22 results about "Dynamic elasticity" patented technology

The invention belongs to the field of security protection, and particularly relates to a cross-border traffic pool dynamic elastic scheduling system and method, and the method comprises the steps: collecting the real-time quality and traffic parameters of a multi-operator link, and generating a scheduling detection sequence in combination with historical data and the hidden intention of a service appeal text, generating state data through fusion calculation and sending the state data to a cross-border traffic pool dynamic scheduling platform; the flow pool dynamic scheduling model is used for decoupling a time sequence delay coupling relation between parameters, flow consumption fluctuation caused by cross-domain routing convergence is predicted, a feature vector containing a flow excess risk probability and link quality fluctuation is extracted, a target scheduling instruction is generated in response to a cross-domain linkage scheduling condition, and a flow distribution proportion is adjusted or a path is switched. According to the invention, elastic resource allocation and excess risk early warning are realized, and the utilization rate of cross-border traffic resources is improved.

The invention discloses an automatic test method and test platform based on cloud computing, and belongs to the technical field of software testing, and the method comprises the steps: firstly constructing a dynamic elastic resource pool containing a virtualized test node cluster, a tool chain and a distributed data warehouse; after obtaining a performance test request, analyzing data to screen an optimal node combination and tool configuration, and generating a test case set covering a boundary scene and an abnormal path in combination with historical data and reinforcement learning; using an improved genetic algorithm and a load prediction model to disassemble the subtasks and intelligently distributing the subtasks; the progress is tracked in real time through a digital twinborn model, abnormity is recognized, and a multi-stage processing mechanism is activated; and after the test is finished, normalizing the processed data, and generating a panoramic report by means of the analysis model. According to the method, the intelligent level, the execution efficiency, the resource elasticity and the exception handling capacity of automatic testing are improved, and the high-performance testing requirement in a complex scene can be met.

The application relates to the technical field of power system dispatching, and discloses an intra-day forward-looking dispatching fast solving method considering large-scale new energy cluster power generation fluctuation, which comprises the following steps: S1: new energy cluster space-time fluctuation scene generation based on neuron cellular automata, S2: power grid dynamic security domain definition and simplification based on physical information neural network, S3: dispatching fast optimization solving based on model prediction path integral, and S4: dispatching scheme dynamic elasticity and stability evaluation based on the theory of Koopman operator. The new energy cluster space-time fluctuation scene generation method based on neuron cellular automata can effectively generate a space-time scene reflecting the large-scale new energy cluster power generation fluctuation, support uncertainty analysis, has the advantages of high calculation efficiency and scene authenticity, and solves the problem that the traditional statistical model ignores space-time coupling, thereby causing inaccurate scene generation.

The invention relates to the technical field of artificial intelligence security and cloud computing resource management, and discloses an AI reasoning service elastic scaling method and system for an edge cluster, and the method comprises the steps: constructing a dynamic risk file for each hardware computing unit in a computing cluster; distributing the reasoning service request to a target hardware calculation unit of which the risk state is matched with the security demand level; instantiating an independent logic calculation container for each allocated reasoning service request, and destroying the logic calculation container after the reasoning task is executed; and monitoring the resource configuration change of the computing cluster, and updating the risk state of the computing cluster in the dynamic risk file. According to the method, a mixed protection mechanism with logic isolation as a main part and physical reset as an auxiliary part is adopted, and hardware-level state pollution attacks triggered by antagonistic input are effectively defended in a dynamic elastic edge AI reasoning scene on the premise that the elastic scalability is not obviously sacrificed.

The invention relates to the technical field of roadbed continuous compaction detection, and discloses a calibration method of roadbed continuous compaction detection equipment, which comprises the following steps: combining a plurality of rubber pads with different hardness and thickness to obtain a simulation test system; s2, testing the dynamic elasticity modulus of the plurality of rubber cushion layers to verify the rigidity uniformity and continuous variability of the rubber cushion layers; s3, performing in-situ single-point vibration test on the simulation test system, acquiring a steel wheel vibration acceleration signal by means of roadbed continuous compaction detection equipment, preprocessing the acquired signal, and calculating a continuous compaction detection index needing to be calibrated; and S4, taking the mean value of the dynamic elastic modulus of the rubber cushion layer as an equivalent stiffness reference value, and fitting the correlation between the index to be calibrated and the dynamic elastic modulus by adopting a regression analysis method so as to obtain a calibration curve. According to the method, a more accurate and universal calibration result can be provided for roadbed compaction quality detection equipment, the calibration efficiency is improved, and the calibration cost is reduced.

The present application belongs to the field of safety protection, and particularly relates to a cross-border traffic pool dynamic elastic scheduling system and method, comprising: collecting real-time quality and traffic parameters of multiple operator links, combining historical data and implicit intention of business appeal text to generate a scheduling detection sequence, generating state data through fusion calculation and sending to a cross-border traffic pool dynamic scheduling platform; using a traffic pool dynamic scheduling model to decouple the time sequence delay coupling relationship between parameters, predicting the traffic consumption fluctuation caused by cross-domain route convergence, extracting a feature vector containing traffic excess risk probability and link quality fluctuation, generating a target scheduling instruction in response to cross-domain linkage scheduling conditions, and adjusting the traffic distribution ratio or switching the path. The present application realizes elastic resource allocation and excess risk early warning, and improves the utilization rate of cross-border traffic resources.

The invention relates to a network toughness evaluation and elasticity adjustment method based on digital twinning, and belongs to the technical field of communication network simulation and optimization. The method comprises three parts of digital twin network modeling, network toughness quantitative evaluation and an elastic adjustment method. A directed weighted graph is used for representing network topology, and three specific parameters of delay, bandwidth and packet loss probability are introduced to construct a digital twinborn body of an actual network; calculating a key and toughness comprehensive coefficient of the node for evaluating the key degree of the node and evaluating the network toughness; different fault conditions are classified and processed; in a normal condition, Dijkstra is used for rerouting; adjusting a trigger strategy of the directly connected nodes; and an alarm is given independently for abnormal communication loss. According to the method, the network toughness is systematically and quantitatively evaluated, a dynamic elastic adjustment strategy is triggered for a node destruction and paralysis failure scene, and optimization of the network toughness is realized.

The invention relates to a manufacturing system node ALCR strengthening strategy method of a double-layer dynamic Bayesian network, belongs to the field of reliability analysis, and aims to solve the problem that redundant resource allocation is unreasonable due to the fact that a traditional key node equipment strengthening strategy occupies limited resources. A critical value of node equipment capacity redundancy and an inhibitory penalty function of resource overload are considered, and an improved reinforcement strategy (ALCR) based on an optimization theory is provided. The dynamic elasticity evaluation method of the double-layer dynamic Bayesian network is combined to compare the elasticity strengthening effects after different strengthening strategies are strengthened, and the accuracy and effectiveness of the ALCR strengthening strategy are verified. When the equipment average degree is large, compared with other reinforcement strategies, the improved reinforcement strategy based on the optimization theory can ensure that the system has better elastic performance, provides a theoretical basis for further formulating a reliable production strategy and reducing the maintenance cost, and is suitable for popularization and application. And an improvement direction is indicated for further improving the reliability of the node strengthening strategy of the manufacturing system.

The invention discloses an electric power data quality checking method and system based on dynamic elastic scheduling, and aims to solve the problems that in the prior art, centralized scheduling cannot process massive electric power data, the checking time consumption is long, the upper limit of parallel tasks is low, and a traditional database is slow in query. The method comprises the following steps of: segmenting data into a plurality of blocks through data volume estimation, single server processing capacity and maximum allowable check duration, and scheduling a plurality of execution servers to perform parallel processing by a container cloud; a distributed storage architecture is adopted, an LSM tree structure is adopted to store check results, and the storage and query efficiency is optimized in combination with an exclusive check result table, LZ4 and ZSTD dual-mode compression, timestamp column value and other fragmentation strategies. According to the electric power data quality checking method and system, the time consumption of data checking is low, the checking result query speed is high, and the problems of timeliness and result query of data checking in the electric power data are effectively solved.

The invention belongs to the technical field of data processing, and particularly relates to a GIS flange bolt tightening quality judgment method based on torque corner curve analysis, which comprises the following steps of: resampling torque and corner data based on a preset angle step length, and calculating instantaneous tangent rigidity by adopting a Gaussian kernel weighted difference operator, the high-frequency friction noise in the aluminum alloy tightening process is smoothly inhibited; constructing a dynamic elastic reference value based on the linear elastic region characteristics and the hardening coefficient; and calculating a damage accumulation value based on the deviation between the instantaneous stiffness and the reference value, and when the accumulation value exceeds a threshold value, judging that micro-yield occurs and stopping. According to the method, transient viscous sliding interference and real plastic deformation are effectively distinguished through an energy integral idea, the problem of misjudgment caused by no obvious yield point and individual difference of the cast aluminum alloy is solved, and high-precision lossless judgment of the bolt tightening quality is achieved.

This invention discloses a dynamic task scheduling system for space control simulation model computation, comprising a scheduling center, several scheduler nodes, and several executor nodes. The scheduler nodes and executor nodes are deployed on different server clusters. The scheduling center dynamically adjusts task scheduling based on dynamic load balancing technology according to the task scheduling requirements of the space control simulation service, allocating tasks to registered scheduler nodes. The scheduler nodes are used for task production and caching, and trigger the executor center using Remote Procedure Call (RPC) technology. They are also used for dynamic elastic scaling of executor nodes for tasks that cannot be fulfilled. The executor center logs into the scheduling center via heartbeat registration to achieve remote communication between the two. It is also used to decompose tasks and trigger the corresponding executor nodes. The executor nodes execute the corresponding space control simulation model computation tasks.

The application discloses a deep coal bed gas reservoir high brittleness sweet spot area prediction method, system and equipment, relates to the oil and gas and coal bed gas geophysical exploration field, and the method comprises the steps of: taking dynamic elastic modulus as the independent variable, taking coal bed fracture pressure as the dependent variable, adopting a multiple linear regression method to perform fitting, determining a partial regression coefficient, and thereby constructing a brittleness index model; based on original data of a target area deep coal bed gas reservoir, adopting prestack simultaneous inversion technology and rock physical formula to perform inversion and calculation, obtaining a three-dimensional dynamic Young's modulus data body, a three-dimensional dynamic Poisson's ratio data body and a three-dimensional dynamic shear modulus data body, and substituting into the brittleness index model to obtain a three-dimensional brittleness index data body; according to a brittleness index threshold, dividing a region corresponding to the three-dimensional brittleness index data body to determine a high brittleness sweet spot area. The application can improve the accuracy of predicting the high brittleness sweet spot area of the deep coal bed gas reservoir.

The invention discloses a full-automatic control method and system of a pretreatment open-width all-in-one machine, and relates to the field of all-in-one machine automatic control, and the method comprises the steps: firstly obtaining the liquid rate, temperature and operation state data of a fabric in real time, and constructing a fabric state feature vector; and analyzing the vector by using a rheological model, and accurately estimating the dynamic elastic modulus of the fabric in the humid and hot environment. On the basis, the optimal tension reference value matched with the current physical state is dynamically calculated, traditional constant tension setting is replaced, and a motor torque instruction is solved by combining a feedforward and impedance composite control algorithm. Therefore, by sensing the physical property change of the fabric in real time and pre-judging and adjusting the tension threshold value, the problem of dynamic tension mismatching caused by feedback lag and model singleness in the prior art is solved, and dead creases of the high-density fabric in the processing process are effectively avoided.

The invention relates to a device which can be easily integrated into a drying oven or high-temperature furnace (18), and which enables the determination of the dynamic elastic modulus of materials at the desired temperature.

The present application belongs to the technical field of data processing, and particularly relates to a GIS flange bolt tightening quality discrimination method based on torque rotation curve analysis, which comprises the following steps: resampling torque and rotation angle data based on a preset angle step, and calculating instantaneous tangent stiffness by using a Gaussian kernel weighted difference operator to smooth and suppress high-frequency friction noise in the aluminum alloy tightening process; constructing a dynamic elastic reference value based on linear elastic zone characteristics and hardening coefficient; calculating damage cumulative value based on the deviation of instantaneous stiffness and reference value, and determining micro yield and stopping when the cumulative value exceeds the threshold value. The present application effectively distinguishes transient viscous sliding interference and real plastic deformation through the energy integration idea, solves the misjudgment problem caused by the absence of obvious yield point and individual differences of cast aluminum alloy, and realizes high-precision nondestructive discrimination of bolt tightening quality.

This application provides an optimized configuration method for a regional energy system, comprising the following steps: acquiring multi-dimensional basic data of the regional energy system; constructing a dynamically flexible hierarchical optimization model; performing flexible adjustments on a time scale, energy mutual assistance in spatial sub-regions, and dynamic weighting of multi-entity demand based on the multi-dimensional basic data; determining the collaborative optimization boundaries of energy storage and energy, and energy storage and load at different levels, as well as the overall collaborative optimization objectives of energy storage, energy, and load; introducing a capacity configuration sub-model, a real-time scheduling sub-model, and a game arbitration sub-model, combining a multi-entity collaborative game mechanism to resolve disagreements and dynamically adjust parameters to achieve Pareto optimality; integrating a dynamic mapping mechanism of multiple energy storage characteristics into the hierarchical optimization model; and outputting a collaborative optimized configuration scheme for energy storage, energy, and load in the regional energy system based on the collaborative results. This application achieves dynamic adaptability of the optimized configuration scheme for the regional energy system.

The application discloses a kind of digital renminbi and alliance chain interconnection and intercommunication method, based on dynamic elasticity scalable prophet, to form prophet network with digital renminbi operating agency, pass through the architecture to open block chain and digital renminbi system, help digital renminbi in alliance chain network Legal, orderly, compliance circulation, solve the problem that block chain obtains digital renminbi data, realize the interconnection and intercommunication of block chain and digital renminbi, reduce the cost that block chain directly changes into access digital renminbi system, expand the application scene of digital renminbi block chain system.In addition, the present application also improves the throughput of prophet returning digital renminbi data to block chain and the resource utilization efficiency of digital renminbi operating agency, solves the problems of low throughput and low resource allocation efficiency of the prophet network formed by operating agency.

In order to mainly solve the technical problems, the invention provides a dynamic elastic doctor scheduling algorithm and system method based on multi-objective optimization, and the method comprises the following steps: 1, elastic layered architecture: decomposing a scheduling problem into a fixed shift layer and an elastic response layer, and giving consideration to both stability and flexibility; 2, multi-objective collaborative optimization: introducing fuzzy logic to dynamically adjust the weight of an objective function to adapt to different scenes (such as normal vs. Emergency); and 3, a man-machine cooperation mechanism: allowing doctors to improve acceptability by feeding back iterative optimization algorithm preferences. Through the advantages, the dynamic elastic doctor scheduling algorithm based on multi-objective optimization can provide an efficient, flexible and humanized doctor scheduling solution.

The present application relates to the field of geology system algorithm, and particularly relates to a method for determining excess silicon, comprising: sample screening and data processing, dynamic elastic network regression modeling, land-derived detrital silicon Si 碎屑 Calculation and excess silicon Si 过量 Correction, the present application sets up the calculation model of Si 碎屑 , introduces TOC as a covariant, captures the relationship between detrital silicon and organic matter, obtains the coefficients a, b and intercept c through dynamic elastic network regression fitting of sample data by MATLAB. Dynamic elastic network can effectively select important features and reduce model overfitting. The model successfully solves the problems of non-representativeness of background ratio and negative value of excess silicon in the traditional method through double-parameter dynamic fitting, dynamic elastic network regularization and double verification mechanism.

This application discloses a fully automatic control method and system for a pre-processing flat-width integrated machine, relating to the field of integrated machine automatic control. First, it acquires real-time data on the fabric's liquid content, temperature, and operating status to construct a fabric state feature vector. Then, it uses a rheological model to analyze this vector and accurately estimate the dynamic elastic modulus of the fabric under humid and hot conditions. Based on this, it dynamically calculates the optimal tension reference value adapted to the current physical state, replacing the traditional constant tension setting, and combines a feedforward and impedance composite control algorithm to solve the motor torque command. By sensing changes in fabric properties in real time and predictively adjusting the tension threshold, it solves the dynamic tension mismatch problem caused by feedback lag and a single model in existing technologies, effectively avoiding the formation of dead creases in high-density fabrics during processing.

The present invention relates to a method and system for allocating a frequency spectrum (100) to users of a dynamic elastic optical network, taking into account contiguity and continuity constraints. The method comprises: storing, in a database (110), data of the optical network topology, such as interconnected nodes, links and capacities of each link; storing, in the database, user information, such as source and destination nodes, required traffic load and paths; classifying users into categories based on their bandwidth requirements in frequency slot units (FSU); partitioning the frequency spectrum of each link into areas (410, 420) associated with each user category; and allocating contiguous FSUs (411) or adjacent contiguous FSUs (412) in the area (410) corresponding to the user category.

The application discloses a kind of dynamic elastic resource expansion power station computing power server, it is related to computing resource management technical field, including distributed state perception acquisition module, data pre-processing and structured construction module, feature extraction and risk quantification analysis module, deep learning intelligent evaluation module and dynamic risk regulation and rhythm management module:Distributed state perception acquisition module, in the process of water power dispatching task live migration, through the distributed state perception system deployed in the central dispatching control platform of power station computing power server, continuously, real-time acquisition the running state of each key node in migration link and link quality parameter data.The application realizes risk identification and intelligent regulation in the process of water power dispatching task live migration by the dynamic elastic resource expansion mechanism of multi-module cooperation, improves the perception ability to node state and link exception, discriminates migration loss risk in combination with deep model, and dynamically adjusts dispatching strategy, guarantees task continuity and operation safety.