47 results about "Resource analysis" patented technology

The invention discloses a river and lake backflow recognition and driving mechanism analysis method based on interpretable machine learning, and relates to the technical field of hydrology and water resource analysis and artificial intelligence application, and the method comprises the steps: collecting long-sequence hydrology data of a river and lake system; taking operation nodes of the large hydro-junction project as boundaries, and dividing the time sequence into different characteristic periods; constructing a multi-dimensional input feature set; a class weight balance strategy and a Bayesian optimization algorithm are adopted to train a backward flow recognition model based on a gradient lifting decision tree; a marginal contribution value of each hydrological driving factor is calculated by using an SHAP interpretability method, a physical threshold for inducing backward flow is identified by combining an SHAP dependency graph with a binary box plot, analysis results in different periods are compared, and an evolution rule of a backward flow driving mechanism is revealed. The method effectively solves the problems that a traditional method is difficult to capture nonlinear hydrological response and the black box model lacks physical mechanism explanation, and can accurately recognize the backward flow event.

Some embodiments are directed to a resource allocation analysis system implemented via a back-end application computer server. A resource data store may contain electronic records associated with a set of resource types, each electronic record including an electronic record identifier and resource parameter. The back-end application computer server may receive, from the resource data store, information about a set of resource types to be analyzed, including the associated resource parameters. The computer server may then execute a differential evolutionary algorithm to optimize the set of resource types based on at least one non-linear constraint and generate resource analysis results. The back-end application computer server may, according to some embodiments, perform a resampling process that uses non-parameterized historical data, regression on at least one resource type, and moment matching.

The invention relates to the technical field of resource processing, provides a resource data fluctuation analysis processing method and device, a storage medium and a program product, and can automatically perform resource data fluctuation analysis processing. The method comprises the following steps: in response to a data extraction trigger event, extracting first resource data and corresponding first service volume data of each service in an analysis period from a multi-service system; classifying the first resource data of each service and the corresponding first service volume data according to preset multi-class resource inspection tasks to obtain second resource data and corresponding second service volume data under each class of resource inspection tasks; for each type of resource inspection task, acquiring fluctuation information of the second resource data and the corresponding second business volume data under each preset resource analysis dimension and / or each resource analysis dimension combination, and obtaining a fluctuation analysis result under the resource inspection task according to the fluctuation information; and triggering creation of a corresponding resource processing task according to a fluctuation analysis result.

A system includes a processor that executes computer executable components stored in a memory. The computer executable components include an application identification component that identifies a new imperative application where recovery workflow for the new imperative application is unavailable. The computer executable components include an analysis component that analyzes the new imperative application to determine resources required to be protected; the analysis component determines an order of steps to be performed within a workflow to guarantee recovery of the new imperative application. The computer executable components include a recovery design component that utilizes a subset of legacy recovery plans to create, at least in part, a preliminary recovery plan for the new imperative application; the recovery design component tests the preliminary recovery plan and iteratively updates the preliminary recovery plan until a failure-free recovery plan is developed for the new imperative application.

The invention relates to the field of human resource management, in particular to a human resource management method based on multi-modal data fusion and adaptive learning, and adopts the technical scheme that the method comprises the following steps: constructing a time sequence data portrait of a target object through static attribute data, dynamic behavior data and external environment data; and inputting the multi-modal data into a preset feature extraction model for feature extraction to obtain a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a pre-trained human resource analysis model to obtain an analysis result, and finally executing a corresponding human resource management operation according to the analysis result. The personnel and post matching degree score, the demission risk probability and the recommended development path are analyzed, intelligent resume screening and personnel and post matching optimization can be carried out, employee demission risk prediction and intervention suggestion can be carried out, personalized employee development path planning can be carried out, and the employee development path planning efficiency is improved. And deep learning and dynamic optimization capabilities are improved through an algorithm framework of multi-modal data fusion and dynamic adaptive learning.

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 invention discloses a Yellow River downstream city landscape ecological risk analysis method based on high-score data, and relates to the technical field of resource analysis, and the method comprises the steps: obtaining land utilization classification data, dividing an ecological risk evaluation price network based on the land utilization classification data, carrying out the statistics of landscape pattern indexes in each grid, and carrying out the calculation of the ecological risk evaluation price network. Generating landscape interference degree space distribution data; obtaining multi-dimensional geographical environment factor data of the research area, performing spatial correlation analysis on the multi-dimensional geographical environment factor data and the land utilization classification data, and screening out dominant environment factors; generating landscape vulnerability spatial distribution data based on a spatial association relationship between the dominant environmental factors and the land utilization classification data; according to the method, all technical links are connected in series by taking a uniform grid space as an analysis reference, so that refined space representation and scientific coupling fusion of the landscape interference degree and the landscape vulnerability are realized, and the space accuracy of a landscape ecological risk analysis result is greatly improved.

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.

The invention relates to the technical field of power systems, in particular to a novel adjustable resource fault early warning method for wide-area measurement data anomaly detection, and the method comprises a data collection unit which is used for obtaining original measurement data from a wide-area measurement system; the data processing unit is used for realizing data preprocessing, anomaly detection, fault risk assessment and adjustable resource analysis and early warning functions; the communication unit is responsible for data transmission and information interaction with a wide-area measurement system and a power system dispatching control center; and the display and alarm unit presents the fault early warning information and the adjustable resource adjustment suggestion in a visual mode, and triggers sound-light alarm when the fault risk reaches the early warning level. According to the method, the deep auto-encoder is combined with the adversarial training mechanism to realize wide-area measurement data anomaly detection, high-dimensional complex data can be effectively processed, the accuracy and robustness of anomaly detection are remarkably improved, and the inherent limitation of a traditional statistical analysis and machine learning method is overcome.

The application provides a data trusted computing framework based on a consortium blockchain, entities include a data demander, a data provider, a consensus node and a certificate authority; a structure is divided into a data registration layer, a data trusted layer, a data consensus layer, a data processing layer and a data delivery layer. The data registration layer adopts a data architecture paradigm based on the consortium blockchain, divides data into identification, characteristic data and data entities to standardize a data registration process, provides a unified access mode for heterogeneous, heterogeneous and heterogeneous data resources and integrates data resources; the data trusted layer uses a data trusted computing mechanism, so that the data provider provides a data resource analysis and processing result for the data demander without contacting original data; the data consensus layer includes a data trusted traceability mechanism, guarantees safety and integrity of data flow; the application can change a traditional data hosting / exchange as a service mode into a data processing as a service mode and realizes data "available but invisible".

The invention relates to a resource analysis method and device, computer equipment, a storage medium and a program product. The method comprises the steps that in response to a thermodynamic diagram display operation for the hybrid cloud platform, an embedded vector corresponding to a resource node in a resource topological graph of the hybrid cloud platform is obtained, and the embedded vector of the resource node is generated by performing embedded coding based on an operation index of a resource represented by the resource node; based on embedded vectors corresponding to resource nodes in the resource topological graph, a thermodynamic diagram of the hybrid cloud platform is obtained through rendering, the thermodynamic diagram comprises node icons corresponding to the multiple resource nodes respectively, and icon colors of the node icons are related to processor use conditions and / or storage resource use conditions. The side boundary visual information of the node icon is related to network bandwidth and / or delay. By adopting the method, the application scene can be widened.

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 invention relates to a novel security industry data resource analysis method, and belongs to the technical field of security, efficient processing and intelligent decision making of security data are realized through an end-side cloud cooperation architecture, real-time target detection is performed through deploying a lightweight YOLOv8 model through an edge end, and preliminary anomaly recognition is completed; an LSTM neural network is trained on the cloud platform based on historical alarm data, and high-risk area prediction in the next 24 hours is realized; a DBSCAN clustering algorithm is combined to carry out spatial correlation analysis on the personnel trajectory, and a suspicious gang is automatically identified; and finally, an entity relation network is constructed through the knowledge graph, and cross-system event reasoning is supported. According to the technical combination, the system has the capabilities of full space-time coverage, full factor fusion and full process intelligence, a closed-loop safety prevention and control system is formed, and the automation level and the actual combat capability of the security and protection system are effectively improved.

The invention discloses a communication method, device and system, a storage medium and a program product. The method comprises: a first network element sending first information to a second network element, the first information indicating a network resource application; the second network element sends second information to the first network element, wherein the second information indicates a network resource application result; the first network element determines to establish a proprietary bearer for the terminal; and under the condition that the network resource application is successful, the first network element sends third information to a third network element, and the third information indicates to establish a proprietary bearer for the terminal. According to the scheme of the invention, only the network resource analysis is transferred to the second network element, and the first network element completes other analysis, so that the signaling interaction between the first network element and the second network element is reduced under the condition that the service experience analysis of the terminal can be completed, the signaling impact on the core network equipment and the link is avoided, and the service experience of the terminal is improved. And the analysis time delay is reduced and the analysis efficiency is improved.

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.

The invention discloses a large language model quantitative quality evaluation system, which comprises a resource analysis end, a quantitative execution end and an evaluation analysis end, and is characterized in that the resource analysis end is used for collecting a device data set, determining hardware resource constraints of edge devices, and dividing the sensitivity level of a functional layer to quantification in a large language model to obtain a sensitivity sequence; the quantization execution end is used for establishing a mapping rule and realizing precision grade mapping; balancing quantization precision loss and resource consumption through iterative optimization, determining a final allocation scheme and quantization parameters, constructing a mixed precision quantization operator library, determining a compilation tool chain of edge equipment, and constructing a quantization model of a large language model; the evaluation analysis end tests different tasks so as to evaluate the quality of the quantitative model on the edge device and judge whether the quality reaches the standard or not; and performing precision adjustment iteration and resource cutting optimization of the quantitative model for substandard items in evaluation, monitoring key indexes and storing a system data set.

The invention discloses a project progress deviation dynamic early warning method oriented to whole process consultation, relates to the technical field of project early warning, and is used for solving the problems of unbalanced working face advancing rhythm and uneven resource distribution. The method comprises the following steps: calling classification data of working surfaces of all areas, detecting ring number propulsion rates and tool changing frequencies, calculating engineering propulsion indexes and shield wear coefficients according to the classification data, further evaluating area propulsion synchronization fluctuation rates, judging whether to enter a resource analysis mechanism or not according to the fluctuation rates, and collecting grouting material consumption of the working surfaces in the mechanism; the method comprises the following steps: counting arrival intervals of muck transport vehicles, identifying a vehicle accumulation state, detecting stratum hardness when accumulation is abnormal, predicting a resource consumption trend based on grouting consumption, generating a resource consumption level after correction in combination with the stratum hardness, judging whether areas are synchronously unbalanced or not according to the level, selecting corresponding pre-control measures, and improving the overall propulsion efficiency of a tunnel.

The invention provides a wind power plant micro-siting and model optimization method based on Weibull parameter perpendicularity and spatio-temporal evolution, and relates to the field of wind resource analysis and wind power prediction. The method comprises the following steps: S1, collecting multi-height-layer laser radar observation data; s2, calculating a scale parameter A and a shape parameter K according to the wind speed data of the actually measured height layer, and reconstructing a Weibull parameter field; s3, analyzing the Weibull parameters from a time dimension and a height dimension; s4, establishing a wind resource-fan performance mapping model; and S5, developing a collaborative optimization algorithm, optimally selecting point locations, and matching wind turbine generator types and hub heights to obtain a final scheme. The method has the beneficial effects that the real wind speed distribution and energy capture process on the wind sweeping surface of the fan can be more accurately reflected, the accuracy of wake flow loss calculation is greatly improved, the limitation that the links are separated or sequentially processed in the traditional process is broken through, and the overall optimization of the overall design scheme of the wind power plant is realized.

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.

The embodiment of the invention discloses a data processing method for a resource exchange service, related equipment and a program product, and the method comprises the steps: obtaining service data generated by the resource exchange service, and determining the data attribute of the service data; based on the determined data attributes, selecting a target model from a model pool, the target model being associated with at least one data attribute; respectively calling the target model and the rule engine, and performing resource analysis on the resource provider based on the business data to obtain a model analysis result corresponding to the target model and a rule analysis result corresponding to the rule engine; and based on the model analysis result and the rule analysis result, a resource analysis report of the resource provider is generated, and an accurate resource analysis result can be generated in a complex and changeable service environment.

The invention provides an application program performance monitoring method and system, electronic equipment and a program product. According to the scheme, a resource configuration file of a role model in a target application program is obtained; performing model resource analysis calculation processing on the resource configuration file to obtain model resource data; performing data report generation processing on the model resource data to obtain an application program performance report; and performing performance optimization processing on the role model according to the application program performance report to obtain an optimization result. According to the scheme, the efficiency of application program performance monitoring can be improved, and the method can be widely applied to the fields of animation game making engine software and development systems, digital culture product making software, digital culture creative software and the like in the digital creative industry.

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 invention relates to the technical field of game optimization, and discloses a distributed storage-oriented game resource loading optimization method, which comprises the following steps of: acquiring game modes of a user, performing game resource analysis on a target user, and executing corresponding loading optimization methods according to different game modes. According to the game resource loading optimization method oriented to distributed storage, through an intelligent resource loading strategy, timely loading of key resources is ensured, waiting time is shortened, game fluency and user satisfaction are improved, different optimization strategies are adopted for a single-person mode and a multi-person mode, respective characteristics are fully considered, resource utilization efficiency is improved, and user experience is improved. And automatic judgment and decision are performed according to the user behavior data and communication information, so that manual operation of the user is reduced, and the loading process is more intelligent and efficient.

This application relates to the field of data processing technology and discloses a method and system for personalized content recommendation of short dramas based on big data mining. The method includes: analyzing short drama features to generate content vectors; analyzing user behavior based on the content vectors to obtain emotional patterns; constructing an interest graph and training an emotional resonance network to form a recommendation model; applying an emotional rhythm algorithm to sort and generate a recommendation list; generating multimodal preview resources; analyzing user interaction behavior to adjust emotional weights and optimize the recommendation effect. This application addresses the problems of existing short drama recommendation systems that overemphasize content type matching while neglecting the emotional experience dimension, lack overall planning of emotional sequences, and have a single content preview method. By constructing a recommendation mechanism based on emotional resonance and a multimodal preview system, it improves the emotional matching accuracy of recommended content and user satisfaction.

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 invention discloses an automobile door hinge production line resource state scheduling system based on the industrial Internet of Things, and the system comprises a production line data module which collects the global real-time data of a production line, and obtains a fusion resource state matrix through the multi-modal feature synchronization and alignment preprocessing operation; the resource analysis module is used for performing dynamic resource calculation on the fusion resource state matrix to obtain hinge production stability characteristics and hinge production fluctuation trend characteristics, and obtaining a dynamic efficiency vector of each resource entity based on the hinge production stability characteristics and the hinge production fluctuation trend characteristics; the decision analysis module is used for constructing a discrete event simulation engine based on the dynamic efficiency vector, performing multi-round Monte Carlo deduction in combination with the current work order queue to generate a resource future conflict probability graph, and generating an optimal scheduling instruction sequence based on the resource future conflict probability graph and in combination with a directed graph network; and the scheduling execution module is used for realizing resource state scheduling of the automobile door hinge production line based on the optimal scheduling instruction sequence.

The invention discloses an intelligent matching method and system for heterogeneous resource interaction information and a public object model, and the method comprises the following steps: S1, carrying out the heterogeneous resource analysis of the GBB-based heterogeneous resource interaction information through structural body analysis, path generation and path information storage, converting type constraint and hierarchical association implied in the information into a structured symbol sequence, and outputting standardized attribute path information; s2, on the basis of standardized path information obtained by heterogeneous resource analysis, through coprocessing of abbreviation word semantic recognition and extension, semantic quantification and type verification, automatic matching is achieved under complex naming rules and structural differences, and an optimal mapping set meeting semantic association and technical feasibility is output; according to the method, a full-process processing mechanism of analysis-extension-matching-verification is constructed, and semantic analysis and structure optimization technologies are combined, so that automatic and accurate matching of heterogeneous data is realized, and the efficiency and precision bottlenecks of traditional manual configuration are solved.