62results about How to "Guaranteed rationality" patented technology

The invention provides an expandable block chain identity authentication method and system for a distributed resource aggregation scene, and relates to the technical field of block chain identity authentication, and the method comprises the steps: receiving a user identity authentication request, generating an identity identification string through a distributed Hash algorithm, and selecting a verification node cluster to deploy a smart contract; each verification node executes the smart contract to verify the identity identification string, constructs an access authority control strategy and generates an authentication block; and when the number of the blocks reaches a preset threshold value, selecting a newly added verification node based on the terminal equipment information, deploying an intelligent contract, and realizing distributed storage through the verification node cluster broadcast authentication blocks. According to the invention, the expandability of identity authentication is improved, the dynamic expansion of the verification node is realized, and the reliable storage and efficient propagation of the authentication information are ensured.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention discloses an electric power engineering technical-economic review method based on deep learning. The method comprises the following steps: S1, automatically capturing project data such as engineering quantity, an equipment list and material cost, and carrying out preliminary detection; s2, analyzing data by using a deep learning model, and analyzing and classifying text information through natural language processing; s3, establishing a charging benchmark rule base, and automatically checking the cost data in the technical and economic files; s4, adopting a self-adaptive material semantic matching algorithm to examine equipment and material data, and carrying out market information price matching; s5, constructing a mapping relation between the project amount and the typical cost, and generating a deviation report; s6, establishing a data center to support multi-dimensional statistical analysis and a real-time cost report; and S7, combining historical and real-time data, performing early warning through a deep learning algorithm, and generating an intelligent review report. According to the invention, automation and intellectualization of electric power engineering technical-economic review are realized, and data processing efficiency and review accuracy are optimized.

The invention belongs to the technical field of seam welding detection, and particularly discloses and provides a roof waterproof roll seam welding detection method which comprises the following steps: constructing a three-dimensional model of a to-be-constructed welding area, and marking the type of a welding detection point; welding characteristic analysis is conducted on the welding area, and all welding characteristic indexes are obtained; the number of welding detection points is determined, and the welding detection points are marked; confirming a standard passing threshold value of each welding detection point corresponding to each welding detection index; building a welding quality inspection model; sequentially carrying out quality inspection according to a set welding quality inspection plan, and recording quality inspection values; and the welding quality score value is output, and a welding quality inspection report of the waterproof coiled material is constructed and fed back. According to the method, the defect that current welding detection points are arranged comprehensively is effectively overcome, the specific welding characteristics of the waterproof coiled material are fully combined, the adaptability of a seam welding detection scene of the roof waterproof coiled material is improved, and meanwhile the representativeness and rationality of a welding detection result are guaranteed.

The invention provides a one-dimensional pneumatic design method and device for an axial flow compressor, and belongs to the field of axial flow compressor pneumatic design. The method comprises the following steps: taking values of a plurality of design variables as the state of a reinforcement learning agent; the intelligent agent outputs the adjustment amount of the design variable according to the state, and the adjustment amount serves as the action executed by the intelligent agent; applying the action to the value of the current design variable to obtain an updated design variable; utilizing a one-dimensional inverse problem design program to generate a one-dimensional pneumatic design scheme of the gas compressor; utilizing a one-dimensional normal problem analysis program to output performance indexes; constructing a reward function according to the performance indexes; based on feedback provided by the reward function, a depth deterministic strategy gradient algorithm is adopted to train the intelligent agent; and performing one-dimensional pneumatic design of the gas compressor by using the trained intelligent agent. According to the method and device provided by the invention, the problems that the one-dimensional design of the axial flow compressor depends on experience, the efficiency is low, automatic optimization is difficult and the response is slow can be solved.

The invention discloses a loss diagnosis and health management system and method for a transformer, and belongs to the technical field of intelligent transformers, and the system comprises a thermal fingerprint module which is used for recording a temperature drop curve of each part of the transformer after planned power failure, and obtaining a thermal inertia fingerprint of the transformer based on the fitting of multiple temperature drop curves; the theoretical temperature module is used for calculating the theoretical cold body temperature of each part of the transformer based on the real-time environment temperature and the thermal inertia fingerprint when the transformer runs; the net temperature rise module is used for acquiring the actual temperature value of each part of the transformer and subtracting the corresponding theoretical cold body temperature from the actual temperature value; weak thermal characteristic signals caused by insulation aging and loss abnormity of the transformer can be accurately extracted from strong background noise such as load fluctuation and environment temperature through technologies such as thermal inertia fingerprint construction and net temperature rise separation, early diagnosis of progressive health deterioration is realized, support is provided for intervening potential faults in advance, and the fault diagnosis accuracy is improved. And the passive situation of post-treatment of operation and maintenance is changed.

The invention discloses an auditing process and authority control management system and method applied to data sharing, belongs to the auditing process and authority control management system and method applied to data sharing, and aims to solve the technical problem of how to realize management control of an auditing process and resource use authority of resource sharing. Comprising a resource data management module, a resource application management module, a resource authorization monitoring module, an authority management module and a message management module, and can realize strict control of auditing processes and use authorities related to resource authorization in a data sharing process. The resource authorization monitoring module and the authority management module are matched to strictly control the use range and the use time limit of resources, and the resource use reasonability and the resource application correctness are guaranteed; rapid application methods such as resource application search, batch application and form content default are provided, the application efficiency is greatly improved, functions such as auditing verification, information notification and batch auditing are provided, and the auditing efficiency is effectively improved.

The invention relates to a ball valve detection method and a ball valve, and relates to the field of ball valve leakage detection.The ball valve detection method comprises the steps that detection image information of a preset detection area is obtained; determining a left inflation position and a right inflation position according to the detection image information and preset interface features; a preset inflation device is controlled to inflate the left inflation position according to a preset left inflation air pressure value, and after inflation, the left air pressure value of the ball valve is obtained; based on the condition that the left side air pressure value is inconsistent with the left side inflation air pressure value, reporting a left side air leakage prompt; an inflation device is controlled to inflate the right inflation position according to the right inflation air pressure value, and after inflation, the right air pressure value of the ball valve is obtained; reporting a right side air leakage prompt based on the condition that the right side air pressure value is inconsistent with the right side inflation air pressure value; based on the condition that the left side air pressure value is consistent with the left side inflation air pressure value and the right side air pressure value is consistent with the right side inflation air pressure value, air leakage detection is completed. The method has the effect of improving the working efficiency.

The application provides a control method and a control device of compressor operation frequency and a water heater. The control method comprises the following steps: calculating the suction pressure attenuation ratio of the compressor; judging the frost degree of the heat exchange equipment according to the suction pressure attenuation ratio of the compressor; and dynamically setting the initial operation frequency of the compressor according to the frost degree of the heat exchange equipment. The control method further comprises the following steps: comparing the initial operation frequency of the compressor with the historical operation frequency of the compressor recorded in a database; and controlling the actual operation frequency of the compressor according to the comparison result. The control method can guarantee the rationality of the actual operation frequency of the compressor, solve the problem of low defrosting efficiency caused by the fixed operation frequency of the compressor during the defrosting process, and improve the energy efficiency.

The application discloses a kind of collaborative robot job parameter dynamic optimization method, comprising: real-time acquisition of the multimodal sensor data of collaborative robot in the process of job, multiple job parameters are analyzed based on job quality evaluation model to identify key parameter set from it;Multi-objective function is constructed with job time, end force as optimization target, and multi-objective function is converted into single-target optimization function by weighting sum method;Key parameter set is input to machine learning model, and single-target optimization function is used as optimization target to carry out iterative optimization, in each iteration, the standard deviation σ of the current learning result of machine learning model is obtained, according to the comparison result of standard deviation σ and preset critical value s, dynamically select optimization strategy, when σ≥s, new parameter set is generated using random exploration strategy, when σ<s, new parameter set is generated using guided optimization strategy of machine learning model, and the optimized parameter set is output.

The application provides a method and system for multi-party secure calculation of coefficient of variation, belonging to the field of multi-party secure calculation, and used for providing a new scheme for achieving the task of securely calculating the coefficient of variation of a data group, wherein the multi-party includes an initiator of a calculation task, a referee and a plurality of participants, the participants and the initiator hold private data, the initiator and the referee are two different parties, and the method comprises the following steps: the participants pre-process the data, the referee generates a public key and a private key based on a self-developed homomorphic encryption algorithm, and sends the public key to the participants, so that the private data of all the participants is encrypted, all the participants collect the encrypted data to the initiator, the initiator calculates an encrypted sum, the referee decrypts the sum and sends it to the initiator to obtain a mean value, all the participants calculate variance elements according to the mean value, and the variance elements are segmented, recombined and collected to the initiator, so that the initiator can calculate a standard deviation and then calculate a coefficient of variation.

This invention relates to the field of medical information technology, and in particular to a method and system for generating clinical multi-agent task sequences. The method includes the following steps: acquiring and structuring core clinical objectives, which include patient basic information, clinical indicators, and disease management goals; decomposing the core clinical objectives into several structured sub-objectives with dependencies and execution order based on a clinical pathway template library and a medical knowledge graph; for each structured sub-objective, splitting it into multiple minimum executable clinical sub-tasks according to a clinical sub-task decomposition rule library, and defining the execution subject type, input / output, and dependencies for each clinical sub-task to construct a sub-task-level directed acyclic graph; integrating the sub-task-level directed acyclic graphs, identifying dependencies across structured sub-objectives, generating a global clinical task directed acyclic graph, and performing dependency verification and clinical logic consistency verification.

The invention relates to a self-adaptive management method and system for a database plan cache, and the method comprises the steps: firstly judging whether the plan cache is hit or not after a database receives an SQL statement, and triggering a hard analysis generation plan and caching the plan when the plan cache is not hit; if the cache is hit, further judging whether a corresponding multi-execution plan exists or not; and when only a single execution plan exists, analyzing the relationship between the number distribution of execution tuples and the number of execution times by adopting an execution efficiency algorithm to dynamically judge whether the data is inclined. And when a plurality of execution plans exist, entering a multi-plan cache management stage, selecting the execution plans according to a matching result of the current binding variable predicate selection rate and the cache plan historical selection rate, and generating and caching a new plan when the matching fails. According to the method, the data skew is accurately identified by executing the efficiency algorithm, intelligent matching and multiplexing of plans are realized by means of a multi-plan cache management mechanism, and the overall performance of the database in a data skew scene is improved.

The invention discloses an analog signal range judgment and switching system with calibration and self-diagnosis functions, which relates to the technical field of analog signal monitoring and comprises an analog signal acquisition module, an analog signal range analysis module, an analog signal range switching module and a database, the method comprises the following steps: firstly, analyzing the influence of different environment temperature intervals on the optimal linear interval of the ADC to obtain the optimal linear interval of the ADC in the different environment temperature intervals, determining the optimal linear interval of the ADC according to the current environment temperature, and judging whether an analog signal falls into the optimal linear interval of the ADC and whether the current range gear loses efficacy; and then the target range gear is obtained by analyzing the influence among the range gears under different gear working conditions, and the current gear is switched to the target range gear, so that the effectiveness of range analysis and the precision of ADC sampling are guaranteed, and the rationality of range switching is also guaranteed.

The application provides a multi-round reasoning network traffic prediction method and device based on size model cooperation, which comprises the following steps: inputting historical traffic data into at least two time series prediction models, obtaining prediction results and calculating comprehensive confidence based on prediction errors, and generating a prediction effect ranking; inputting historical data, prediction results and confidence into a large language model, and evaluating and ranking the prediction effect of each model by the large language model; comparing the two rankings, and if they are consistent, calibrating and optimizing the large language model, and if they are inconsistent, adopting an independent adjustment strategy to enhance the sensitivity of the prediction results of the model with the best ranking, and obtaining target prediction results. Through the two-way comparison of the independent ranking of multiple models and the evaluation ranking of the large language model, the large language model can be isolated when the rankings are inconsistent, and an independent adjustment strategy is adopted, thereby effectively avoiding the direct impact of the reasoning deviation of the large language model on the prediction results, and improving the robustness and accuracy of network traffic prediction.

The present invention discloses a processing method, device, equipment and storage medium for a power grid engineering database, wherein the method includes obtaining all GIM initial data of a target power grid engineering and unified management of multi-version and multi-type data; extracting header information of each GIM initial data, and determining the extension file corresponding to each GIM initial data according to the header information; storing each GIM initial data in each data table structure; processing each data table structure according to relational database management system technology to extract a unique identifier for each GIM initial data; determining the primary key information and foreign key information corresponding to each data table structure; and constructing a target database based on each data table structure, unique identifier, primary key information and foreign key information. The processing method for a power grid engineering database provided by an embodiment of the present invention can significantly improve the efficiency and quality of power grid engineering data management, and provide a solid technical foundation for the sustainable development and intelligent upgrading of power grid engineering.

The invention relates to the technical field of LCD screen detection, in particular to an LCD surface mounting detection device and method, and the device comprises an AOI detection platform which is used for carrying out the optical detection of an LCD screen; the detection analysis module is used for analyzing the obtained optical detection result; the sorting module is used for sorting the LCD screens to different conveying belts according to the analysis result of the detection and analysis module; the chip mounting platform is used for carrying out chip mounting on the LCD screens meeting the chip mounting requirements; and the moving module can move the LCD screens which are sorted by the sorting module and meet the surface mounting requirements to a surface mounting platform. The AOI detection platform and the surface mounting platform are arranged adjacently, so that transmission between different procedures is reduced, the production stability is guaranteed, and the qualified rate of products is increased.

The application discloses a kind of based on multi-sensor's grid map two-way asynchronous construction method and system, the method includes: obtaining three-dimensional point cloud data, RGB image and depth map;Based on the space corresponding relation of RGB image and three-dimensional point cloud data, three-dimensional point cloud data is semantically labeled;Three-dimensional point cloud data, RGB image and depth map are timestamped alignment, coordinate transformation and filtering processing, obtain final point cloud data, with semantic point cloud data point cloud data is spatiotemporal alignment generation fusion point cloud data as semantic grid map input;Construct semantic grid map, adopt the two division strategies of front view map and rear view map, by independent thread asynchronous update;Establish motion object database and predict dynamic object motion trajectory based on time sequence prediction algorithm, update in semantic grid map synchronously.The application effectively guarantees the intelligent device obstacle avoidance success rate and path planning rationality, guarantee the operation safety and efficiency under complex environment.

The embodiment of the invention provides an insurance premium auditing method and device, equipment, a storage medium and a program product. Belongs to the technical field of data processing. The method comprises the following steps: receiving a to-be-converted rate table file sent by a configuration terminal and insurance type information of a target insurance type; converting the to-be-converted rate table file into a to-be-used rate table; determining a compliance premium interval and an authorized premium interval according to a to-be-used rate table, a target insurance type identifier, a target insurance amount, a target risk factor and target limit claim-free information in the insurance type information; collecting real-time reference data corresponding to the target risk factor; determining a to-be-used authorized premium interval according to the real-time reference data and the authorized premium interval; determining an audit result corresponding to the target insurance premium according to the to-be-used authorized insurance premium interval and the compliance insurance premium interval; and outputting an auditing result. The method solves the problems that the efficiency of manual insurance premium auditing is low, and the insurance premium auditing result is difficult to reflect the real-time risk change.

The utility model relates to a device of crushing technology field, and disclose a kind of cutting and crushing device for limestone processing, including jaw crusher frame, receiving table and vibrating feeder, the rear end of jaw crusher frame is fixedly installed with receiving table, eccentric shaft is rotatably installed on jaw crusher frame, electromagnetic clutch is installed on eccentric shaft in the right side near, the right end of electromagnetic clutch is provided with main pulley, the upper end of receiving table is rotatably installed with roll shaft in the left and right sides near, conveying belt is installed between the outside of roll shaft, uniformly distributed sieve slot is provided on the inclined plate position of vibrating feeder, irregular baffle is fixedly installed on vibrating feeder in the front end near discharge port.The device can effectively remove soil in limestone, ensure the normal discharging of limestone, and the on-off state of electromagnetic clutch can be controlled to start and stop the conveying belt, which can be used flexibly according to actual conditions and effectively reduce energy consumption.

The invention provides a distribution network non-power-cut operation digital decision and scheme generation method and system based on a live-action three-dimensional model. The method comprises the following steps: firstly, constructing a three-dimensional digital twinborn scene; receiving user job task information, positioning to a position corresponding to the scene, and calling a job method knowledge base to screen a preliminary candidate job method; and then simulating candidate method implementation in the scene, screening out qualified candidate methods through dynamic safety distance verification and feasibility analysis, generating a recommendation scheme sequence through quantitative evaluation comparison and selection, generating a preliminary job implementation scheme report according to template filling information, and finally receiving user auditing and modifying confirmation information and storing a final scheme. According to the method, the three-dimensional space relation of the line corridor is accurately reproduced by means of the three-dimensional digital twinning scene, quantitative data support is provided for operation method selection through multi-link simulation, verification and evaluation, information blind areas and misjudgment risks are eliminated, decision subjectivity is reduced, and rationality and safety of an operation scheme are guaranteed.

The application discloses a method for enhancing position monitoring of a closed space PNT network and a high-precision map, and relates to the field of wireless positioning. The method comprises the following steps: establishing a semantic unit grid of a target closed space; establishing a mapping relationship database of semantic information of any one entity object element and position information of the semantic unit where the entity object element is located; acquiring a grid code of a semantic unit where a target entity object is located; and obtaining position semantic information of the target entity object based on the grid code of the semantic unit and the mapping relationship database. According to the technical scheme, the grid code of the semantic unit where the user is located is calculated only once, the semantic information is obtained by reading the mapping relationship database index based on the grid code of the semantic unit, and the calculation amount and response waiting time of the user position monitoring information are greatly reduced. Furthermore, the rationality of the user position monitoring information is improved, and the calculation amount of the generated user position density monitoring information is reduced.

The application discloses a kind of machine learning training topology generator and the method for generating topological discriminator model, comprising the following steps: with matrix pair form characterizing real topological data, and pre-processing;Topology generator is constructed, and topological pseudo-matrix pair data is generated;Topological discriminator is constructed to identify the source of topological data;The topological generator and the topological discriminator are based on the adversarial training of generative adversarial network;Low-voltage area topological matrix pair data is generated, and is converted into visual topological graph.The application realizes the coevolution of topological generator and topological discriminator by constructing topological generator and topological discriminator and through the adversarial training of both, and then enables topological generator to automatically generate a large number of topological data in accordance with real station area statistical distribution and engineering rationality from simple input, with the technical effects of high generation quality, high automation efficiency, guaranteeing physical rationality, solving data scarcity problem and strong flexibility and adaptability.

The application discloses an indoor situation generation method and device combining thin-plate spline interpolation and natural neighborhood interpolation and a medium, and relates to the field of electric digital data processing.The method comprises the following steps: acquiring original sampling data; performing grid division, merging and extracting data falling into the same grid to obtain a first sample data set; generating preliminary interpolation data by using thin-plate spline interpolation; extracting supplementary sampling point data from the preliminary interpolation data in an area not covered by the original sampling data to obtain a supplementary sample data set; performing grid division and merging to obtain a second sample data set; combining the supplementary sample data set and the second sample data set, filtering the supplementary data, and obtaining a target sample data set; and generating final situation data by using natural neighborhood interpolation.The application can effectively improve the situation generation quality under the condition of uneven sample distribution by filling in sparse area samples through thin-plate spline interpolation and finely processing the samples through natural neighborhood interpolation.

The invention discloses an acoustic radar near-surface wind speed inversion method and system based on entropy weight feature fusion, and the method specifically comprises the steps: carrying out the preprocessing of acoustic radar frequency spectrum data, and obtaining the preprocessed frequency spectrum data; based on the preprocessed spectrum data, constructing a Doppler window dynamic migration model based on turbulence dynamics power law distribution; on the basis of a Doppler window dynamic migration model, candidate spectrum peaks are selected at each height layer, a feature space is constructed, feature weights are dynamically distributed by using an information entropy theory, and an optimal spectrum peak is selected; introducing a symmetry constraint optimization strategy to the optimal spectrum peak, detecting the profile symmetry of the wind spectrum in the symmetric direction, and calibrating an asymmetric result to obtain a target wind speed inversion result; and comparing and evaluating the target wind speed inversion result and the wind speed of the anemometer tower as a reference to complete inversion result verification. According to the method, the wind speed inversion precision of the acoustic radar in a complex environment is effectively improved, and better evaluation and efficient utilization of wind energy resources are promoted.

The utility model relates to punching equipment technical field, and disclose a new energy automobile frame processing is with punching equipment, including numerical control laser cutting machine, the workbench of numerical control laser cutting machine places the locating disc, the lower extreme of locating disc is close to both ends place and rotates and installs the support shaft, the left and right both ends of support shaft all are fixedly installed with double conical roller, the front and back both ends of numerical control laser cutting machine all are fixedly installed with the baffle, the inside of slide groove all slide and install square bearing, the inside between square bearing all are fixedly installed with two -way screw rod, the mobile block between in the similar one end all are fixedly connected with the angle and resist piece. The device can be more labor -saving and fast to move to the workbench with the cooperation of double conical roller and track, and meanwhile can fix the same batch chassis frame on another set of locating disc in advance, realizes the feeding and discharging fast, avoids lifting to the workbench and then carries out the tedious tooling positioning operation, improves the efficiency of overall processing procedure.

The invention relates to the technical field of ecological restoration, in particular to an ecological restoration monitoring method and system for a coal mining subsidence area. Obtaining soil recovery state time sequence information; when the soil recovery state at the end point moment of the time sequence information of the soil recovery state meets a soil target state, the time sequence information of the soil recovery state and vegetation planting parameters are input into a vegetation recovery state prediction network, and the time sequence information of the vegetation recovery state is obtained, the vegetation recovery state prediction network is a black box model constructed based on a long-short term memory neural network; and when the vegetation recovery state at the end point moment of the vegetation recovery state time sequence information meets a vegetation target state, performing ecological recovery monitoring on the soil modification coal mining subsidence area executing the soil modification control parameters by taking the soil recovery state time sequence information and the vegetation recovery state time sequence information as monitoring baselines. According to the method, scientificity and effectiveness of cultivated land protection and ecological restoration of the coal mining subsidence area can be improved.

The invention provides a behavior prediction model construction method and a behavior prediction method in a manual control stage of an automatic driving vehicle, and relates to the technical field of intelligent automobile and man-machine cooperative driving, and the method comprises the steps: converting multi-dimensional structured data into a sequence text which can be analyzed by a large language model based on a semantic template, and inputting the sequence text; taking the converted semantic sequence as input, constructing a multi-modal large model guided generative manual control behavior prediction model, and outputting a manual control behavior sequence; and taking a multi-modal large model guided generative manual control behavior prediction model as a teacher model, and performing knowledge distillation on the teacher model to obtain a manual control stage behavior prediction model based on cross-scene knowledge distillation migration. According to the method, the manual control behavior prediction model guided by the multi-modal large model is constructed, and the construction of the manual control behavior prediction model adaptive to different driving scenes is completed by means of a cross-scene knowledge distillation migration technology.

The invention relates to the technical field of damage evaluation, in particular to a method for calculating the accumulated damage ammunition consumption of an open-space ammunition hitting bridge floor, which comprises the following steps of: according to the open-space ammunition hitting bridge floor to each damage degree, determining the coordinates of a hit point by utilizing Monte Carlo simulation, judging whether the hit point is hit or not, and calculating the damage probability; the open space ammunition amount required for destroying the bridge deck by the open space ammunition to reach the damage level can be rapidly calculated through the ammunition using amount corresponding to the damage probability, reasonable supply and preparation of the ammunition amount are guaranteed, and then a bridge deck target strike strategy is formulated.

This application provides a resource sharing method, resource sharing device, and storage medium, relating to the field of communication technology, for improving the utilization rate of network resources in access network equipment. Applied to a first blockchain node, which is an access network device contracted with the blockchain system, the method includes: generating a first block based on the network resource information of the first blockchain node, and publishing the first block to the blockchain system; predicting the amount of shareable network resources of the first block within a target time period based on the historical network resource information of the first block; the target time period being the period after the current time; and sending a sharing request to the blockchain system when the amount of shareable network resources exceeds a preset threshold; the sharing request information indicating the amount of shareable network resources of the first block within the target time period.