46results about How to "Realize a reasonable distribution" patented technology

The invention provides a large model content generation auditing method and system based on man-machine collaboration, and relates to the technical field of large models, and the method comprises the steps: deconstructing the generation process data of to-be-audited content, constructing a content risk propagation map, mapping a multi-level auditing strategy library, and recognizing an uncertainty region needing manual intervention. And obtaining manual auditing judgment and correction operation, forming auditing knowledge precipitation and perfecting an auditing strategy library. According to the method, the content risk source can be accurately positioned, the auditing efficiency is improved, a closed-loop optimized man-machine collaborative auditing mechanism is formed, the misjudgment rate is effectively reduced, and the large model content security is improved.

The invention relates to a virtual power plant optimization scheduling method and system. The method comprises the following steps: establishing an operation model of a multi-type adjustable resource main body; constructing a master-slave game model of the aggregator and the resource main body, wherein the master-slave game model comprises an upper-layer model taking the aggregator as a leader and a lower-layer model taking the resource main body as a follower; solving a master-slave game model of the aggregator and the resource main body to obtain an optimal compensation price strategy and an optimal response power strategy, and constructing an optimal power scheduling plan according to the optimal response power strategy; the optimal power scheduling plan is used for being issued to each adjustable resource main body for execution so as to realize optimal scheduling of the virtual power plant. According to the method, the participation enthusiasm of the resource main body can be stimulated, the user participation degree can be improved, the scheduling instruction execution rate can be improved, the model accuracy can be improved, the cooperative capability of heterogeneous resources can be improved, and the overall operation economy and stability of the virtual power plant can be improved.

The invention relates to an artificial hail suppression operation method, device and equipment and a medium. The method comprises the steps of performing data fusion processing on multi-source meteorological monitoring data, airspace control information, an operation point resource state and protection target information to generate a dynamic operation situation map; constructing a multi-target robust optimization model based on the dynamic job situation map; an improved multi-objective evolutionary algorithm is adopted to solve the multi-objective robust optimization model, and a Pareto optimal solution set is obtained; performing multi-attribute decision on the Pareto optimal solution set based on the real-time preference weight, and generating an optimal operation scheme meeting actual requirements; and analyzing the optimal operation scheme to generate a specific operation instruction. By adopting the method, the limitation that traditional artificial hail suppression operation depends on experience decision can be effectively broken through, the operation blindness is reduced, the reasonable distribution of operation resources is realized, the protection effect of important areas is improved, the operation cost and disaster loss are reduced, and the scientization, precision and high-efficiency level of the artificial hail suppression operation is remarkably improved.

The present application relates to the technical field of energy. The present application relates to a multi-power full-time energy tracking energy storage system. It comprises a data effective reservation unit, a PCS matching unit, a VSG control working unit, a parameter updating simulation unit and a simulation parameter reservation unit; the data effective reservation unit is used for collecting load power data, and simultaneously performing effectiveness analysis on the load power data; according to the analysis result, effectiveness reservation is performed; the PCS matching unit is used for establishing a PCS group, and simultaneously performing working parameter analysis on the multi-power PCS in combination with historical load power data in the PCS group; through the combination of the reserved real-time load power data and the PCS group, multi-power PCS efficiency value evaluation is performed, the predicted efficiency value of each multi-power PCS under the condition of real-time load power data can be obtained, the multi-power PCS with the highest predicted efficiency value is selected as the working parameter for input, working mode switching is performed, and the overall efficiency of the system can be improved.

The invention discloses an uplink service message identification processing method and device, a terminal and a medium. The method comprises the following steps: acquiring core feature information corresponding to an uplink service message; obtaining a target message core data structural body according to the core feature information; obtaining a PDU session identifier corresponding to an uplink service message based on the target message core data structure body; obtaining a QoS flow identifier based on the PDU session identifier and the target message core data structure body; based on the QoS flow identifier, obtaining an uplink service message after scheduling processing; performing query processing on the QoS flow identifier to obtain a target packet data convergence protocol instance; and completing a QoS identification processing flow of the uplink service message based on the target packet data convergence protocol instance. The invention aims to realize rapid QoS identification, classification and processing of the uplink service message, improve the message processing efficiency and accuracy, and reduce the system resource overhead.

The invention provides an energy efficiency optimization algorithm for a low-power wide area network (LPWAN), and aims to reduce the energy consumption of LPWAN equipment in a data transmission process and prolong the service life through adaptive data rate adjustment and a micro machine learning (TinyML) technology. The algorithm core comprises a self-adaptive data rate adjustment mechanism, and the transmission rate is dynamically adjusted according to the real-time link quality index and the signal strength. A TinyML model is integrated for local data processing and intelligent decision making, and the data uploading amount is reduced; according to the intelligent dormancy awakening strategy, energy consumption use of equipment is predicted and optimized according to an equipment use mode; and a multi-parameter optimization scheduling algorithm is adopted, and signal quality, equipment electric quantity and environmental factors are integrated for scheduling. In addition, the security of data transmission and user privacy protection are also considered, and a lightweight encryption technology is adopted. The practical application test in various LPWAN technologies verifies the effectiveness of the algorithm, realizes the obvious reduction of energy consumption and the prolonging of the service life of equipment, and has high expandability and adaptability.

The application relates to the technical field of aluminum alloy structure design, and discloses an aluminum alloy net shell structure design method and system based on a genetic algorithm. The method receives design requirement parameter input by a user, including span, height and load conditions of the net shell structure; divides the net shell structure into multiple design units corresponding to nodes or rod pieces; obtains historical performance data of aluminum alloy material, such as strength, rigidity and durability, from a database; determines the importance level and constraint level of each design unit based on the above data; generates an initial population containing multiple design schemes by using a genetic algorithm; iteratively executes selection, crossover and mutation operations to optimize the design individual; collects structure response data such as stress, strain and displacement in real time in the iteration; confirms whether a preset constraint condition is violated based on the data, and adjusts the genetic algorithm parameter if the constraint condition is violated; and outputs an optimal design result and generates a structure analysis image for the user to view.

This invention provides a GPU resource allocation method, apparatus, electronic device, and storage medium. The method includes: in response to an inference task request, determining an execution server among several servers to execute the inference task request; wherein multiple service models of inference services awaiting GPU allocation are deployed in the memory of the several servers, each server deploys a GPU management unit for allocating GPUs to the inference service, and the execution server deploys a target inference service required for executing the inference task; and allocating GPUs to the target inference service through the GPU management unit. This method avoids latency caused by thread start-up and shutdown by pre-deploying the service models of the inference service in the server's memory, placing them in a state of being started but awaiting activation. The method of this invention can significantly reduce the response time of inference services, providing a better user experience.

This invention provides a method and system for optimizing downhole communication links based on self-organizing networks, relating to the field of communication link technology. The method includes acquiring communication node information, constructing a network topology, and determining network characteristic parameters; constructing a link quality prediction model to evaluate link quality; performing dynamic network partitioning and establishing a node priority ranking table to select the optimal transmission path; and real-time monitoring of link status, triggering node self-organizing reconfiguration when necessary. This invention can improve the connectivity, stability, and transmission efficiency of downhole communication networks, reduce communication latency, and enhance the safety of downhole operations.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

The application relates to a power grid data processing method, device, equipment, readable storage medium and program product. The method comprises the following steps: obtaining service data generated by interaction of each subject unit in a source grid-load-storage coordination system; distributing the service data to corresponding main processing node groups based on corresponding service scenarios of the service data; the main processing node groups comprise at least two main processing nodes, each main processing node is pre-configured with a data processing algorithm and a resource allocation strategy matched with the corresponding service scenario; the load state of each main processing node is obtained, and the service data is distributed to a target main processing node for data processing; the target main processing node refers to a main processing node whose core running load index in the load state is in a corresponding preset interval range. The method can improve the data processing efficiency of power grid data.

This invention discloses an integrated intelligent monitoring system for air, space, and water using a wind-solar hybrid power supply, specifically relating to the field of intelligent monitoring. It includes a wind-solar hybrid power supply module, a sensing and monitoring module, a wireless self-organizing network communication module, and an intelligent management and control module. The wind-solar hybrid power supply module provides clean energy; the sensing and monitoring module collects environmental and operational data; the wireless self-organizing network communication module enables bidirectional data transmission and interaction between monitoring nodes; and the intelligent management and control module performs fusion analysis of multi-source data, water quality level prediction, and early warning triggering. The operation of the wind-solar hybrid power supply module specifically includes the following: classifying power supply differences into different levels based on power supply evaluation differences. This invention achieves long-term unattended, accurate, and efficient monitoring in outdoor scenarios without mains power through stable wind-solar hybrid power supply, comprehensive air, space, and water monitoring, reliable Mesh network transmission, and intelligent analysis, early warning, and dynamic optimization.

The application provides a mixture spectral component identification method and system under an edge computing architecture, and relates to the technical field of intelligent identification. The method comprises the following steps: in a cloud server, based on a standard spectral library and historical sample data, a candidate component spectral set is obtained by using a sparse regression method; the candidate component spectral set is downloaded to an edge computing node and stored locally to construct an edge spectral sub-library; after the edge computing node receives spectral data of a to-be-detected mixed sample, the edge spectral sub-library is linearly combined and solved based on a non-negative least square algorithm to obtain non-negative weight coefficients of each component; and the component composition in the to-be-detected mixed sample and the proportion of each component are determined according to the non-negative weight coefficients. Through edge-cloud cooperation, the application reduces the computing load of the edge end under the premise of ensuring the identification accuracy, meets the on-site real-time detection demand, avoids the negative weight problem, and improves the physical rationality of the result.

The utility model discloses a square bait fishhook group, which relates to the technical field of fishing gear, and comprises a bait fixing piece, a fishing rod, a fishing rod and a fishing rod, the horizontal fishing piece is connected with the bottom of the bait fixing piece, a plurality of first connecting structures are arranged on the horizontal fishing piece at intervals, and the first connecting structures are used for being detachably connected with fishhooks; the multidirectional fishing piece comprises a sliding block and a plurality of transverse fishing pieces, the sliding block is arranged on the bait fixing piece in a sliding and penetrating mode, the transverse fishing pieces are arranged in different directions, one end of each transverse fishing piece is connected with the sliding block, and the other end of each transverse fishing piece is provided with a second connecting structure; the second connecting structure is used for being detachably connected with a fishhook. According to the square bait fishhook set, the fishhooks can be rapidly replaced, other parts of the square bait fishhook set cannot be damaged, reasonable distribution of the fishhooks is achieved through the horizontal fishing rod and the multi-directional fishing rod, and the rate that fishes bite the fishhooks and the probability that the fishes are caught in the fishhooks are greatly improved.

The invention provides a pre-stress rolling mill and relates to the technical field of metallurgical equipment, the pre-stress rolling mill comprises a rack, a roller system, a rack pre-tightening mechanism and a hydraulic control system, the roller system is rotatably mounted on a housing through a bearing seat, and the rack pre-tightening mechanism comprises a pre-tightening hydraulic cylinder matched with the bearing seat in an aligned manner; the output end of the pre-tightening hydraulic cylinder vertically penetrates through the memorial archway and is in threaded connection with the bearing seat, and the pre-tightening hydraulic cylinder applies pre-tightening force in the vertical direction to the roller system. The hydraulic control system is provided with a hydraulic pipeline and a pressure adjusting switching valve, the hydraulic pipeline is connected with the pre-tightening hydraulic cylinder, the pressure adjusting switching valve is arranged on the hydraulic pipeline, the pressure adjusting switching valve is provided with a first working position and a second working position, when the pressure adjusting switching valve is located at the first working position, first pressure is provided for the pre-tightening hydraulic cylinder, and when the pressure adjusting switching valve is located at the second working position, second pressure is provided for the pre-tightening hydraulic cylinder. And providing second pressure for the pre-tightening hydraulic cylinder, wherein the second pressure is higher than the first pressure. The pre-stress rolling mill can keep proper pre-tightening force in a roll gap adjusting stage and a rolling stage.

The invention belongs to the technical field of blast furnace blast, and relates to blast furnace uniform blast equipment and method for changing the inclination angle of a hot air branch pipe. The hot air branch pipes are evenly distributed in the circumferential direction of the bustle pipe, meanwhile, the inclined included angle alpha is formed between the axis of the straight pipe section of each hot air branch pipe and the radial plane of the bustle pipe, and due to the design, right-angle turning in the hot air flowing process is structurally reduced, pressure loss and vortex dissipation caused by the right-angle turning are reduced, and the heat exchange efficiency is improved. The main guide direction of the original tangential flow speed of hot air in the hot air bustle pipe is maintained, it is guaranteed that the air quantity entering all the branch pipes is basically consistent, the air quantity distribution uniformity of all the tuyeres of the blast furnace is remarkably improved, and good flow stability and adaptability are achieved. Numerical simulation verifies that the comprehensive blast uniformity is optimal under the working condition that the hot air branch pipe is inclined by 75 degrees. The blast furnace can effectively improve blast uniformity, reduce airflow deviation and energy loss and improve the stability and smelting efficiency of the blast furnace, and has good industrial application value.

This invention discloses an articulated vehicle and its braking force distribution method. The articulated vehicle includes a tractor and a trailer, which are connected by a hinge. The braking force distribution method includes: acquiring the current parameters and current road condition information of the articulated vehicle in real time when it brakes; determining the current braking force demand and current risk coefficient based on the current parameters and current road condition information; determining the current braking force distribution ratio of the trailer based on the current risk coefficient; and determining the braking force of the tractor and trailer based on the current parameters, current braking force demand, current braking force distribution ratio of the trailer, and current road condition information. The technical solution of this invention achieves a reasonable distribution of braking force between the tractor and trailer, avoiding safety hazards caused by unbalanced braking force distribution.

This invention discloses a State of Charge (SOC) display system and method for unmanned logistics vehicles, belonging to the field of battery management technology for unmanned vehicles. The system includes: a vehicle controller, relays, a gateway, and a battery management system. When the vehicle controller and battery management system receive fast charging / slow charging / driving signals, the relay switches close, the gateway starts working, and forwards the data to the backend management system. When the vehicle controller and battery management system receive a driving signal, the backend management system displays the current SOC and driving status. When the vehicle controller and battery management system receive fast charging / slow charging signals, the backend management system displays the current SOC, charging status, charging time, and estimated full charge time. If the fast charging / slow charging / driving signal is lost, the backend management system displays the last received SOC and the vehicle's offline status, flexibly displaying information such as vehicle SOC, vehicle status, charging time, and estimated full charge time, achieving visualized monitoring of vehicle status and the charging process.

The invention discloses an open space personnel management method based on unmanned aerial vehicle vision, and relates to the technical field of image monitoring. Comprising the following steps: step 1, generating a current frame fusion detection result of each unmanned aerial vehicle based on multi-unmanned aerial vehicle cooperative sensing of a self-organizing Mesh network; 2, multi-person continuous tracking based on a space-time association diagram is carried out, each unmanned aerial vehicle constructs the space-time association diagram according to a current frame fusion detection result and a previous frame fusion detection result, and a current frame tracking result is generated; and step 3, multi-scale personnel counting and area management based on a Gaussian Laplacian pyramid, wherein each unmanned aerial vehicle gathers statistical data and alarm information through a self-organizing Mesh network and transmits the statistical data and the alarm information to a ground management and control platform. The problems that in the prior art, the coverage range of a single unmanned aerial vehicle is limited, the accuracy of multi-target tracking is insufficient in sheltering and appearance similar scenes, a single-scale detection method is poor in adaptability to personnel target size changes, and a counting result verification mechanism is lacked are solved.

The application discloses a Tibetan prosody structure prediction method based on syntax information, relates to the technical field of speech synthesis, and is applied to the prosody structure prediction field in Tibetan speech synthesis. The Tibetan prosody structure prediction method based on syntax information comprises the following steps: S1, Tibetan text analysis and virtual word connection quantization are completed, syntax probability, hierarchical focus and pause difference are extracted, and a Tibetan prosody prediction database is stored and constructed after preprocessing; S2, boundary discrimination is performed based on virtual word connection relationship strength, influence range hit marking and word sequence distance; S3, entropy feature analysis is performed through syntax role probability data and boundary determination data; S4, three-layer prosody boundary type sequences are generated according to boundary assignment, and over-dense pauses are inhibited; and S5, rhythm intensity evaluation is performed through pause duration difference and syntax information entropy data. The problems of pause confusion and increased understanding burden caused by the misplacement of prosody and semantic hierarchy in Tibetan long speech synthesis are solved.

The application discloses a real-time dynamic task allocation and scheduling method for a multi-vehicle cluster, relates to the technical field of task scheduling, and comprises the following steps: acquiring real-time physical running state sequences of each vehicle node in the multi-vehicle cluster and global task distribution characteristic sequences of a task set to be allocated; constructing a space-time topology tensor with dynamic edge weights; performing node feature aggregation on the space-time topology tensor; calculating a state divergence degree between real-time local physical states of the vehicle nodes and expected states corresponding to an initial task allocation correlation matrix; extracting a sub-cluster topology tensor within the local reconstruction boundary; inputting the sub-cluster topology tensor into the task scheduling network for local deduction to generate a local correction allocation matrix; and updating a task execution sequence of the target vehicle node and associated vehicle nodes within the local reconstruction boundary by using the local correction allocation matrix. The application improves the stability and adaptability of cluster task scheduling.

The invention discloses a circuit breaker service life prediction system and method based on the Internet of Things, and relates to the technical field of circuit breakers, and the system comprises an Internet of Things data collection module, a scene grouping module, a data quantification module, a key factor identification module, a service life prediction module and an early warning priority output module. The Internet of Things data acquisition module is used for acquiring environment data and working condition data; the scene grouping module is used for performing scene grouping on the circuit breakers from two dimensions of environmental conditions and working condition loads; the data quantification module analyzes the comprehensive life loss of each circuit breaker; the key factor identification module is used for outputting key factors of the corresponding scene groups; the life prediction module is used for constructing a scenarized life prediction model; key factor data collected by the Internet of Things in real time are substituted into the prediction model to calculate the residual life; and the early warning priority output module is used for carrying out early warning response when the model output result is smaller than the residual life early warning time limit, and carrying out priority ranking on all label factors contained in the same scene group.

The invention discloses an elevator Internet of Things data high-concurrency hierarchical compression transmission method and system based on edge computing, and the method comprises the steps: an elevator Internet of Things edge computing node collects elevator operation full-amount Internet of Things data in real time, and the data is graded into key data and conventional data through a multi-dimensional data value quantitative evaluation method. The node carries out lossless packaging on key data, carries out high-power compression on conventional data, initializes adaptive transmission strategies for the two types of data and then transmits the two types of data to the cloud platform. The edge computing node senses the network transmission state in real time, dynamically adjusts the transmission strategy according to the network state, improves the conventional data compression ratio and reduces the transmission rate when the network is congested, and allocates higher bandwidth for key data. Meanwhile, a dynamic adaptive mathematical model is constructed based on network state parameters and transmission performance parameters, optimal parameters are solved, and self-adaptive adjustment and optimization of a transmission strategy are completed. And the real-time performance and effectiveness of elevator emergency disposal are guaranteed.

The application discloses a workflow execution optimization method based on a random time Petri net, which comprises the following steps: S1, a service time model is constructed, total average service time of activities under different structures is calculated, and current load is updated to obtain a target function of minimum workflow service time; S2, according to the target model of minimum load balancing service time, executor capacity and actual task quantity allocated to the executor are converted into executor load to perform a traversal cycle to find an optimal candidate executor; S3, a waiting time model is constructed, and a target function of minimum workflow execution time is calculated based on the target function of minimum workflow service time; and S4, according to the target function of minimum workflow execution time, optimization of the random time Petri net execution time is performed. The application constructs a workflow execution time model based on the random time Petri net, which is used for analyzing, calculating and reducing workflow process execution time.

The invention is suitable for the technical field of power transaction data processing, and provides a power transaction data full-link standardization processing method and system, and the method comprises the steps: determining a remaining time interval corresponding to a completion behavior characteristic index of a target completion execution main body when different sample sets correspond to different remaining time intervals, and when the target completion execution main body executes subsequent missing data completion processing consistent with the service type, preferentially distributing the data completion task of which the predicted remaining time falls into the remaining time interval to the target completion execution main body. According to the method, an existing completion mode and an auditing mechanism are not changed, and reasonable distribution of completion tasks is realized through accurate matching of the tasks and time conditions, so that the amplification effect of completion errors in an exception recognition stage is effectively reduced, and the stability and consistency of exception recognition results are improved. The method can be stably operated in a large-scale and batch data processing scene.

The application relates to the technical field of load balancing, in particular to a load balancing method and system of a software switch. The method extracts a network layer five-tuple and a transmission protocol type through asynchronous sampling of an overload queue, identifies a congested queue and divides characteristic classification data streams; analyzes unevenness of load distribution between different characteristic classification data streams, integrates throughput gain of cross-core parallelism and a retransmission penalty of message disorder into a single benefit evaluation value, and performs binary asynchronous scheduling between cross-core interleaving distribution and single-core calculation based on the evaluation value. The application introduces unevenness of load distribution to quantify the concentration degree of ordered flow, comprehensively analyzes the value evaluation of parallel gain and retransmission penalty, realizes reasonable allocation of multi-core resources, and adapts to load balancing of massive heterogeneous terminal access of an Internet of Things edge gateway.

The application discloses a bridge structure self-adaptive sampling monitoring method and device suitable for an extreme road environment, and belongs to the technical field of bridge structure health monitoring.The core target of the application is to solve the problems of repeated arrangement of existing monitoring equipment, road-bridge data fragmentation, and low self-adaptive sampling regulation precision.Through innovative design of a road-bridge multiplexing integrated sensing node, single-node multi-parameter and full-scene monitoring are realized, and the arrangement cost and construction difficulty are reduced; through construction of a self-adaptive sampling strategy based on fuzzy logic control, a feasible algorithm model is given, continuous dynamic regulation of sampling parameters is realized, monitoring precision and low power consumption are taken into account, deep collaborative linkage of road environment monitoring and bridge structure monitoring is realized, and the safe operation of the bridge structure under the extreme road environment is ensured.

The invention provides a vehicle control system and a communication control method between vehicle devices. The system comprises a first control module, a second control module and a third control module. Main service logic is deployed in the first control module; deploying atomic service logic in the second control module; deploying actuator driving logic in the third control module; the system is configured to operate in the following first communication architecture or second communication architecture: in the first communication architecture, the first control module and the second control module are integrated in the same heterogeneous processor, and the second control module and the third control module are connected through a first external communication network; according to the second communication architecture, the first control module and the second control module are connected through a second external communication network; the second control module and the third control module are integrated in the same hardware entity, so that the overall electrical architecture is simplified, the number of high-speed interfaces is reduced, and the cost is reduced.

The invention discloses a resource configuration updating method and device, a storage medium and electronic equipment, and relates to the technical field of education, and the method comprises the steps: obtaining historical task execution data of a to-be-updated agent; comprehensively evaluating the historical task execution condition of the to-be-updated intelligent agent according to the historical task execution data to obtain execution capability data representing the task execution capability of the to-be-updated intelligent agent; determining a grade updating type of the to-be-updated intelligent agent, and updating the resource configuration grade of the to-be-updated intelligent agent according to the grade updating type to obtain a target resource configuration grade corresponding to the to-be-updated intelligent agent; and performing resource configuration on the to-be-updated intelligent agent according to the target resource configuration level, and determining target resource configuration information corresponding to the to-be-updated intelligent agent. According to the method, the resource configuration of the intelligent agent is updated by determining the level updating type and updating the resource configuration level, so that reasonable allocation of computing power resources is realized, and the service processing capability of the intelligent agent is guaranteed.