855results about How to "Guaranteed reasonableness" patented technology

The invention discloses a charging pile power regulation and control method and system, and particularly relates to the technical field of charging pile management, data is collected from a multi-dimensional data source and summarized to form a preliminary information set, and a standard information set is obtained through format standardization processing; feature data of the charging pile are extracted based on the standard information set, and charging task analysis and resource occupation analysis are carried out respectively; inputting the analysis result into a pre-trained machine learning model to generate a charging priority coefficient; constructing a priority matrix, and dividing the charging piles into high priorities and low priorities according to the charging priority coefficients; and finally, dynamically adjusting a power distribution strategy according to the priority type, optimizing low-priority task power distribution while meeting high-priority task requirements, and improving the operation efficiency and the resource utilization rate of the charging station. According to the method, the real-time operation state and the charging task characteristics of the charging piles are combined, the power distribution strategy is dynamically adjusted, the priority division and power distribution proportion of the charging piles are adjusted in real time, and the self-adaptive capacity of operation of the charging station is improved.

The invention provides a community management method and system based on an unmanned aerial vehicle, electronic equipment and a storage medium, and relates to the field of community management. The method comprises the steps of obtaining an initial inspection task of an unmanned aerial vehicle cluster and planning an inspection route, and controlling the unmanned aerial vehicle cluster to execute inspection operation to obtain multi-source inspection data. And constructing a community portrait based on the inspection data, identifying community management hidden dangers through a classification reasoning model, and generating an early warning event and a processing task. A processing task is decomposed into hierarchical sub-tasks by utilizing an ontology reasoning framework, a task execution main body is selected, and a task set is generated. And a multi-Agent reinforcement learning framework is adopted to carry out space-time collaborative arrangement on the task set to form an overall collaborative scheme, the overall collaborative scheme is converted into an interpretable scheduling decision instruction, and finally the unmanned aerial vehicle is controlled to execute the task. According to the technical scheme, the emergency response speed of security and protection and the capability of coping with complex conditions are improved.

The invention discloses a low earth orbit satellite Internet of Things communication method and system based on a dynamic block chain, and the method specifically comprises the steps: taking at least one ground station as a consensus node in each network partition, forming a consensus network, and selecting a main node from a plurality of consensus nodes of each consensus network through employing an RBFT algorithm; a satellite transit algorithm is adopted to predict transit information of each low-orbit satellite, and the low-orbit satellites passing through any consensus network are set as accounting nodes of the consensus network according to the transit information; the method comprises the following steps: acquiring a service request of a satellite communication terminal, forwarding the service request to a main node of a consensus network to which the service request belongs through a low-orbit satellite of a transit satellite communication terminal, performing verification and priority ranking on the service request according to the main node, and if the verification is passed, performing broadcast and consensus verification on all nodes of the current consensus network. According to the invention, the communication efficiency and safety of the low-orbit satellite Internet of Things are improved, and reliable technical support is provided for satellite Internet application.

The invention relates to the technical field of power grid planning, in particular to a charging pile planning method based on dynamic analysis. The method comprises the following steps: obtaining electric vehicle use data in a target area, and carrying out charging demand prediction analysis according to the electric vehicle use data to obtain a charging demand prediction model; based on the charging demand prediction model, performing multi-scene simulation to obtain charging demand distribution map data, multiple scenes including different traffic flows, different driving modes and different charging demand scenes; obtaining geographic information data of the target area; and constructing a spatial analysis model according to the geographic information data, and evaluating the candidate position of the charging pile according to the charging demand distribution map data, thereby obtaining position suitability score data. According to the method, different scenes are simulated, so that the adaptability and robustness of planning are enhanced.

The invention discloses a method suitable for adding a control shunt under multiple scenes in a demand response execution process, and the method comprises the steps: obtaining real-time load data, historical load data, environment parameter data and user behavior data, and carrying out the processing through a tensor decomposition method and a support vector machine, and obtaining a scene feature vector and a scene type identifier; real-time load data and system constraint data are combined, a fuzzy comprehensive evaluation method and a graph neural network are adopted for processing, and a shunt response capability matrix and a control constraint matrix are obtained; processing by adopting a multi-objective optimization method to obtain an optimization objective function set, a weight coefficient matrix and a constraint condition set; and processing by adopting a genetic algorithm and a dynamic programming method to obtain a control strategy matrix and an execution time sequence vector. According to the invention, accurate control and dynamic optimization in the demand response process can be realized, and the execution efficiency and reliability of the control strategy are improved.

The invention discloses a complex terrain wind field numerical simulation method considering turbulence anisotropy, and the method comprises the steps: considering the turbulence anisotropy of an inflow boundary, and determining the condition type and parameters of the inflow boundary; acquiring ground roughness information of the complex terrain, and correcting a wall surface function; obtaining high-precision topographic data, determining a computational domain range, and generating a computational domain grid; on the basis of an inflow boundary turbulence retentivity principle and a leeward slope flow separation characteristic, a turbulence model closing coefficient is corrected; and the corrected linear pressure strain RSM model is adopted to simulate a complex terrain wind field value, and complex terrain wind field flow field information is obtained. According to the method, the inlet boundary and leeward slope turbulence anisotropy are considered, the wall function is corrected, meanwhile, the complex terrain modeling and grid generation mode is simplified, and the simulation precision is effectively improved.

The invention relates to the technical field of multi-path information processing, and provides a multi-path optimization method, device and system for network routing, and the method comprises the steps: obtaining network node information, obtaining a plurality of available paths based on the network node information, evaluating all available paths, and obtaining network bandwidth data and an initial weight; adjusting the initial weight to obtain an initial path weight and a path priority table, distributing and identifying data packets of network flow by using the path priority table, obtaining a flow data packet with a path identifier, and adjusting the initial path weight after obtaining a flow load log and network delay data based on the flow data packet; and generating a flow scheduling scheme to update the path priority table. Through obtaining network node information and utilizing a bandwidth evaluation algorithm, initial path evaluation reflecting network conditions is generated, and through real-time data feedback of a dynamic monitoring module, a flow scheduling scheme capable of carrying out adaptive adjustment at any time is generated, so that the defects of the prior art in the aspect of dynamic adaptability are improved.

The invention discloses a partial discharge positioning method, system and device based on an acoustic-electric combined signal, and relates to the technical field of electrical device detection, and the method comprises the steps: deploying a plurality of sensor nodes based on a target electrical device, and collecting an electromagnetic signal and a sound wave signal generated by partial discharge at the same time; calculating a preliminary positioning result of the partial discharge source based on the collected acoustic-electric combined signal; environment parameter data, historical operation data and electrical equipment structure information in the electrical equipment are collected and input into a preset error correction model, and a corresponding error correction interval is obtained; when a certain preliminary positioning result exceeds the corresponding error correction interval, obtaining a timestamp corresponding to the preliminary positioning result; performing multi-source information fusion positioning based on the environmental parameter data, the historical operation data, the electrical equipment structure information and the corresponding timestamps, and analyzing and determining final positioning coordinates of the partial discharge source; the accuracy of partial discharge signal positioning is improved, and the positioning efficiency is improved.

The invention provides a segmental bridge wind vibration performance evaluation method and system, and relates to the technical field of segmental bridge wind vibration performance. Laser scanning is used for obtaining geometric parameters of a segmental bridge and collecting material characteristics, the geometric parameters and the material characteristics are imported into finite element software, a basic model is established, and boundary conditions are set; modal analysis is executed in finite element software, the natural vibration frequency and the vibration mode are calculated through a Lanczos method, and basic data are provided for wind load analysis; simulating a wind load by using a Davenport wind spectrum, setting a wind speed and a wind direction, and then applying the wind speed and the wind direction to the model; finally, the wind load condition is adjusted, the performance of the bridge under different wind loads is tested, and the displacement, acceleration and stress distribution of the bridge are analyzed and calculated through dynamic response to complete the wind vibration performance evaluation of the segmental bridge.

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention discloses an intelligent construction scheme optimization system based on building decoration, and relates to the technical field of building decoration. The system comprises four modules, and the constructor selection module is used for selecting a construction principal according to the performance value of the constructor. The building material monitoring module is used for dividing the storage area into a plurality of monitoring areas and marking the monitoring areas as deviation or overlapping areas according to the area overlap ratio; calculating a zone condition value, and marking the zone condition value as a suitable or non-suitable zone; and calculating a storage score value, and generating a storage early warning signal or a storage qualified signal. The construction safety supervision and analysis module is used for monitoring a construction site in real time and generating a construction early warning signal; calculating an operation monitoring value; and calculating a construction environment coefficient, and generating an environment control abnormal signal or an environment control normal signal. The construction progress risk monitoring module is used for collecting delay data, calculating progress influence values and generating influence signals of different levels; and adjusting the progress plan. According to the system, through intelligent management, the construction efficiency and safety are improved, and the construction cost is reduced.

The invention discloses an intelligent auxiliary system and method for regular inspection of a pressure vessel, and aims to improve the intelligence, efficiency and accuracy of inspection of the pressure vessel. The system comprises a data acquisition module, a data processing module, a risk assessment module, an inspection plan generation module, a report generation module, a remote monitoring module and a historical data management module. Operation parameters of the pressure vessel are collected in real time through the sensor, the data processing module carries out elimination and trend analysis on abnormal data, and the risk assessment module assesses the operation state of the pressure vessel through machine learning and a fuzzy logic algorithm. The system dynamically generates an inspection plan according to an evaluation result and adjusts an inspection period through Bayesian updating, and a generated inspection report has a digital signature to ensure safety. The historical data management module stores and analyzes long-term data and supports trend prediction of equipment health conditions, and the remote monitoring module provides real-time state checking and early warning.

The invention relates to the technical field of textile, in particular to a digital textile equipment management method based on big data, and the method comprises the following steps: 1, an equipment connection and data initialization stage: checking the data interface type of equipment in each link of a textile process, and connecting the data interface type to a workshop data collection network, establishing an electronic file for each device, setting initial data acquisition parameters, and carrying out pre-operation test and calibration on the devices; 2, a production process monitoring and data recording stage; according to the scheme, the equipment performance evaluation model is established by using a big data analysis technology, multiple factors such as energy consumption efficiency, a production stability index and an equipment failure rate trend are comprehensively considered, and the equipment performance is comprehensively and accurately evaluated, so that sudden equipment failures are effectively avoided, the risk of production interruption is reduced, and the production efficiency is improved. The overall management efficiency and the operation stability of the equipment are improved, the continuity of the production process is guaranteed, and the cost increase caused by equipment faults is reduced.

The invention discloses a garbage truck real-time monitoring and remote scheduling method based on the Internet of Things, and the method comprises the following steps: S1, collecting the real-time data of the operation state of a garbage truck, and carrying out the preprocessing of the real-time data; s2, constructing a task prediction model based on an improved adaptive graph neural network, and generating a preliminary task distribution matrix and a path planning scheme; s3, optimizing the preliminary task allocation matrix and the path planning scheme by adopting an improved PPO algorithm; s4, the optimized task allocation matrix and the path planning scheme are sent to a garbage truck vehicle-mounted terminal, and the task completion rate and the path deviation value are calculated; s5, the operation state of the garbage truck is monitored in real time, and the monitoring result and the operation state data are transmitted to the cloud Internet of Things platform; and S6, dynamically updating the scheduling instruction. According to the method, the Internet of Things, the adaptive graph neural network and the improved PPO algorithm are fused, intelligent scheduling and real-time optimization of the garbage truck are realized, and the method has the advantages of high efficiency, stability and low-cost operation.

The invention discloses an urban inland inundation prediction monitoring method, system and device and a medium thereof, and the method comprises the steps: obtaining historical ponding distribution information and a flood prevention starting plan of a target urban monitoring region based on collected rainfall prediction data and rainfall early warning levels; acquiring current flood prevention drainage facility information and drainage facility state results according to the historical ponding distribution information and the flood prevention starting plan; in the predicted urban inland inundation deduction model, performing urban inland inundation simulation calculation based on rainfall prediction data, historical ponding distribution information, a flood prevention starting plan and a corresponding drainage facility state result to obtain an urban inland inundation simulation result; generating a plurality of waterlogging and ponding monitoring units based on the urban waterlogging simulation result, and collecting corresponding waterlogging and ponding monitoring data; optimizing the urban inland inundation deduction model when the urban inland inundation simulation result and the inland inundation ponding monitoring data meet deviation judgment adjustment conditions; according to the invention, the processing efficiency of urban flood prevention and typhoon prevention emergency scheduling is improved.

The embodiment of the invention discloses a network security alarm processing method and device, electronic equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a network security alarm; retrieving a target text vector associated with the network security alarm in a network security domain knowledge base; the network security domain knowledge base is a knowledge base constructed after vectorization processing is carried out on network security corpora; based on the target text vector, an alarm vector corresponding to the network security alarm, a preset tool library and a large language model, obtaining a research and judgment processing flow of the network security alarm; executing a research and judgment processing flow; and obtaining a research and judgment result of the network security alarm based on an execution result of the research and judgment processing flow.

The invention belongs to the field of track foreign matter detection, and discloses a track foreign matter detection method based on a YOLO algorithm. Comprising the following steps: collecting track foreign matter images to form a data set, and performing sample expansion processing and label processing on each image in the data set so as to obtain a sample set; a channel attention mechanism and a direction perception mechanism are added into the YOLOv5, constraint conditions are set, and then an improved YOLOv5 algorithm is obtained and marked as a G-YOLOv5 model; a G-YOLOv5 model is pre-trained by using the sample set, and a trained G-YOLOv5 model is obtained; a real-time image of the track is collected and processed, the processed image is imported into the trained G-YOLOv5 model, and a real-time detection report is obtained; the obtained real-time detection report is arranged on a visual interface, and efficient track foreign matter detection based on the YOLO algorithm is achieved.

The invention discloses a CFD-based liquefied natural gas after-condenser structure optimization method and device. The method comprises the steps that an initial model is established based on an assembly drawing, and geometric pretreatment is completed; extracting a fluid channel, segmenting and selecting a computational domain, and carrying out local encryption on a key region; generating a polyhedral grid by using a grid division tool, and completing grid independence verification; importing the polyhedral mesh into a solver, and carrying out model setting; boundary and wall surface conditions are set, and solver parameters are configured; setting an initial flow field through a hybrid initialization method, and establishing a flow monitoring window and a temperature monitoring window to adjust simulation until convergence; analyzing the temperature cloud picture and the flow vector diagram, and adjusting the structure of the baffle plate; the tower diameter and the height of the filler layer are adjusted according to a physical quantity field change curve of the filler layer, and the performance of the recondenser is continuously improved. The problem of how to deeply study the flow heat transfer rule in the after-condenser and obtain the flow field distribution characteristics is solved, so that the working performance of the after-condenser is improved.

The invention discloses a multi-agent path planning method, device and equipment, and the method comprises the steps: dividing a map according to first grids of a preset size, carrying out the global planning of all agents on the map, and generating a global path, the global path being a road section passing through a plurality of first grids from a starting point to a target point; on the basis of each path section of the global path, local planning is conducted on all agents, a local path is generated, and each path section is a road section formed by the center points of every two adjacent first grids; real-time data are obtained by monitoring changes of dynamic obstacles and dynamic targets in a map in real time, and the local path and / or the local path are / is updated and planned according to the real-time data to obtain an updated path. Potential collision risks can be quickly found, obstacle avoidance measures can be taken in time, and the safety of a multi-agent system and the smooth completion rate of tasks are improved.

The invention relates to a three-dimensional rapid modeling method based on section contour multi-feature constraint, and the method comprises the steps: extracting preset key points based on the drilling space information data of a geologic body section, and constructing a discrete point set of the geologic body section; searching a starting point pair for the discrete point set, and unifying the bypassing direction of adjacent point sets; constructing an initial adjacent contour point set based on the starting point pair and the bypassing direction, performing multi-feature constrained auxiliary point interpolation on the initial adjacent contour point set, and constructing a one-to-one corresponding point set; carrying out interlayer interpolation on the contour point set after the auxiliary point interpolation; and based on the shortest diagonal constraint, carrying out triangulation network splicing on the contour point set after interlayer interpolation. According to the method, the property and the inlaying process of the basic triangular patch can be considered, reconstruction of sparse contour line discrete points with low shape similarity and different points is realized, and the problem of complex surface reconstruction under a sparse profile is effectively solved.

The invention relates to a method and a device for tracking a dynamic resource dependency relationship and terminal equipment. The method comprises the following steps: acquiring cloud resource dependency data of a cloud service platform and / or a data center in real time; constructing a cloud resource dynamic dependency graph according to the cloud resource dependency data; detecting the cyclic dependence of the cloud resource dynamic dependence graph by adopting a depth-first search algorithm to obtain a cyclic dependence detection result; and using a TGCN algorithm to predict the future cyclic dependence of the cloud resource dynamic dependence graph to obtain a cyclic dependence prediction result. According to the method, a real-time cloud resource dynamic dependency graph is constructed, a depth-first search algorithm and a TGCN algorithm are adopted to process the cloud resource dynamic dependency graph to obtain a cyclic dependency detection result and a cyclic dependency prediction result, and a basis is provided for determining corresponding resource cyclic dependency prevention measures and processing strategies. And data is provided for effective cloud resource management and optimization, so that problems and risks caused by cyclic dependence are reduced, and the reliability of cloud services is improved.

The invention discloses a self-adaptive resource scheduling method for improving cluster reconstruction efficiency, and relates to the field of resource scheduling distribution, and the method comprises the steps: monitoring the resource use data of each node in a cluster in real time through a monitoring agent, and obtaining the health state of the node through a heartbeat mechanism; collecting input task requests, predicting the resource demand quantity of each task, and performing preliminary queue processing on the tasks to obtain a task queue group; setting a resource competition constraint according to the task queue group and the resource use data and the health state of each node, obtaining dynamic resource scheduling corresponding to each task by using an optimization algorithm, and allocating the tasks to each node; a resource scheduling dynamic graph is constructed, a visual interface is set, and the resource scheduling dynamic graph is arranged on the visual interface and used for displaying resource scheduling, providing a user-friendly interface and realizing high-efficiency scheduling of adaptive resources in a cluster reconstruction process.

The invention relates to the technical field of safety monitoring of deep foundation pit construction adjacent to railways, and particularly discloses a safety monitoring device and method for deep foundation pit construction adjacent to railways. The system comprises a supporting structure safety analysis module, a settlement risk analysis module, a train passing construction safety evaluation module, a geological level risk evaluation module, a displacement level risk evaluation module, a database and a construction process construction safety evaluation module. Whether the construction of the deep foundation pit is safe or not is analyzed from the two levels of the safety change condition of the deep foundation pit when a train passes and the safety change condition of the deep foundation pit in the long-term construction process, that is, the deep foundation pit risk is automatically monitored from the four levels of the foundation pit supporting structure, the rail settlement risk, the foundation pit geology and the foundation pit displacement; the method avoids neglecting the instant safety risk, helps to evaluate the instant influence on railway facilities, and can grasp the overall safety trend, thereby helping to adjust the construction strategy and maintenance measures in time.

The invention provides a carbon dioxide phase change blasting numerical simulation method based on an FDEM. The carbon dioxide phase change blasting numerical simulation method comprises the following steps that a carbon dioxide adiabatic expansion p-V relation is determined according to a Span-Wagner fluid model; establishing a finite-discrete element (FDEM) numerical model, and setting a non-reflection boundary; determining mesoscopic parameters in the FDEM model according to the physical and mechanical parameters of the rock mass; and applying a carbon dioxide phase change blasting load, and solving a finite-discrete element (FDEM) model. According to the method, the Span-Wagner fluid model recommended by the American national standard is adopted to replace a traditional ideal gas model to calculate the adiabatic p-V relation of the carbon dioxide, the description of the carbon dioxide pressure is closer to the reality, the value of the FDEM mesoscopic parameter is associated with the physical and mechanical indexes of the rock mass, a theoretical basis is provided, the reasonability of the parameter value is ensured, and the method has the advantages of high reliability and high reliability. Therefore, a carbon dioxide blasting numerical simulation result is close to an actual application result, and the accuracy of the numerical simulation result is improved.

The invention relates to a low-voltage power distribution network fragile area identification method. The method comprises the steps of obtaining related power data of a low-voltage power distribution network; in combination with a complex network theory, constructing a node importance evaluation index model reflecting the structural vulnerability of the power distribution network, and performing calculation; constructing a state vulnerability evaluation index model reflecting the operation state of the power distribution network and calculating; performing weighting by using a weight analysis method, and performing weighting on the node importance evaluation index and the state vulnerability evaluation index to obtain subjective and objective weights of each index; coordinating subjective and objective weights according to Nash equilibrium of the game theory, and calculating a comprehensive weight; comprehensive vulnerability is calculated by using a TOPSIS algorithm improved by grey relational degree, and vulnerability grades are divided according to Euclidean distance; and constructing a routine and fault determination process, distinguishing routine vulnerability assessment and emergency vulnerability assessment, and outputting node, line and region vulnerability levels. The method can improve the accuracy of low-voltage power distribution network fragile area discrimination, thereby improving the reliability and safety of the power distribution network.

The invention relates to a vehicle wire harness arrangement scheme determination method and device, equipment and a medium. The method comprises the following steps: determining a system schematic diagram of a vehicle wire harness in a target vehicle according to electric device attribute information of each piece of electric equipment in the target vehicle and vehicle wire harness topological information of the target vehicle; according to the system schematic diagram and the electrical device position information of each electrical device in the target vehicle, determining a preliminary arrangement scheme of the vehicle wire harness; and according to the initial arrangement scheme, sequentially carrying out space checking and dynamic stress simulation on the vehicle wire harness, and determining a target arrangement scheme of the vehicle wire harness. By adopting the method, the stress requirement of the target vehicle can be comprehensively met, and a more accurate and reasonable wiring harness arrangement scheme can be determined.

The invention provides a data defect detection and correction method for an electric power scene, and the method comprises the steps: collecting the data of a sensor, extracting spatial-temporal features, constructing a global high-dimensional feature representation, and carrying out the dimension reduction, thereby obtaining a feature vector after the dimension reduction; time sequence anomaly detection and space anomaly detection are carried out on the feature vectors after dimension reduction, detection results are synthesized, and a comprehensive anomaly score is calculated; classifying the abnormal data according to the comprehensive abnormal score, and constructing a self-adaptive correction model to preliminarily correct all the abnormal data and iteratively optimize the model; monitoring the corrected data in real time, calculating an anomaly detection error, updating parameters of anomaly detection and correction models, and applying the parameters to the models; the optimal learning rate is dynamically determined to accelerate the convergence of the model, the abnormal detection and correction model parameters are migrated and updated, the model is dynamically updated, and the performance index of the system is monitored in real time, so that the operation safety and stability of the power system are improved.

The invention relates to a construction method of a potential sliding surface model for two-dimensional slope stability analysis, belongs to the field of engineering disaster prevention and reduction and computer aided design, and particularly provides a construction method of a two-dimensional slope potential sliding surface model in a principal stress deflection mode. According to the method, principal stress deflection is combined with the most unfavorable shearing direction by means of a side slope shear failure physical and mechanical model, a potential sliding surface model capable of effectively showing the actual sliding surface form when the side slope slides is constructed, meanwhile, known boundary conditions of a lower sliding-out point and an upper sliding-out point of the sliding surface are introduced, and the sliding surface is constructed. The method achieves the dual goals of reasonability and simplicity of potential sliding surface generation, further reliably improves the accuracy of slope stability evaluation under complex conditions, further provides powerful scientific guidance for slope collapse range definition and reinforcement area determination, and improves the slope stability evaluation accuracy. The implementation method has the advantages of being high in practicability, wide in application range, good in universality, high in calculation efficiency and the like.

The embodiment of the invention discloses a computing resource scheduling method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a current idle computing resource quantity and a historical idle computing resource quantity corresponding to service equipment, and carrying out the scheduling of computing resources based on the historical idle computing resource quantity and the current idle computing resource quantity, and determining a resource scheduling configuration amount for the service equipment, and performing task scheduling allocation on the service equipment based on the resource scheduling configuration amount. According to the embodiment of the invention, the real-time accuracy of the idle resource scheduling configuration quantity which can be used for scheduling currently by the service equipment is ensured, and then the task scheduling allocation is dynamically performed through the real-time and accurate resource scheduling quantity, so that the idle calculation resource quantity can be ensured to reach a relatively high utilization rate at any time; therefore, the rationality of resource allocation is ensured.

The invention provides a hydraulic fracturing pressure relief method for a multi-layer thick and hard top plate of an extra-thick coal seam. The method comprises the steps that the rock stratum occurrence of the multi-layer thick and hard top plate is obtained through a top plate drilling method; based on a rock mechanics experiment method and a roof peeping method, the stability of the multi-layer thick and hard roof is evaluated, and a fracturing target layer in the multi-layer thick and hard roof is judged; directional drill holes are formed in the fracturing target layer according to the rock stratum occurrence; the fractured target layer is subjected to fracture forming in the directional drilling process through abrasive jet and staged fracturing; and the crack expansion range of the fractured target layer is monitored in real time based on the in-hole micro-seismic monitoring method, and fracturing construction parameters are dynamically adjusted according to the crack expansion range. According to the hydraulic fracturing pressure relief method for the multi-layer thick and hard roof of the extra-thick coal seam, by means of rock stratum testing before fracturing, determination of fracturing construction key parameters and monitoring after fracturing, the good pressure relief effect of the multi-layer thick and hard roof is guaranteed, and effective prevention and control of strong mine pressure disasters of the multi-layer thick and hard roof are achieved.