159results about How to "Stable execution" patented technology

The invention relates to the technical field of unmanned aerial vehicles, in particular to a mooring unmanned aerial vehicle safety management system which comprises a multi-source data acquisition module, a data fusion and analysis module, an intelligent risk assessment module, a control instruction generation module and an execution mechanism module. The multi-source data acquisition module acquires flight and mooring cable data of the unmanned aerial vehicle by using various sensors, and transmits the flight and mooring cable data to the data fusion and analysis module through a time division multiple access protocol with low packet loss rate and low delay; the intelligent risk assessment module judges a risk level by combining a risk assessment model based on a support vector machine and a Bayesian network algorithm according to the information, and generates prompt information if the risk level exceeds a preset range; the control instruction generation module generates instructions according to a risk prompt and a preset strategy, ranks the instructions and sends the instructions to the execution mechanism module; a flight control system in the execution mechanism module cooperates with a mooring cable electric take-up and pay-off device and the like, real-time adjustment and control over the flight attitude of the unmanned aerial vehicle and the cable state are achieved, and it is ensured that tasks are safely and stably executed in the complex environment.

The invention provides a low-altitude industry chain information intelligent cooperation and airspace management platform based on federal learning. Through cluster ad hoc network and decentralized federated learning, the method is divided into three stages of data acquisition, data preprocessing and analysis application, low-altitude scene data communication of dynamic topology and static topology is realized, and the efficient communication requirement in a low-altitude operation scene is met. According to the system, differential data transmission strategies are adopted, optimization design is carried out on a single machine, a co-task cluster, a cooperative cluster and a non-cooperative cluster, and the communication efficiency and the resource utilization rate are improved. In the data preprocessing stage, federated learning aggregation of multi-source data fusion, data anonymization and decentralization is combined, and data privacy protection and safe sharing of three parties of industry, university and research are ensured. In the analysis and application stage, low-altitude aircraft task scheduling, airspace flow control and environmental condition evaluation are realized through aircraft analysis, airspace analysis, environmental analysis and digital twinborn technologies.

The invention relates to the field of juicer communication, in particular to a background communication method and a background communication system for a juicer system. The method comprises the following steps: obtaining a fruit and vegetable image reserved in a juicer; performing self-adaptive juicing feature analysis on the reserved fruit and vegetable image, performing intelligent juicing parameter adjustment, and constructing a self-adaptive juicing strategy; identifying surrounding environment parameters of the juicer; according to the surrounding environment parameters of the juicer, a self-adaptive juicing strategy is carried out, environment trend influence intelligent adjustment is carried out, juicing control simulation is carried out, and juicing control simulation data are obtained; multi-period juicing effect evolution is carried out on the juicing control simulation data, abnormal state prediction is carried out, and juicer abnormal early warning signals and juicer abnormal fault prediction information are generated; acquiring the network access state of the current juicer; through efficient and rapid background communication, the juicer use experience and performance of a user are improved.

The invention discloses a large-depth pressure-resistant communication antenna of an unmanned underwater vehicle and the underwater vehicle, and belongs to the technical field of underwater vehicles, the antenna comprises an antenna shell, a pressure-resistant cabin body and a fin-shaped component, the pressure-resistant cabin body is a component forming a cabin body segment of the underwater vehicle, and the fin-shaped component is a fin-shaped component. The antenna shell comprises a radial supporting part fixed to the pressure-resistant cabin and a shell part fixed to the top end of the radial supporting part, the fin-shaped component is fixed to the radial supporting part, an antenna unit is installed in the shell part, and a wireless communication function unit connected with the antenna unit is arranged in the pressure-resistant cabin. The large-depth pressure-resistant communication antenna of the unmanned underwater vehicle has the advantages of being excellent in communication quality, high in pressure resistance, optimized in size, high in space utilization rate, stable and reliable for a long time and the like, and can meet operation requirements in a deep sea environment.

The invention relates to the technical field of ship mooring scheduling, in particular to an intelligent scheduling method and system for ship mooring. The method comprises the following steps: acquiring ship basic information and wharf facility equipment data; establishing a ship berthing rule, and obtaining a ship berthing initial plan by using the ship basic information and the ship berthing rule; obtaining an auxiliary equipment distribution plan according to the ship mooring initial plan and the wharf facility equipment data, and obtaining a ship mooring initial scheduling plan in combination with the ship mooring initial plan and the auxiliary equipment distribution plan; and constructing a ship mooring plan evaluation model, evaluating the initial ship mooring scheduling plan by using the ship mooring plan evaluation model, adjusting the initial ship mooring scheduling plan according to an evaluation result, and obtaining an optimal ship mooring scheduling plan. According to the invention, the problem of intelligent scheduling of port ship berthing is solved, intelligent scheduling of berthing and unberthing of ships is realized, and the operation efficiency and safety of a port are improved.

The invention relates to a smeltery surrounding soil heavy metal monitoring distribution and health assessment method and system. The method comprises the following steps: acquiring heavy metal pollutant emission data, regional topographic data, meteorological data and population data; obtaining heavy metal settlement data according to the heavy metal pollutant emission data, the regional topographic data and the meteorological data; arranging soil monitoring points according to the heavy metal settlement data in combination with the regional topographic data and the meteorological data; and calculating the health risk according to the population data and the heavy metal settlement data. According to the invention, the problems of too many sample distribution and inaccurate distribution of heavy metal in the surrounding soil of the smeltery in the prior art are solved, the problem that the influence of the smeltery on the health of surrounding people is not fully considered is solved, the accuracy and efficiency of monitoring distribution are improved, and according to the monitored heavy metal settlement data, the real-time monitoring of heavy metal settlement is realized. And health assessment is carried out on surrounding residents, so that prevention of diseases and control of the environmental pollution degree are facilitated.

The invention relates to the technical field of tire quality evaluation, in particular to a tire characterization method and system based on a transverse force coefficient, and the method comprises the following steps: selecting a test tire and a test road section, and obtaining tire test data based on the test tire and the test road section; setting a data quality analysis model, and performing quality detection on the tire test data by using the data quality analysis model to obtain target test data of the tested tire; building a tire characterization index analysis mechanism, and obtaining tire characterization parameters based on the tire characterization index analysis mechanism and the target test data; obtaining characterization parameter characteristic information of the tire characterization parameters based on the target test data; and obtaining a transverse force friction coefficient according to the characterization parameter characteristic information, and analyzing and evaluating the tire performance of the tested tire according to the transverse force friction coefficient. The tire is tested based on the transverse force friction coefficient, and the use performance of the tire is effectively known.

The invention relates to the technical field of dynamic monitoring and slope protection and reinforcement, in particular to a cutting slope protection and reinforcement method and system based on a dynamic monitoring technology, and the method comprises the following steps: building a cutting slope real-time monitoring network according to the dynamic monitoring technology, and obtaining the dynamic monitoring information of a cutting slope through the cutting slope real-time monitoring network; a cutting slope multi-dimensional analysis system is constructed based on the dynamic monitoring information and cutting slope protection and reinforcement requirements; obtaining a first index analysis result, a second index analysis result and a third index analysis result of the cutting slope according to a cutting slope multi-dimensional analysis system and the dynamic monitoring information; and making a cutting slope protection reinforcement scheme by combining the first index analysis result, the second index analysis result, the third index analysis result and the dynamic monitoring information. According to the invention, real-time monitoring and multi-dimensional analysis are carried out on the cutting slope based on a dynamic monitoring technology, the feasibility of cutting slope protection and reinforcement measures can be improved, and the quality and benefits of a project are improved.

The invention discloses a method and device for elastically and telescopically supporting NodeManager resource scheduling of a big data cluster. The method comprises the steps that S01, host load evaluation and resource management are carried out, and whether the load of a host is excessive or not is judged; s02, according to a NodeManager resource optimization strategy, dynamic optimization of resources is carried out; s03, automatic management of NodeManager resources: according to the data obtained in the step S01, determining whether the resource allocation of the NodeManager needs to be adjusted or not; and S04, identifying and processing NodeManager resource saturation, and discovering a NodeManager machine with resource saturation in time by continuously monitoring a cluster state. According to the method and the device for elastically and telescopically supporting the NodeManager resource scheduling of the big data cluster, the NodeManager resource scheduling of the big data cluster can support automatic elastic telescoping through the technical means of improving the NodeManager resource utilization rate of a single physical machine, controlling the upper limit of the NodeManager resource of an over-configured CPU and a memory, discovering and responding to a saturated machine, expelling running tasks and the like.

The invention relates to the technical field of cloud manufacturing, in particular to a cloud manufacturing quality control and defect prediction method and system based on deep learning. The method comprises the following steps: acquiring production field data in a manufacturing process through data acquisition equipment, and uploading the production field data to a cloud for next analysis; extracting information features of the production field data and performing feature fusion to obtain an information data feature set; constructing a joint deep learning prediction model, and training the joint deep learning prediction model by using the information data feature set; and completing cloud manufacturing quality control and defect prediction through the trained joint deep learning prediction model. The cloud manufacturing quality control and defect prediction are completed by extracting various characteristics of the production field data and training the joint deep learning prediction model, the quality problem and the defect prediction problem in the manufacturing process are solved, the production efficiency is effectively improved, the product quality is optimized, and the intelligent and automatic upgrading of the manufacturing process is promoted.

The invention relates to the technical field of slope disaster monitoring, in particular to a high and steep slope geological disaster monitoring method and system based on multi-source data fusion. The method comprises the following steps: tracking surface deformation through PS-InSAR time sequence analysis and atmospheric phase correction to obtain surface deformation characteristics; identifying the apparent diseases of the slope, and extracting spatial and temporal distribution characteristics of the apparent diseases of the slope; analyzing spatio-temporal evolution characteristics under geologic structure constraints by utilizing slope rock mass structure characteristics and the earth surface deformation characteristics; according to underground water level dynamic and potential sliding surface weakening features and the slope apparent disease spatial and temporal distribution features, extracting disaster-causing key factor features after cooperative correction; and combining the disaster-causing key factor characteristics, the true three-dimensional geological environment background characteristics and the spatio-temporal evolution characteristics to analyze the comprehensive early warning grade and the potential instability mode of the landslide. Scientific support is provided for high and steep slope geological disaster prevention and control, and engineering construction and operation safety can be guaranteed.

The invention relates to the technical field of urban traffic management, in particular to a pavement defect monitoring and predicting method and system, and the method comprises the following steps: constructing a pavement digital twinborn model of a target pavement; constructing a historical road surface monitoring data set, and obtaining road surface monitoring index accurate data and road surface high-definition image data in real time; according to the road surface digital twinborn model and the road surface monitoring data set, obtaining the index weight of each road surface monitoring index by using a double-source weight fusion method; and updating the road surface digital twinborn model based on the road surface monitoring index accurate data, the index weight and the road surface high-definition image data, realizing real-time monitoring and prediction of target road surface defects, and formulating a road surface maintenance strategy. On the basis of the road surface digital twin model, the influence degree of each road surface monitoring index on the road surface defect is considered, the real-time, accurate and efficient monitoring and prediction of the road surface defect are realized, the road surface maintenance strategy is formulated in time, and the traffic capacity and safety of the road are guaranteed.

The invention relates to an intelligent planning method and system for recent mining of an open gravel mine. The method comprises the following steps: acquiring geological data of the gravel mine; formulating a medium and long term mining plan of the gravel mine; constructing an ore body entity model based on the gravel mine geological data and the medium and long term mining plan; constructing an ore body unit body model on the basis of the ore body entity model; setting an ore body unit ID for each ore body unit in the ore body unit model to obtain an ore body unit attribute file; based on the ore body unit attribute file, determining the mining mode of the open sand mine; constructing a recent planning optimization model of the open gravel mine; and calculating the optimal mining path of the open-pit sand-gravel mine by using the recent planning optimization model of the open-pit sand-gravel mine. Through the method and the device, the problems that the mining cost is increased and the efficiency is reduced due to the fact that the mining sequence cannot be flexibly changed due to no recent intelligent planning in related technologies are solved.

The invention relates to the technical field of slope ecological restoration evaluation, in particular to an ecological restoration evaluation method and system for a high and steep slope in a cold and cold mountainous area. The method comprises the following steps: acquiring ecological restoration status data of the high and steep slope in the cold and cold mountainous area; according to the ecological restoration current situation data, vegetation restoration state parameters of slope ecology are obtained; based on the ecological restoration current situation data, analyzing the water and soil conservation capability and nutritional value indexes of the slope soil, and obtaining soil restoration state parameters of the slope ecology through the water and soil conservation capability and the nutritional value indexes; the ecological restoration status data, the vegetation restoration state parameters and the soil restoration state parameters are combined to obtain slope ecological restoration evaluation indexes; and establishing a slope ecological restoration evaluation index system, and evaluating the ecological restoration condition of the high and steep slope in the cold and cold mountainous area according to the slope ecological restoration evaluation index system and the slope ecological restoration evaluation indexes. The method solves the problem of reasonably and effectively evaluating ecological restoration of the high and steep slope in the cold and cold mountainous area.

The invention relates to the technical field of cultural relic preservation environment monitoring, in particular to an intelligent cultural relic environment real-time monitoring method and system. The method comprises the following steps: acquiring a real-time monitoring infrared image of a cultural relic environment through infrared monitoring equipment; performing image enhancement processing based on the cultural relic environment real-time monitoring infrared image to obtain a cultural relic environment monitoring first optimized image; performing image reconstruction on the cultural relic environment monitoring first optimized image to obtain a cultural relic environment monitoring reconstructed image; and constructing an environment monitoring model, and combining the environment monitoring model and the cultural relic environment monitoring reconstruction image to complete intelligent real-time monitoring of the cultural relic environment. According to the method, the infrared image is enhanced and then reconstructed, and the environment temperature change is identified according to the reconstructed image, so that the problem of accurately monitoring the temperature and humidity distribution condition of the cultural relic preservation environment in real time is solved, and the cultural relics can be ensured to be in the optimal preservation environment.

The invention relates to the technical field of image recognition, in particular to a multi-goods-type material information recognition processing method and system. The method comprises the following steps: acquiring a material image in a Lab mode through image acquisition equipment; constructing a first image generation model, and combining the material image and the first image generation model to obtain a first image of the material image; in the first image, extracting texture features of the material image; on the basis of various machine classification models, the credibility of the various machine classification models is obtained by utilizing texture features of the multi-goods-type material image test samples; and according to the credibility and the material image, obtaining the joint credibility of the machine classification model for identifying the multiple kinds of materials, and completing identification processing of the information of the multiple kinds of materials based on the joint credibility. According to the method and the system, the efficiency of classifying, sorting and grading various materials in the dry bulk cargo transfer and storage process is improved by accurately identifying the information of the various kinds of materials.

The invention relates to the technical field of transaction risk control, in particular to a transaction risk control method and system, and the method comprises the following steps: obtaining platform transaction information through a transaction risk control system; setting a transaction data transmission and arrangement mechanism to arrange and detect the platform transaction information, and obtaining a transaction information transmission result; establishing an information feature analysis model according to the platform transaction information, and analyzing a transaction information transmission result by using the information feature analysis model to obtain transaction feature information of an online transaction platform; and analyzing a platform transaction condition based on the transaction feature information and the platform transaction information so as to guarantee risk control and safe operation of an online transaction platform. According to the transaction risk control method and system, the mathematical model is utilized, the transaction data transmission, arrangement, analysis and application processes are optimized, the user experience and the platform operation efficiency can be improved, and the safety and stability of the platform can be effectively guaranteed.

The invention provides an ROS-based flight control method in an unmanned aerial vehicle denial environment, and belongs to the technical field of unmanned aerial vehicle flight control. An unmanned aerial vehicle system for realizing the control method comprises an airborne computer main control module, a flight control module, a power module, a camera module, an optical flow module, a communication module and an upper computer module; the upper computer module is connected with the airborne computer main control module through the communication module, the flight control module, the camera module and the optical flow module are all connected with the airborne computer main control module, the flight control module is connected with the power module, and the camera module comprises a tracking camera module and a monocular camera module. Tasks such as autonomous takeoff, fixed-height hovering, fixed-point flying and autonomous landing can be achieved under the condition of GPS denial, accurate control is achieved, due to the ROS distributed design thinking, functions of the unmanned aerial vehicle become easy to achieve, and corresponding functions which do not need to be set can be started through one key only by packaging used modules and then writing the modules in a launch program.

The embodiment of the invention discloses a breakpoint continuous migration method and device for heterogeneous database distributed migration and a medium, belongs to the technical field of heterogeneous database migration, and solves the problems that after heterogeneous database migration is abnormally terminated, the whole migration process is usually restarted, resources are calculated, and the total migration time is prolonged. Comprising the steps that a system service node carries out persistence on migration execution information, and a migration service node carries out persistence on execution task information; in response to abnormal interruption of the system service node and / or the migration service node, after the system service node and / or the migration service node are / is recovered, the system service node determines a completed execution task and an uncompleted execution task based on the persistent migration execution information; starting a breakpoint continuous migration process, and redistributing the determined uncompleted execution task to a migration service node by the system service node; and the migration service node checks whether an uncompleted execution task is completed or not based on the execution task information, and returns an execution result to the system service node.

A valve core piece comprises a valve core piece and a connecting rod connected to the valve core piece, the valve core piece is arranged on the upper surface of a valve seat, the connecting rod penetrates out of a valve cover, a drainage channel communicated with the periphery of the bottom from the center of the bottom is formed in the valve core piece, the drainage channel is communicated with a first hole in the center position, and the first hole is communicated with a second hole in the center position. The drainage channel corresponds to the second hole in the circumferential direction at the peripheral position; the rotary drive is connected to the free end of the connecting rod; according to the frequency type automatic drain valve, the conduction state of the frequency type automatic drain valve can be adjusted through rotation of the valve element part, the working time of rotation driving can be accurately controlled in a timing mode, and compared with control achieved through a thermal power mode, an active control mode has the advantage of being stable in execution; under any condition, the on-off time per minute can be not more than 3 times, and the on-off time and the off time are strictly distributed and controlled according to the amount of condensed water generated by the system.

The invention relates to the technical field of wind profile radar data processing, in particular to a wind profile radar data adaptive quality control method and system under the influence of extreme weather. The method comprises the following steps: acquiring wind profile radar spectrum data, and calculating radial speeds of four inclined beams in the east, the south, the west and the north according to the wind profile radar spectrum data; obtaining a horizontal wind component of an inclined beam according to the radial speed; synthesizing the horizontal wind component to obtain a new wind speed of the inclined wave beam; and constructing a wind speed profile by using the new wind speed, obtaining an optimal wind speed profile in combination with a balloon sounding profile and the wind speed profile, and taking wind speed data of the optimal wind speed profile as product data. According to the three-beam detection principle, the optimal wind speed profile is obtained through the wind speed data resynthesized by the wind profile radar data, and the problem of poor availability of the wind profile radar observation data in extreme weather is solved.

The invention relates to the technical field of photoacoustic imaging, in particular to a three-dimensional photoacoustic imaging method and system based on a two-dimensional outline of an imaging part. The method comprises the following steps: extracting a two-dimensional contour of an imaging part, and planning a two-dimensional moving path according to the two-dimensional contour; according to the two-dimensional moving path, the position coordinates of the movement of the mechanical arm are obtained; adjusting the position of the photoacoustic imaging probe based on the position coordinates, and adjusting the posture of the photoacoustic imaging probe according to the mechanical information of the photoacoustic imaging probe; and completing the three-dimensional photoacoustic imaging of the target area by using the photoacoustic imaging probe with the updated attitude. According to the invention, full-coverage conformal three-dimensional photoacoustic imaging of the outline of the imaging part is realized through the low-cost two-dimensional camera, and the problems that in the three-dimensional photoacoustic imaging technology based on photoacoustic tomography, the luminous flux distribution of imaging planes in different target areas is inconsistent due to the fixed orientation of a probe, an imaging blind area exists, and the imaging range is limited are solved.

The invention relates to the technical field of rock mechanics and intelligent detection, in particular to a rock strength and failure mode prediction method and system. The method comprises the following steps: acquiring data of a rock sample to be detected to obtain a multi-source feature set; constructing a feature coefficient prediction model, and inputting the multi-source feature set into the feature coefficient prediction model to obtain a feature coefficient; screening the multi-source feature set based on the feature coefficient to obtain an optimal feature subset; constructing a rock strength and failure mode prediction model, and optimizing hyper-parameters of the rock strength and failure mode prediction model by adopting an automatic hyper-parameter optimization framework; and inputting the optimal feature subset into the optimized rock strength and failure mode prediction model to obtain a rock strength prediction value and a failure mode. The problem that rock strength and failure mode prediction precision is not accurate enough and cannot be predicted at the same time in the prior art is solved, and the prediction precision is greatly improved through multi-source data collaborative prediction.

The invention relates to the technical field of internet energy transaction, in particular to an energy internet transaction method and system based on a block chain, and the method comprises the following steps: collecting the electric quantity data of a user through an intelligent collection device, and carrying out the interaction with the block chain, the users comprise energy selling users and energy consumption users; making an intelligent contract used for being arranged on a block chain network based on a self-adaptive quotation competition strategy and a benefit guarantee strategy; a user registers on the energy transaction platform and submits a transaction request, and energy transaction is realized based on the smart contract and the power grid; and generating a new block by using the transaction information, and connecting the new block to the end of the block chain based on a consensus mechanism for storage. According to the invention, the fairness of energy transaction can be improved, and the earnings of the buyer and the seller are balanced.

The invention relates to the technical field of material carrying, in particular to a grab bucket grabbing point calculation method and system based on terrain distribution. The method comprises the following steps that point cloud data of materials in a cabin are obtained through radar equipment, and the point cloud data are divided into a plurality of grabbing areas according to the structure of the cabin; carrying out grid processing on the point cloud data in the grabbing area to obtain grid point cloud data; obtaining a grid value of a grid standard point according to the grid point cloud data; and constructing a target grabbing point screening model, and screening a target grabbing point in the grid point cloud data by combining the target grabbing point screening model, the grid value and the grab bucket parameter. According to the method, the point cloud data of the material terrain distribution are obtained through the radar equipment, and then the point cloud data are subjected to data analysis to obtain the optimal grabbing point, so that the problem of improving the material grabbing efficiency is solved.

The invention provides a high-precision and stability implementation method for PLCOPEN motion control, and the method comprises the following steps: S1, separating a user control logic task and a motor control service task to different threads for execution in a process of loading a PLC application program; s2, providing a motor motion control service on a motor control task by taking the function block as a unit; and S3, the user control logic executes the motion control function block. According to the PLCOPEN motion control high precision and stability realization method provided by the invention, the user control logic task and the motor control service task are separated to different threads for execution, so that the influence of the user logic execution time change on the motor control instruction issuing time can be avoided; through the separation, the motor control service task can be executed more stably and accurately, the control precision deviation caused by the instruction time problem is reduced, it is ensured that the motor motion can be carried out strictly according to expectation, and the control precision of the whole system is effectively improved.

The invention relates to the technical field of natural language processing, in particular to a multi-label classification data enhancement method and system based on a large language model. The method comprises the following steps: obtaining an original text data set, and obtaining a double-weighted label relation network according to the original text data set; performing tail driving sampling in the double-weighted label relation network, and generating a creative label of the original text data set according to a sampling result; generating a creative label text by using a large language model and the creative label; and combining the creative label texts to obtain multi-label classification enhanced data. According to the method, tail driving sampling is carried out after the label relation network is established by utilizing existing labels, label combinations are designed and innovated in consideration of label matching and style consistency, the number of instances of rare labels is increased, the problem of long-tail distribution is effectively solved, meanwhile, consistency and correlation with original data can be kept, and the method is suitable for large-scale popularization and application. And the generalization ability of the large language model in practical application is improved.

The present application relates to the technical field of industrial unmanned aerial vehicle application and intelligent scheduling, and particularly discloses an unmanned aerial vehicle highway inspection task intelligent planning management system, which comprises a task input module, an intelligent planning engine, a task execution management module, a data hub and a feedback optimization module; the task input module receives and checks and analyzes inspection task requirements and highway basic information; the intelligent planning engine decomposes task priorities based on highway multi-dimensional attributes, dynamically allocates unmanned aerial vehicle resources and generates an optimal path meeting multiple constraints; the task execution management module issues adaptive instructions, monitors unmanned aerial vehicle states and processes inspection data; the data hub uniformly stores whole-process data; and the feedback optimization module optimizes a decision model based on historical data. The present application improves inspection planning accuracy and resource utilization, guarantees data quality, realizes self-evolution and ensures efficient and reliable highway inspection.

The invention discloses a carbon electrode process control method and system, and the method comprises the steps: carrying out the secondary index division of multi-source data indexes of a carbon raw material, and constructing a comparable data space of the indexes of the raw material; establishing a comprehensive index system based on the comparable data space, and constructing a two-stage linear weight coupling structure based on the comprehensive index system to form an index fusion weight vector; based on the index fusion weight vector, constructing a multi-path evaluation decision model, and performing weighted calculation on each index in the comparable data space according to the index fusion weight to generate a corresponding sorting result; based on the sorting result, establishing a standard reaching probability prediction model, and correcting the sorting result according to the standard reaching probability; based on the corrected sorting result, unification processing of the process window is achieved, and a process parameter map is constructed; and carrying out process execution optimization and process monitoring on the carbon electrode production process based on the process parameter atlas. According to the method, the stability and reusability of the carbon electrode process decision are improved.

The present application relates to the field of earthquake monitoring and early warning, in particular to a dynamic evaluation and early warning method and system for active fault earthquake risk, which constructs and optimizes an active fault earthquake detection system according to historical information of an active fault monitoring area; a three-dimensional equidistant grid model of the active fault is established, and information collection points in the active fault earthquake detection system are screened according to an error analysis model of the collection points to determine target monitoring points of the system; information of the active fault is monitored through the detection system and the target monitoring points to obtain active fault earthquake monitoring data; the relative displacement of the active fault is predicted based on the monitoring data and the three-dimensional equidistant grid model, and the evaluation and early warning of the active fault earthquake are realized in combination with the relative displacement and the active fault earthquake monitoring data. The present application can monitor the active fault in real time and analyze the movement of the active fault, realize the evaluation and early warning of the active fault earthquake, and accurately predict the possibility and influence range of the earthquake.