and screening biases, upgrading policy matching from superficial textual association to deep compliance verification, thus improving matching accuracy and adapting to the application and screening needs of various complex preferential policies for enterprises.

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 discloses a method for quickly delineating a potential mineral resource prediction area based on remote sensing alteration zones, and relates to the technical field of mineral resource analysis. The method comprises the following steps: based on remote sensing data, using atmospheric correction and mineral mapping to extract alteration zone information; performing rasterization processing on mineral investigation data to obtain a mineral investigation raster image; performing registration analysis and data fusion on the alteration zone information and the mineral investigation raster image to obtain fused data; generating a vector cloud space according to coordinates based on the mineralization zone and the fused data, and performing mineralization zone restriction analysis based on the vector cloud space; and determining the potential mineral resource prediction area based on the mineralization zone restriction analysis result. The application can improve the delineation efficiency and precision of the potential mineral resource prediction area by superimposing remote sensing data and mineral investigation data.

This invention discloses a collaborative optimization design method for bearing systems based on TRIZ theory, belonging to the field of mechanical design and innovation methods. First, based on the optimization requirements of the bearing system performance, this invention establishes a three-level functional model of supersystem-system-subsystem and identifies key problem clusters. The functional model includes at least one of the following: useful functions, harmful functions, insufficient functions, and excessive functions. Then, based on the three-level functional model, contradiction solutions and resource analysis are performed at the component level, system level, and supersystem level to obtain contradiction solutions. Subsequently, a matter-field model is constructed and solved, and the TRIZ evolutionary law is applied to guide system reconstruction to obtain a system evolution scheme. Finally, the contradiction solutions and the system evolution scheme are cross-integrated and their feasibility is evaluated to generate an innovative conceptual design scheme for the bearing system. This invention effectively solves the problems of existing technologies being limited to single problems and isolated components.

This invention discloses a method for identifying and analyzing the driving mechanism of river and lake backflow based on interpretable machine learning, belonging to the fields of hydrological and water resources analysis and artificial intelligence application technology. The method includes: collecting long-sequence hydrological data of the river and lake system; dividing the time series into different characteristic periods using the operational nodes of large-scale water conservancy projects as boundaries; constructing a multi-dimensional input feature set; training a backflow identification model based on a gradient boosting decision tree using a class weight balancing strategy and a Bayesian optimization algorithm; calculating the marginal contribution value of each hydrological driving factor using the SHAP interpretability method; identifying the physical threshold inducing backflow by combining a SHAP dependency graph with a binary box plot; and comparing the analysis results of different periods to reveal the evolution law of the backflow driving mechanism. This invention effectively solves the problems of traditional methods' difficulty in capturing nonlinear hydrological responses and the lack of physical mechanism explanation in black-box models, and can accurately identify backflow events.

The embodiment of the present application discloses a kind of multi-channel equipment and the multi-waveform implementation method based on time division resource, in multi-channel equipment, time division spectrum resource analysis module according to the occupation situation of waveform in time domain space and frequency domain space in the applied system, dynamically divide waveform into multiple groups;General digital-analog conversion distribution module according to the center frequency point of each waveform group distributes each waveform group to corresponding digital-analog conversion channel for conversion, and carries out radio frequency channel setting to multi-channel equipment;Algorithm logic resource scheduling module according to waveform grouping result and time domain occupation situation allocates CPU kernel resource and FPGA logic resource to each waveform group, and introduces digital waveform to corresponding radio frequency channel of multi-channel equipment.The technical scheme provided by the embodiment of the present application can realize the purpose that applied system makes full use of time-frequency space and spectrum resource based on multi-channel equipment, and provides more effective integrated scheme for aviation integrated radio.

This specification provides a method, apparatus, device, and readable storage medium for configuring DPU resources. The method includes: accessing a preset path of a target server through a set channel to obtain the PCI resource configuration information of the target server's current hardware; calculating the amount of allocated hardware resources in the target server's hardware resources based on the obtained PCI resource configuration information; and calculating a critical value for the maximum reserved hardware resources based on the allocated hardware resources. The target server includes a DPU device. This technical solution automatically obtains the server's PCI resource configuration and calculates the maximum reserved resource critical value, effectively avoiding the tedious process of repeatedly restarting the server to gradually approach the critical value in traditional manual testing, significantly improving testing efficiency. Simultaneously, this method ensures the accuracy of the critical value results through precise system resource analysis, providing a reliable basis for resource reservation under the DPU.

This invention discloses a reverse engineering method to solve the problem of FPGA control bit occupancy, belonging to the field of hardware security. This method addresses the issue that control bit occupancy prevents the correct reconstruction of the corresponding logic function of logic units during reverse engineering. Compared to existing technologies, this method does not rely on complex algorithms or manual intervention, is applicable to various FPGA reverse engineering scenarios, and allows researchers to achieve efficient and accurate circuit function reconstruction under simple experimental conditions, thus providing effective support for FPGA bitstream file resource analysis and security assessment.

The application discloses a kind of intelligent resource management tracing system and method based on blockchain, it is related to data analysis technical field.The method includes the following steps, data acquisition, establish resource analysis database, real-time update to resource analysis database;According to historical resource distribution data, historical resource cancellation data and resource use data, resource scheduling analysis is carried out;According to resource scheduling analysis result, establish resource integration scheduling model, and carry out resource intelligent scheduling;After using resource, resource cancellation is carried out, and resource cancellation data is backed up;Real-time acquisition resource distribution data and resource cancellation data, real-time acquisition resource distribution data and resource cancellation data are used as historical resource distribution data and historical resource cancellation data, and resource analysis database is updated.The application analyzes the scheduling of resources, trains intelligent scheduling model, distributes resources greater than average usage rate and less than average loss rate, to ensure that the use efficiency of resources is higher.

A model parallel training method and device, equipment, storage medium and program product are disclosed. Resource data of each computing node in a computing cluster is analyzed to generate resource analysis results. Training data of a model is analyzed to generate training data analysis results. A partition adjustment strategy is generated according to the resource analysis results and the training data analysis results. The training data is segmented based on the partition adjustment strategy to distribute training data that is adapted to the resource capacity of the corresponding computing node to each computing node. The model is split into at least two sub-models, and the sub-models are distributed to the corresponding computing nodes to perform parallel training on the distributed training data using the sub-models. The embodiments of the present application can adapt to the dynamic changes of node resources and the differences in training data characteristics, improve the resource utilization of model parallel training, accelerate the training convergence speed, and ensure the stability and efficiency of training.

The present disclosure provides a dialogue processing method, device and equipment and a storage medium. The method comprises: obtaining dialogue information, determining a dialogue language type of the dialogue information; performing resource analysis processing on the dialogue information to obtain a high-resource language type corresponding to the dialogue information; obtaining a first task instruction and a second task instruction; simulating a first task agent in a target language model according to the first task instruction, performing cross-language understanding processing on the dialogue information in the dialogue language type in the high-resource language type based on the first task agent to obtain a dialogue understanding result in the high-resource language type; simulating a second task agent in the target language model according to the second task instruction, performing inference decision processing on the dialogue understanding result based on the second task agent to obtain reply information corresponding to the dialogue information. The method can effectively improve the accuracy of the generated reply information.

This invention relates to the field of construction management technology, specifically to a full-process management platform for the construction of hollow sandwich slab structures. It addresses the problems of traditional construction management methods, which often struggle to effectively monitor construction progress and rationally allocate construction resources, leading to low construction efficiency, increased costs, and compromised quality, thus failing to meet the needs of modern construction management. The full-process management platform includes a progress monitoring module, a progress analysis module, an analysis and judgment module, a notification management module, a resource management module, and a resource analysis module. This platform enables precise monitoring of the construction progress of hollow sandwich slab structures and intelligently selects and allocates optimal construction resources based on real-time progress and construction needs, thereby effectively improving construction efficiency, shortening the construction period, ensuring project quality, reducing construction costs, minimizing resource waste, and enhancing the intelligent management level of the entire construction process.