72results about How to "Targeted optimization" patented technology

The invention discloses a terminal data automatic backup and recovery method and system, and relates to the technical field of data backup and recovery, and the method comprises the steps: dynamically adjusting the priority, and generating a personalized backup strategy; capturing data change in real time and executing incremental backup; and encrypting the backup data for version recovery. According to the terminal data automatic backup and recovery method provided by the invention, accurate analysis and priority division are performed on the terminal data through the classification model, so that the backup plan can be dynamically adjusted according to the importance of the data in the backup process. Data change is captured in real time, incremental backup is executed, and the real-time performance and efficiency of backup are effectively improved. An incremental backup algorithm is adopted, only a file change part is recorded, and a change area of a data block is quickly positioned by utilizing hash value comparison, so that the requirement of a storage space is reduced, and meanwhile, the transmission overhead of backup data is reduced. According to the method, better effects are achieved in the aspects of backup real-time performance, backup accuracy, backup pertinence and backup efficiency.

The invention relates to the technical field of geological exploration, in particular to a geological exploration safety monitoring and early warning method and system, and the method comprises the following steps: carrying out the exploration region division based on a geological exploration data set, carrying out the risk assessment and density assignment of geological units in combination with the risk degree, and generating a geological risk density map. According to the method, through geological risk assessment and density assignment, exploration area division and risk assessment, and in combination with risk level judgment of geological units, safety monitoring and early warning in the geological exploration process are more refined and scientific, and by means of stress analysis simulation and terrain sensitivity analysis, the safety of the geological exploration process is improved. According to the geological disaster early warning method, the stress response of the geological unit under natural and artificial loads is revealed, the capability of identifying risk points and sensitive areas in an exploration area is improved, early warning is carried out on geological disasters in the early stage, the real-time performance and pertinence of geological disaster early warning are optimized, and losses caused by the geological disasters are reduced.

The invention is suitable for the technical field of water treatment, and particularly relates to an intelligent operation and maintenance method, system and equipment for water treatment, and the method comprises the steps: obtaining water quality information and system images, and precisely knowing the operation condition and treatment effect of a water treatment system; key parameters of the water treatment system are obtained based on the water quality information, feature data of system images are obtained according to the key parameters, and the operation performance of the water treatment system is effectively quantified and analyzed; determining first operation and maintenance positive parameters of the water treatment system according to the key parameters of the water treatment system; according to the first operation and maintenance parameter of the water treatment system and the characteristic data of the system image, determining a second operation and maintenance parameter of the water treatment system to realize targeted optimization so as to improve the stability and efficiency of the water treatment system; according to the second operation and maintenance positive parameter of the water treatment system, a water treatment operation and maintenance result is obtained, water quality changes are responded more sensitively, operation and maintenance work efficiency and timeliness are improved, and optimization pertinence is improved.

The invention discloses a multistage safety response control method of an industrial and commercial liquid cooling energy storage system, and relates to the technical field of electric energy storage systems, a sensor network collects an operation state data time sequence matrix, and abnormal data cleaning is carried out on the time sequence matrix; the method comprises the following steps: preprocessing a vibration signal of a cooling system, extracting characteristic data of abnormal vibration through Fourier transform and energy distribution analysis, and positioning a time-frequency distribution abnormal region; generating a time sequence multivariable data set according to the characteristic data of the abnormal vibration, determining a cause label according to the fused time sequence multivariable data set, obtaining the inherent frequency and the resonant frequency of the cooling system in combination with simulation analysis, and matching and determining the cause of the abnormal vibration; an LSTW neural network is used for predicting the abnormal resonance risk, and corresponding countermeasures are taken for the cooling network according to the prediction result; unnecessary vibration caused by error adjustment is avoided, the relation between cooling efficiency and safety is balanced, and unnecessary power loss is reduced.

The invention discloses a water quality self-adaptive regulation and control system and method based on multi-point detection, and relates to the technical field of water quality self-adaptive regulation and control. A sensor network collects water quality data in each sub-region of a target water area in real time, and abnormal regions are screened out after water quality abnormal states in the sub-regions are determined according to water quality abnormal scores; performing inspection on each abnormal area by using an inspection unmanned aerial vehicle, and summarizing to generate a water area inspection data set after obtaining corresponding inspection data; outputting an intervention strategy for the target water area by the water quality intervention knowledge graph, executing the intervention strategy, automatically controlling the operation of the water treatment facility by using the automatic control model, collecting corresponding intervention feedback data, and adjusting and optimizing the intervention strategy according to the intervention feedback data; and a water quality monitoring report is sent to a data receiving end at the time node meeting the constraint condition. When the water quality in the target water area is abnormal, automatic and adaptive adjustment control is realized, and the water quality in the target water area is prevented from deteriorating.

The invention provides a respirator self-adaptive control method, system and equipment and a storage medium, and relates to the field of respirator control. The method comprises the steps that physiological parameters and environmental parameters of a respirator wearer and initial running state data of the respirator are obtained, man-machine state evaluation is conducted based on the physiological parameters and the environmental parameters, and a man-machine state evaluation result is determined; determining an initial control strategy of the respirator based on the man-machine state evaluation result and the initial operation state data of the respirator; acquiring historical data in the use process of the respirator, and adaptively adjusting the initial control strategy based on the historical data to obtain an optimized dynamic control strategy; multi-source sensing data of the respirator are obtained in real time, the dynamic control strategy is adjusted in real time based on the multi-source sensing data, and a self-adaptive control strategy is obtained; and the respirator is controlled based on the self-adaptive control strategy. According to the scheme, the wearing comfort and the protection effect of the respirator can be improved.

The invention relates to the technical field of medical data processing, in particular to a postmenopausal osteoporosis patient medical data analysis method and system, and the method comprises the following steps: extracting a bone mineral density measurement value and a bone metabolism index concentration based on patient bone mineral density data, bone metabolism index data and fracture event records; according to the method, through combination of covariance matrix calculation, feature value and feature vector extraction and revealing of deep relevance between data, fine description of bone mineral density and metabolism index changes is achieved, state probability values, fracture records and drug use data are subjected to normalization weighting processing, and an optimized posterior state distribution matrix is generated; the accuracy and comprehensiveness of data fusion are improved, a key dynamic feature set is extracted through screening and accumulation operation, the pertinence and efficiency of analysis and normalization and time interval prediction of a trend curve are optimized, a quantitative result of the bone mineral density change trend and the fracture risk is formed, and high-precision support is provided for illness state assessment and personalized analysis.

The invention discloses a method for enhancing a network boundary security policy of a power monitoring system, and belongs to the field of network security. Comprising the following steps: collecting security equipment strategies of different brands in the power monitoring system in combination with network security equipment characteristics of the power monitoring system, and performing intelligent analysis in combination with asset routing conditions; on the basis of asset detection, routing strategy acquisition and protection strategy acquisition, network security strategy calculation is carried out, and unified strategy management of security boundaries is realized; under the condition that the information security requirement is met, automatic issuing of protection and blocking strategies is realized; through centralized management of security policies of heterogeneous equipment, policy configuration data of the network security equipment is captured in an online acquisition mode, and a unified security policy library is formed in a normalization mode, so that unified management, carding reinforcement, carding optimization, topology modeling, path management and policy opening and plugging functions of the security policies of the heterogeneous network security equipment are realized. The method can be widely applied to the field of safety management and operation maintenance of a power monitoring system network.

The invention discloses a power monitoring system network security equipment security boundary strategy unified management system, and belongs to the field of security. Comprising the following steps of: acquiring information of general safety equipment including a firewall, a switch and a VPN (Virtual Private Network); analyzing traffic, strategies, logs and events by using a machine learning method; when the analysis result is displayed, a blocking suggestion is given and can be automatically issued, and a disposal report is generated; unified and centralized management of heterogeneous brands and heterogeneous models of network security equipment including firewalls, routing exchange, load balancing and VPN in the whole network of an enterprise is realized; through visualization of safety management by a user, safety compliance visualization analysis from a safety perspective is realized. Safety equipment strategies of different brands in a power monitoring system are collected, intelligent analysis is carried out in combination with asset routing conditions, and automatic issuing of protection and blocking strategies is achieved. On the basis of asset detection, routing policy acquisition and protection policy acquisition, policy unified management of the security boundary is realized.

The invention belongs to the field of solar cells, and particularly relates to a hole transport layer, a perovskite solar cell and a preparation method. The hole transport layer comprises a NiOx layer and a self-assembly molecular layer, wherein the self-assembly molecular layer comprises a self-assembly molecular material and a surfactant. The perovskite solar cell comprising the hole transport layer has the advantages of high efficiency, high stability, low production cost and simple preparation process.

The invention provides a power distribution network single-phase earth fault processing and fault rapid regional isolation system for solving the problems existing in power distribution network single-phase earth fault regional isolation at present. The system is composed of an improved compensation damping type active intervention arc extinguishing device installed on a transformer substation bus, primary and secondary fusion intelligent switches installed at all nodes of a distribution line, and a primary and secondary fusion intelligent switch intelligent control terminal. When a single-phase grounding fault occurs, a grounding switch of the compensation damping type active intervention arc extinguishing device is switched on, a primary and secondary fusion intelligent switch control terminal of each node of a power grid generates corresponding low-resistance, medium-resistance and high-resistance zero-sequence protection fixed values, and when the single-phase grounding fault occurs, zero-sequence current protection is started to realize rapid fault area isolation of the single-phase grounding fault.

The invention relates to the technical field of targeted intervention of chordoma, in particular to application of a medicine to treatment of chordoma of different molecular types. The invention provides application of anlotinib, an oxidative phosphorylation inhibitor and desumab in preparation of products for preventing and / or treating chordoma. The chordoma comprises interstitial epithelial transformed chordoma, mesenchymal derived chordoma and bone microenvironment dominant chordoma. The invention also provides a pharmaceutical composition, which comprises an effective dose of anlotinib, and / or an oxidative phosphorylation inhibitor, and / or desumab. Under the condition that current treatment selection is limited, proliferation, clone formation and tumor growth of tumor cells can be remarkably inhibited by applying the medicine to specific molecular subtype chordoma, and compared with existing treatment medicine, the medicine has a better treatment effect, has good safety and shows potential clinical application value.

The invention discloses a petroleum proppant finished product sorting control method and system based on machine learning, and relates to the technical field of petroleum proppant production. A three-dimensional geometric model of the airflow classifier is constructed, and three-dimensional tracks of the spherical particle samples and the non-spherical particle samples are generated; for proppant particles to be graded, shape characteristic parameters of the proppant particles are obtained, a petroleum proppant particle sample with the highest shape similarity with the proppant particles is found, and the speed deviation is calculated; calculating a comprehensive deviation index based on the shape characteristic parameters and the speed deviation of the proppant particles, if the comprehensive deviation index is smaller than or equal to a comprehensive deviation index threshold value, directly grading the proppant particles, and otherwise, performing secondary treatment; the optimal correction parameters are predicted through the intelligent correction model, the proppant particles are corrected, and the corrected proppant particles are fed into an airflow classifier; an optimization objective function is constructed, and optimal process parameters are searched; and the quality control of petroleum proppant finished product sorting is realized.

The invention relates to a method for exploring influence of soil texture on crop growth vigor, and relates to a method for exploring influence of crop growth vigor. The method comprises the following steps: 1, downloading a remote sensing image; 2, acquiring data; 3, constructing a feature variable set; 4, establishing a forest prediction model; 5, obtaining a soil texture spatial distribution map; and 6, extracting NDVI from the remote sensing image as the growth vigor of crops, and performing correlation analysis on the NDVI and the soil texture spatial distribution diagram. The method is based on the soil texture mapping of the random forest, and the soil texture spatial distribution can be quickly and accurately predicted. According to the method, the data is accurate, the model is more efficient, the interior of the farmland can be accurately and individually regulated and controlled, and the soil texture better meets the actual requirements of crop growth. The method can be used in the field of precision planting agriculture.

The invention discloses an advertisement customization service platform based on intelligence, and relates to the technical field of advertisement platforms. The advertisement customization service platform based on intelligence includes a data collection and preprocessing module, which is used to collect user feature data sets and preprocess the user feature data sets; a bias prediction and adjustment module, which is used to identify representative biases in user feature data sets and implement data bias adjustment measures according to representative biases; a fairness evaluation and optimization module, which is used to detect the fairness of different advertisement decisions to different groups and implement fairness optimization measures according to fairness detection results; an advertisement recommendation continuous monitoring module, which is used to generate a fairness inspection report according to fairness detection results and recommend and place advertisements according to the fairness inspection report. The problem that the existing advertisement platform inadvertently learns and amplifies biased data, resulting in unfair advertisement placement results, is solved.

The present invention discloses a dynamic resource allocation method and system for a video customer service analysis task, and relates to the technical field of dynamic resource allocation. A trained customer service rating model is used to rate customer service, and when receiving customers, collected consultation reception data is aggregated to generate a customer consultation data set; risk customers are identified among the received customers, and the concentration of risk customers is constructed according to the time node when the risk customers are identified. If the concentration exceeds the concentration threshold, a customer service resource scheduling strategy is generated using a trained customer service resource scheduling model, and customer service of an adaptive level is allocated to the risk customer among several customer services whose number of pending requests is lower than expected; a feedback value is constructed after recording the risk customer churn rate and satisfaction value, and corresponding dynamic adjustment measures are taken for the allocation of customer resources according to the feedback value; and the customer churn risk is reduced by realizing dynamic optimization and adjustment of the customer resource scheduling strategy.

The invention relates to an intelligent robot grabbing method and device, electronic equipment and a storage medium. The method can comprise the following steps: acquiring multi-modal sensing information corresponding to a target capture scene; based on a multi-modal semantic analysis model, performing semantic analysis processing on the multi-modal perception information, and outputting semantic association information corresponding to the to-be-grabbed object; according to the semantic association information, determining a target grabbed object, a recommended grabbed point corresponding to the target grabbed object and a recommended grabbed strategy; on the basis of a grabbing pose prediction network, pose prediction processing is conducted on the recommended grabbing points, and robot grabbing pose information is obtained; according to the recommended grabbing strategy and the robot grabbing pose information, the target grabbing object is grabbed, and grabbing state parameters are obtained; and on the basis of the grabbing state parameters, the grabbing pose information of the robot is adjusted. According to the technical scheme provided by the invention, objects can be effectively prevented from sliding off, being damaged or colliding, and the intelligent level and the grabbing efficiency of the robot are improved.

The utility model discloses a SF6 gas micro -water density monitoring devices contains micro -water detection module, inlet pipe, exhaust pipe, pump body, L type telescopic pipe and butt joint, drying cylinder, place cavity, step support surface, filter cartridge (infill drying agent), sliding sleeve, upper / lower limit convex ring, sliding groove and convex strip, boss, extruding block, fixed peg, spring, connecting rod, pressure gauge, wireless transmitting module, when working, the pump body draws gas and enters drying cylinder after micro -water detection, conical hole and extruding block - step support - sliding sleeve constitute forced flow structure, and make sample gas to pass through filter cartridge reflux equipment, and pressure gauge and wireless transmission realize pressure monitoring and data report, and the structure is convenient for installation maintenance, and inhibits bypass, and stable reflux moisture content, and improves detection result consistency.

The invention relates to the field of intelligent power grids and intelligent fusion terminals, in particular to a transformer health monitoring system based on an intelligent fusion terminal TTU, and the system comprises a waveform data collection module which is used for collecting the waveform data of a transformer; the environment data acquisition module is used for acquiring operation environment data of the transformer; the denoising and reconstruction module is used for carrying out denoising elimination and waveform reconstruction on the waveform data of the transformer; the feature extraction module is used for performing feature extraction, enhancement and fusion on the preprocessed waveform data and the operation environment data of the transformer to obtain a fusion feature vector; the state analysis module is used for inputting the fusion feature vector into a mixed regression model for health state prediction to obtain a transformer health index prediction value; and the TTU decision module is used for matching the control decision scheme and controlling the working state of the transformer. According to the invention, the accuracy and reliability of transformer health prediction and the reliability of overall operation of a power grid can be improved.

The invention discloses a remote sensing residential area extraction method and system based on multi-source data fusion semantic segmentation, and particularly relates to the field of remote sensing image processing and land utilization mapping. A multi-source fusion automatic labeling strategy is adopted, and a rural residential area pixel-level training label is automatically generated by using an impervious surface product, an open source map interest point and a night light learning area-brightness threshold value; the method comprises the following steps: constructing an SELPFormer lightweight Transform segmentation model, introducing Lite-PPM, SCSE and ELA feature enhancement modules and a lightweight decoder on the basis of SegFormer, and outputting a rural residential spot pixel level extraction result for regional scale rural residential spot mapping.

The invention discloses a student-oriented psychological counseling method based on a large model. The method comprises the following steps: S1, acquiring emotion expression text data; s2, establishing an emotional state feature vector based on the emotional intensity; s3, collecting emotional state feature vectors for multiple times in a preset time window; s4, generating an emotion buffering strategy based on a short-term emotion fluctuation monitoring result; s5, guiding the emotional state; s6, storing the emotional state feature data after the emotional state feature data is relieved into an emotional file of the student; s7, based on emotional state feedback data, adopting an adaptive learning algorithm to finely adjust the large model, optimizing the analysis of an emotional fluctuation state and the generation ability of an emotional buffering strategy, and gradually adjusting and optimizing an emotional buffering method; and S8, based on the emotional state feedback data and the emotional change trend of the student, repeatedly executing the steps S1-S7 to form an emotional buffer closed-loop feedback system. According to the invention, a more efficient and more intelligent solution can be provided for student psychological health management.

The present application relates to reservoir scheduling technical field, disclose a kind of cascade reservoir group scheduling trajectory dynamic optimization method, comprising the following steps: collecting scheduling basic data;Optimization function and constraint condition of cascade reservoir group scheduling are constructed and calculation parameter is set;Using artificial experience decision or conventional method, obtain the initial trajectory of each reservoir each stage;Start iteration, execute several times dynamic programming method and establish historical trajectory library;Continue iteration, execute multi-type flight mode dynamic optimization, randomly select lev flight, spiral flight or navigation flight mode combination historical trajectory optimization current trajectory, iteration until meeting termination condition output optimal scheduling trajectory.The present application also discloses a kind of cascade reservoir group scheduling trajectory dynamic optimization.The present application cascade reservoir group scheduling trajectory dynamic optimization method and system, break through the dimension disaster defect that dynamic programming exists in solving complex reservoir group scheduling trajectory optimization problem, present significant convergence ability and calculation precision.

The application discloses a centrifugal pump volute flow channel parameter optimization method and system, and relates to the technical field of industrial equipment digital optimization; the method comprises the following steps: based on volute structure data and mechanical seal installation data, the inner wall of the volute is partitioned and identified to obtain a sealing front area, a pressure transmission area and a flow discharge area; based on the sealing front area, the pressure transmission area, the flow discharge area, mechanical seal contact requirement data and target working condition data, contact control analysis is carried out to obtain contact control data; based on the sealing front area, the pressure transmission area, the flow discharge area, the contact control data and the volute structure data, flow channel adjustment item extraction is carried out to obtain regional adjustment data; based on the regional adjustment data, impeller outlet structure data, the contact control data and the target working condition data, flow channel sequence correction is carried out to obtain target flow channel parameters; the application can take into account the sealing working state and the target working condition requirement, and improve the pertinence and adaptability of centrifugal pump volute flow channel parameter optimization.

The utility model discloses a carbon monoxide washing water purification device for preparation of calcined petroleum coke, which comprises a sewage pool and reciprocating track assemblies, partition plates are arranged on the inner side of the sewage pool in a staggered manner, and the reciprocating track assemblies are laid on the outer sides of the multiple groups of partition plates and at the bottom end in the sewage pool. The reciprocating running track assembly comprises an S-shaped track, side sliding grooves, a mounting panel and a rack groove, and the side sliding grooves are formed in the two sides of the S-shaped track. According to the carbon monoxide washing water purification device for preparing the calcined petroleum coke, through mutual cooperation of flocculation, sedimentation and filter pressing mechanisms, the flocculation and sedimentation effects of ash in washing water are improved, the turbidity of the treated washing water is reduced, the water content of a filter cake passing through a filter press is reduced, the functionality is high, and after the ash in the washing water is flocculated and settled, the water content of the filter cake is reduced. And finally, harmless treatment is carried out, so that the purpose of purifying the washing water is achieved.

The present invention provides a phosphine-containing compound and a preparation method thereof and an application thereof as a ligand of an ethylene oligomerization catalyst composition. The phosphine-containing compound has a structure as shown in Formula I: wherein R1, R2, and R3 are independently selected from hydrogen, a C1-C20 chain alkyl group, a C3-C20 cycloalkyl group, a heterocycloalkyl group, a substituted or unsubstituted C6-C20 aryl group, a halogen, an alkoxy group, a phenoloxy group, an amine group, and a phosphine-based substituent; and R1, R2, and R3 are the same or different. When used as an ethylene oligomerization catalyst, it can selectively prepare 1-hexene and 1-octene, and also has excellent total selectivity of C8 and C6.

This application provides a method and apparatus for linking supplier profiles with procurement activities. The method includes acquiring multi-source heterogeneous data related to a target supplier from multiple data sources. Upon detecting a change in any data point within this heterogeneous data set, the method triggers a real-time recalculation of the target supplier's health score to obtain a real-time health score. This real-time health score is then used to determine and execute the control strategy for the target supplier within the procurement transaction system, thereby achieving dynamic control over procurement activities involving the target supplier. This method enables real-time supplier status awareness, constructs a hierarchical and categorized differentiated control system, effectively solves the problems of limited control methods and delayed risk response, and significantly reduces compliance and financial risks.

The long-distance tear injection device loaded on the unmanned aerial vehicle comprises a base, the base is fixedly connected to the top end bearing face of the unmanned aerial vehicle, a pressurizing injector is installed on the plate face of the base, a fixing support is installed at the side end of the pressurizing injector, and the pressurizing injector is installed on the fixing support. The pressurizing ejector and the base are limited and fixed through the fixing support, a long gun ejector head is installed at the front end of the pressurizing ejector, the rear end of the pressurizing ejector is detachably connected with a material pot, a pump is installed at the top end of the pressurizing ejector, the input end of the pump is communicated with the material pot through a hose, and the pump is connected with the material pot. And the output end of the pump is communicated with the pressurizing ejector. The pressurizing ejector is installed on the unmanned aerial vehicle, and the unmanned aerial vehicle approaches target personnel by means of maneuverability of the unmanned aerial vehicle and conducts non-fatal strike on the target personnel or areas, so that the target personnel or the areas lose resistance temporarily, and safety of handling personnel is guaranteed.

The invention relates to the technical field of commercial data analysis, in particular to an intelligent demand prediction analysis method and system for commodity auction. The method comprises the following steps: acquiring auction item ontology data; analyzing auction item ontology feature data according to the auction item ontology data; performing dynamic association network analysis on the auction item ontology based on the auction item ontology feature data to generate a dynamic auction item ontology association network; detecting user interaction data; performing user interaction behavior feature analysis processing according to the user interaction data to generate user interaction behavior feature data; performing instant user demand auction probability prediction based on the user interaction behavior feature data to generate instant user demand auction probability prediction data; and transmitting the instant user demand auction probability prediction data to a dynamic auction body association network to carry out instant user association demand auction intelligent analysis, and generating instant user association demand auction prediction data. According to the invention, the accuracy and efficiency of demand prediction in the commodity auction platform are improved.

The embodiments of this specification disclose a method, device and equipment for processing NFC services of a smart wearable device, which are applied to the smart wearable device. The scheme includes: controlling the NFC card reader on the smart wearable device to be in a closed state; in the closed state, receiving an NFC service trigger instruction for the smart wearable device; in response to the NFC service trigger instruction, entering a designated service application on the smart wearable device, and automatically switching the NFC card reader from the closed state to the open state through the designated service application; after the smart wearable device approaches the target NFC device, the target service information is read from the target NFC device through the NFC card reader in the open state, so that the designated service application obtains the target service information; through the designated service application, executing the corresponding target service according to the target service information.

The invention belongs to the technical field of Internet of Things data security, and provides an Internet of Things data confidentiality reading method and system based on a block chain, traced key fragments in a plurality of key fragments on the block chain are analyzed, the overall leakage difficulty degree of the multi-key fragments is evaluated, and for a storage hard disk with a relatively low leakage difficulty evaluation value, the leakage difficulty of the storage hard disk is evaluated. For a hard disk with high risk, key management needs to be enhanced, when a multi-key fragment easy-to-divulge signal is generated, a reference time consumption interval is acquired, and dynamic delay optimization operation is performed on time consumption for reading the traced key in the whole multi-key fragment according to the reference time consumption interval, so that the time consumption of the traced key in the whole multi-key fragment is reduced, and the time consumption of the traced key in the whole multi-key fragment is reduced. According to the method, different traced key fragments are endowed with different delay adjustment amounts according to the traced reading delay adjustment interval, the reading time consumption difference is increased, and the analysis and prediction difficulty of an attacker is increased, so that attack behaviors are effectively resisted, and the confidentiality of Internet of Things data in a block chain environment is guaranteed.