406results about How to "Accurate acquisition" patented technology

The invention discloses an intelligent legal instrument generation method and system based on a large model, and relates to the technical field of natural language processing. According to the method, law related texts are collected through multiple channels and preprocessed, a law domain knowledge graph is constructed, and after pre-training is conducted through a BERT model, the graph and a document sample are fused for fine tuning training; a user selects a document type and an input parameter by means of the interactive interface and transmits the document type and the input parameter to the model to generate a first draft of the legal document, and then multi-dimensional evaluation and optimization circulation are carried out until the legal document reaching the standard is output; the method covers the whole process of data processing, knowledge graph construction, model training and document generation evaluation, enriches knowledge reserve by using multi-source data, improves model pertinence by combining pre-training and fine tuning, and guarantees document quality through multi-dimensional evaluation. The problems of low legal instrument writing efficiency, unstable quality and the like are effectively solved, the legal instrument generation efficiency and quality are improved, and intelligent development of the legal field is promoted.

The embodiment of the invention discloses a bridge bolt monitoring image recognition method and system based on deep learning, and belongs to the technical field of bridge image processing. The method comprises the following steps: acquiring a multi-angle monitoring image set of a bridge bolt part through an image acquisition device, and preprocessing the monitoring image set to generate a standardized target image sequence; positioning a bolt monitoring area for each image frame in the target image sequence based on a pre-trained positioning model, and generating an area coordinate set containing bolt position information; inputting the region coordinate set into a state recognition model, extracting structural state features of each bolt monitoring region, and generating a looseness degree prediction result of the bolt part according to the structural state features; according to a matching result of the looseness degree prediction result and a preset safety threshold range, a bolt state abnormity alarm signal is output; and associating the bolt state abnormity alarm signal to the corresponding monitoring image frame, and generating a monitoring report containing a visual mark.

The invention relates to the technical field of wastewater treatment, in particular to a generation method for a chemical production wastewater treatment system control model. The method comprises the following steps: collecting chemical wastewater data by using an online monitoring instrument, wherein the chemical wastewater data comprises tin-containing wastewater data and etching liquid waste liquid data; determining a wastewater recovery control stage according to the chemical wastewater data; constructing a wastewater control model by utilizing chemical engineering simulation software based on the wastewater recovery control stage; inputting the chemical wastewater data into a wastewater control model, simulating a wastewater recovery control process by using simulation software to obtain wastewater recovery control data, and performing control abnormality judgment on the wastewater recovery control data to obtain abnormal wastewater data; the high-definition industrial camera is used for collecting images of the waste water sedimentation tank, and a centrifugal pump image is recognized and obtained from the images of the waste water sedimentation tank. According to the method, wastewater recovery control is optimized based on a wastewater treatment technology, and the wastewater recovery efficiency and the anomaly detection rate are remarkably improved.

The invention belongs to the field of urban sewage treatment, and provides an inverse fuzzy dynamic optimal self-adaptive aeration control method based on sewage treatment. Comprising the steps of dissolved oxygen concentration kinetic model construction, inverse fuzzy dynamic multi-objective optimization algorithm design, evaluation network and long-term utility function setting, execution network design, actual controller design, execution error function determination, execution network and actual controller parameter optimization and aeration pump control. According to the method, the optimal set value of the dissolved oxygen concentration is obtained through calculation of the inverse fuzzy dynamic multi-objective optimization algorithm; an execution network is designed by utilizing a judgment network and a long-term utility function, and unknown dynamic information of the dissolved oxygen concentration kinetic model is identified; optimization of an execution network and an actual controller is realized through the evaluation network and the execution error function; through the actual controller with the optimal parameters, self-adaptive control over the aeration pump is achieved, the control precision of the aeration degree is improved, and operation energy consumption is effectively reduced.

The invention discloses an automatic environment air quality monitoring method and system, a product and a medium, and relates to the field of environment monitoring, and the method comprises the following steps: obtaining concentration data of malodorous chemical substances based on monitoring sensors in a plurality of monitoring stations; selecting the target monitoring point with the highest concentration data as a reference point, and marking a plurality of potential pollution sources based on the current wind direction and current wind speed data of the target monitoring point at the current monitoring time point; obtaining the reference distance between each potential pollution source and the reference point, the consistency degree with the current wind direction and emission historical data; calculating a pollution score of each potential pollution source based on the reference distance, the consistency degree and the emission historical data; determining the potential pollution source with the highest pollution score as a pollution starting point; and sending the position coordinate of the pollution starting point to a target client. By implementing the method, the accuracy of pollution source speculation can be improved.

The invention discloses an array type multichannel acoustic imaging device and an abnormal sound source positioning display method, and the device comprises a main microphone array which is used for collecting sound signals of a target region; the camera device is used for collecting an image of the target area; the thermal imaging device is used for collecting a thermal image of the target area; the first data processing and analyzing module is used for identifying an abnormal sound signal of the target area and preliminarily estimating the position of an abnormal sound source; acquiring sound field distribution of the abnormal sound source and generating a sound field image by using an acoustic imaging algorithm; the second data processing and analyzing module is used for inputting the change rate of the sound wave parameters of the unit area and the temperature into a second neural network model, obtaining the sound velocity of the unit area in the sound field image, calculating the temperature of the unit area, fusing the sound velocity of the unit area with the temperature of the corresponding unit area in thermal imaging and determining the abnormal temperature; and the display screen is used for displaying the sound field image marked with the abnormal temperature. The abnormal sound source can be effectively distinguished and positioned, and the abnormal temperature can be displayed.

The invention relates to an SF6 density table data abnormity self-diagnosis method, a storage medium and equipment, and the method comprises the following steps: obtaining a data collection time sequence corresponding to a to-be-diagnosed SF6 density table based on the uploading data of the to-be-diagnosed SF6 density table, and at each detection moment, obtaining a data collection time sequence corresponding to the to-be-diagnosed SF6 density table based on the real-time density time sequence; judging whether the change of the density measurement value exceeds a set fluctuation threshold value or not, and if so, judging the change direction of the density measurement value; judging whether air leakage exists or not based on the air pressure time sequence, and if yes, generating an air leakage alarm signal; and calculating a correlation coefficient of the real-time environment temperature time sequence and the density time sequence, judging whether the density value change and the environment temperature change have high negative correlation or not, and if so, judging that the density value change is caused by the fact that the environment temperature at the installation position of the density meter is higher or lower than the air chamber temperature of the electrical equipment body. Compared with the prior art, the method has the advantage that the change reason of the SF6 density value can be accurately and quickly judged.

The invention discloses a double-arm collaborative operation method suitable for a transformer substation tubular bus carrying electrified robot, and relates to the technical field of power system automation. Comprising the following steps: comparing an electromagnetic change threshold value with a dynamic threshold value to obtain an electromagnetic environment change parameter and an early warning signal; adjusting the control parameters of the robot and the sensitivity of a sensor through the early warning signal; determining a strong electromagnetic field area through the electromagnetic environment change parameters, and planning an inspection path of the robot; and according to the inspection path, carrying out tubular bus-bar drainage wire lapping / dismounting operation at the target position. According to the method, the electromagnetic environment change in the transformer substation is monitored in real time, the electromagnetic change threshold value is determined and compared with the dynamic threshold value, and the early warning signals of different levels are generated, so that an operator can be reminded in time or robot parameters can be automatically adjusted, and equipment faults or safety accidents caused by a strong electromagnetic field are avoided.

The invention provides a fault judgment method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining target log data within a preset duration based on fault occurrence time of a target server; extracting target keywords in the target log data based on preset keywords, and determining a target log vector corresponding to the target log data based on the TF-IDF value of each target keyword; and predicting the fault type of the target server based on the target daily vector and the sample fault machine data set by using a KNN algorithm. The log vector is determined through the TF-IDF value based on the keyword, the fault type is judged based on the log vector by using the KNN algorithm, automatic judgment of the fault type is realized, and the TF-IDF can reflect the unique contribution of the keyword to the log data, so that the log vector can reflect the unique contribution of different keywords, the original log data features are better reflected, and the reliability of the log data is improved. Based on the daily vector data judgment, a fault judgment result can be obtained more accurately, and the efficiency and accuracy of fault judgment are improved.

The invention discloses an intelligent compilation system and method of a building construction scheme, and the system comprises a data preprocessing module which is used for obtaining historical construction scheme text data of each building engineering project category; the knowledge base construction module is used for constructing a construction scheme knowledge base of each construction engineering project category by establishing a vector index of a construction scheme vector database of each construction engineering project category; the retrieval information extraction module is used for performing keyword extraction on the construction scheme retrieval statement of the construction engineering project input by the user, and mapping and recalling the construction scheme text data of a plurality of corresponding construction engineering projects; and the construction scheme compiling module is used for obtaining a construction scheme compiling basis of the construction engineering project. Associated storage and value utilization of previous engineering construction schemes are achieved, the scheme compiling efficiency and reliability are improved through intelligent generation of the scheme compiling basis, and effective guarantee is provided for the scheme compiling quality.

The invention relates to the technical field of railway line flaw detection, in particular to railway line automatic comprehensive flaw detection equipment which comprises two steel rails and a flaw detection car and further comprises a C-shaped mounting plate, a buffer assembly, a waist detection mechanism and a bottom detection mechanism. A first fixing rod is transversely arranged in the C-shaped mounting plate, fixing sleeves are slidably connected to the two ends of the first fixing rod correspondingly, and balance assemblies are arranged at the ends, away from each other, of the two fixing sleeves correspondingly. The device has the advantages that different detection assemblies are arranged for different detection areas, so that steel rail detection of different parts is more efficient and accurate, it is ensured that different types of defects can be detected, the detection period is shortened, the balance assembly and the buffer assembly cooperate with each other to enable the head detection assembly to keep a dynamic balance state, and the detection efficiency is improved. The probe is effectively protected from vibration damage, and the adaptability of the probe to the change of the steel rail and the detection stability of the probe are improved.

The embodiment of the invention discloses a tea steaming control method based on capacitance liquid level detection, and relates to the technical field of tea steaming, the tea steaming control method is applied to the tea steaming function of a tea bar machine, the tea bar machine comprises a liquid container, a water suction pump and a water level detection area arranged on the side wall of the liquid container, and a plurality of longitudinally distributed electrode plates are arranged in the water level detection area; the method comprises the following steps: executing a heat preservation process after executing a first tea boiling and steaming operation according to a preset first tea steaming parameter; after the user performs at least one time of tea water taking operation, the real-time remaining water level in the liquid container is collected through the water level detection area; when the real-time residual water level meets a preset tea making parameter adjusting threshold value, the first tea steaming parameter is adjusted according to the real-time residual water level and the pre-obtained tea steaming frequency corresponding to the first tea boiling and steaming operation, and tea steaming control is conducted according to the adjusted second tea steaming parameter. By dynamically adjusting the tea steaming parameters, it is ensured that the appropriate tea water concentration can be obtained in each time of tea steaming, and therefore the tea drinking experience of a user is remarkably improved.

The invention discloses a digital construction organization 4D analogue simulation method, which comprises the following steps of S1, determining an integral construction group; s2, simulating a construction scheme; s3, optimizing a construction scheme; s4, performing field tracking and iterative updating; and S5, progress optimization. The method has the advantages that the BIM three-dimensional construction model of the key control engineering of the expressway is created by utilizing a three-dimensional simulation technology, comprehensive performance evaluation is carried out on the model, construction organization design is carried out on the model, a reasonable construction procedure and a reasonable component movement relation are constructed, and 4D visual dynamic simulation of the whole construction process is realized.

The invention relates to microwave three-dimensional modeling, in particular to a radar microwave-based spatial 3D modeling method, which comprises the following steps of: scanning a target space by using a microwave radar, and collecting echo signals of an object in the target space; the collected echo signals are preprocessed; calculating a three-dimensional coordinate of a reflection point in the target space; performing data registration on the positions of the reflection points corresponding to the echo signals acquired in different time periods, and extracting the position, shape and size of an object in the target space; generating point cloud data of the target space according to the registered reflection point positions, and constructing a spatial three-dimensional model; according to the technical scheme provided by the invention, the defect that precise space 3D modeling cannot be realized by utilizing radar microwaves in the prior art can be effectively overcome.

The invention discloses a building performance monitoring system based on BIM and Internet of Things technology, and relates to the field of building performance monitoring, comprising: a BIM model construction and integration module creating and integrating a building BIM model; the Internet of Things sensor deployment module deploys a sensor; the data acquisition and transmission module acquires and transmits data; the data processing and analyzing module processes and analyzes the data; the building performance evaluation and early warning module performs evaluation and early warning; and the user interaction and visualization module realizes interaction and visualization. And each module has corresponding technologies, such as IFC format integration and low-power consumption sensor, so that the performance is improved. The building performance can be effectively monitored, the BIM model is integrated, comprehensive monitoring, intelligent analysis, accurate evaluation and early warning are achieved, interaction visualization is convenient and fast, safe and comfortable operation of the building is guaranteed, and management and maintenance are convenient.

The invention relates to the technical field of medicine detection, and discloses medicine raw material detection equipment for improving the purity of raw materials, the medicine raw material detection equipment comprises a base and a supporting box, the bottom of the supporting box is fixedly connected to the outer side of the base, the top of the base is fixedly connected with a detection mechanism, and the top of the detection mechanism is fixedly connected with a detection plate; the top end of the supporting box is fixedly connected with a driving box, multiple filtering and impurity removing can be conducted on medicine raw materials through the impurity removing assembly, impurities in the raw materials can be screened out while the caked raw materials are screened out, the purity of the medicine raw materials is improved, the content of invalid or harmful ingredients in medicine can be reduced by removing the impurities, and therefore the medicine raw materials can be conveniently taken out. The purity and quality of the medicine are improved, the raw materials with higher purity can be used for preparing the medicine which is more efficient, safer and more stable, the treatment effect and the satisfaction degree of a patient are improved, and the content of active ingredients of the medicine can be improved by removing impurities, so that the curative effect of the medicine is enhanced.

The invention provides a question and answer search method and device and terminal equipment. The method comprises the steps that question information is acquired; according to the question information, determining at least one search mode corresponding to the question information in a plurality of search modes; and processing the question information according to the at least one search mode to obtain answer information corresponding to the question information, and performing answer display according to the answer information. The accuracy of searched answers is improved, and the efficiency of searching answers is improved.

The invention relates to the technical field of automatic measurement of flow and liquid level, and discloses a gas flow online calibration system which comprises a component extraction module used for acquiring real-time sensor data, performing spectral component analysis on the sensor data, obtaining component data and calculating characteristic data of the component data; the preliminary compensation module is used for acquiring environment data and mass flow meter data, and performing environment compensation on the mass flow meter data by using the environment data to obtain preliminary calibration flow; the relation construction module is used for constructing a gas component association relation according to the characteristic data and the preliminary calibration flow; and the compensation calibration module is used for performing self-adaptive compensation on the initial calibration flow by using the gas component association relationship and the characteristic data to obtain calibration data. The problem that an existing gas flow online calibration system is still low in calibration precision can be solved.

The invention relates to an integrated experiment table system for measuring electrolytic performance and internal temperature of an alkaline water electrolytic bath. The integrated experiment table system comprises an environment box, the alkaline water electrolytic bath for experiments, a direct-current power supply, a hydrogen side gas-liquid separation bottle, an oxygen side gas-liquid separation bottle, a temperature measuring line, a paperless recorder and a constant-temperature water bath. The alkaline water electrolytic bath for experiments can change flow field design, small chamber scale, heat dissipation and bath body environment temperature control components so as to meet diversified experiment requirements. And the alkali liquor circulating pump is connected with the gas-liquid separation bottle and the electrolytic bath to realize alkali liquor circulation. And the computer terminal is in communication connection with the direct-current power supply, the paperless recorder and the alkali liquor circulating pump and is used for data collection and component control. The hydrogen-side gas-liquid separation bottle and the oxygen-side gas-liquid separation bottle have specific structures for gas-liquid separation and alkali liquor treatment. Compared with the prior art, the experiment table system is easy to disassemble and assemble, stable in operation, capable of decoupling key parameters and obtaining dynamic temperature data in the electrolytic cell, large in freedom degree and capable of guiding industrial hydrogen production strategy making and assisting related research and product research and development of the alkaline water electrolytic cell.

The invention relates to the technical field of arc-shaped screens, and discloses a 3D game scene adaptation method and device based on an arc-shaped screen, and the method comprises the steps: carrying out the three-dimensional coordinate sampling of the surface of the arc-shaped screen, constructing an arc-shaped screen space model, and carrying out the dynamic tracking in a 3D game scene according to the arc-shaped screen space model, and obtaining scene mapping data; performing spatial distortion vector construction and compensation transformation analysis based on the scene mapping data to obtain target scene data; constructing a control grid node by using the curved surface feature tensor, applying a deformation constraint condition to the control grid node, and solving a deformation energy equation to obtain scene deformation control data; the rendering control instruction is created based on the scene deformation control data, and scene state acquisition and space adaptation calculation are executed according to the rendering control instruction to obtain the scene display data, so that accurate correction of scene display is realized, the image quality is remarkably improved, and the stability and continuity of scene display are ensured.

The invention relates to the technical field of pipeline detection equipment, and provides a pipeline crawler aiming at the situation that impurities in a pipeline easily interfere with detection of a pipeline crawler detection instrument, the pipeline crawler comprises a rack, a control system, an image acquisition mechanism, a detection mechanism, an axial walking mechanism, a circumferential walking mechanism and a cleaning mechanism; the axial walking mechanism and the circumferential walking mechanism are both installed on the periphery of the rack, the axial walking mechanism is used for driving the support to move in the axial direction of the pipeline, and the circumferential walking mechanism is used for driving the rack to move in the circumferential direction of the pipeline; the cleaning mechanism is located on the periphery of the rack and comprises a cleaning brush and a first sliding driving part, the cleaning brush is used for brushing the inner wall of a pipeline, and the first sliding driving part is used for driving the cleaning brush to move in the direction close to or away from the rack. The device has the effect of reducing interference of impurities on the inner wall of the pipeline to detection equipment.

The invention belongs to the technical field of AI image recognition, and particularly relates to a visualization method and system based on AI image discrimination, a terminal and a storage medium, and the method comprises the steps: S1, obtaining the actual type of a target object, and carrying out the regional processing of the target object according to the actual type; s2, acquiring actual view information of each sub-region through AI imaging equipment; s3, performing optimization preprocessing on the actual view information to obtain preprocessed view information; s4, extracting and processing the preprocessed view information to obtain actual image features; and S5, comparing the preprocessed view information with the actual image features through an AI image recognition technology to obtain a comparison result. According to the method, a large amount of complex image data can be automatically identified and analyzed, the need of manual intervention is reduced, the data processing efficiency is remarkably improved, and the learning and adaptive capacity of the system to new conditions is also enhanced.

The invention discloses multifunctional water quality parameter monitoring, sampling and analyzing equipment, and relates to the technical field of water quality sampling and analyzing equipment.The multifunctional water quality parameter monitoring, sampling and analyzing equipment comprises a sealed shell and a water quality monitoring device.The sealed shell is internally provided with a storage assembly used for continuously extracting water samples multiple times and annularly storing the water samples; a sampling assembly used for accurately obtaining water quality samples of different depths is arranged in the sealing shell, through the use of a crushing assembly, a pipe descending motor drives a driving bevel gear to rotate, a blocking conical cylinder drives a cutting blade to rotate, and the inclined surface of the blocking conical cylinder shovels off wound aquatic plants and sundries from the outer side of a spring pipe; meanwhile, the cutting blade rotates to cut off the wound aquatic plants and sundries, so that the effect of removing the aquatic plants and sundries wound on the outer side of the bourdon tube is achieved, and compared with the traditional sampling device which goes deep into the water bottom and is wound by the aquatic plants and sundries, the equipment can cut off the aquatic plants and sundries wound on the bourdon tube; and the situation that next water taking is affected by winding of the equipment in the using process is reduced.

The invention relates to the technical field of intelligent traffic, and discloses a deep learning-based expressway traffic flow detection method and system, and the method comprises the steps: obtaining multi-modal traffic data and environment data in real time from each key road section of an expressway, and carrying out the preprocessing of the multi-modal traffic data obtained in real time, including the time-space alignment of the multi-modal traffic data; inputting the preprocessed multi-modal traffic data and environment data into a pre-trained deep fusion network model, and outputting various vehicle parameters for representing expressway traffic flow characteristics; inputting the various vehicle parameters into a pre-trained high-speed traffic flow detection model, and outputting traffic flow grade information; dynamically updating the deep fusion network model at the key road section by adopting a model fusion mode according to the vehicle parameter change condition at each key road section within the preset time; and updating the high-speed traffic flow detection model according to external conditions introduced by the traffic flow grade information in actual use. And the accuracy and real-time performance of high-speed traffic flow detection are improved by combining deep learning.

The invention provides an amplitude-frequency modulation signal decomposition method and device, and relates to the technical field of electric power. The method comprises the following steps: acquiring an amplitude modulation signal and a frequency modulation signal; decomposing the amplitude modulation signal to obtain a first decomposition result of the two-phase voltage under a two-phase rotating coordinate system; decomposing the frequency modulation signal to obtain a second decomposition result of the two-phase voltage under the two-phase rotating coordinate system; and synthesizing the first decomposition result and the second decomposition result to obtain an amplitude-frequency modulation signal decomposition result of the two-phase voltage under the action of an amplitude and frequency common modulation signal in a two-phase rotating coordinate system. The device executes the method. According to the amplitude-frequency modulation signal decomposition method and device provided by the embodiment of the invention, the oscillation component information can be completely reserved through amplitude-frequency modulation signal decomposition, so that the oscillation frequency information can be accurately obtained.

The invention provides an earthwork construction dynamic scheduling method and equipment based on deep reinforcement learning, and a storage medium. The method comprises the steps of obtaining construction information, determining an integrated scheduling target of constraint conditions and construction equipment, and setting a target function; expressing an integrated scheduling problem of the construction equipment as a Markov dynamic decision process, and generating a first agent; designing a reward function based on NSGA-II and DDQN algorithms to train the first agent; generating an initial scheduling scheme, and executing virtual scheduling based on the scheme; on the basis of the assumed disturbance event supplementary constraint condition, generating a second agent through a Markov dynamic decision process; distinguishing jobs in the initial scheduling scheme, and designing encoding and decoding methods of an NSGA-II algorithm according to a distinguishing result; designing a reward function to train a second agent based on the NSGA-II algorithm and the DDQN algorithm after the coding and decoding are designed; and deploying the intelligent agent after training stabilization in an actual construction environment, and generating a dynamic scheduling decision.

The invention discloses an illness state early warning system based on mobile nursing, and relates to the technical field of medical nursing, the illness state early warning system comprises a data acquisition module, a cloud memory, an illness state analysis module and a mobile nursing platform; and the data acquisition module is used for acquiring patient information. According to the illness state early warning system based on mobile nursing, the system obtains comprehensive patient information through the data acquisition module, and the cloud memory is used for caching, so that the integrity and traceability of data are ensured; a disease state analysis module adopts a disease diagnosis model combining a support vector machine and a neural network to compare and analyze vital sign features and image features of the patient with standard data and a typical model in a medical knowledge base, so that subjectivity caused by manual judgment only depending on doctors is avoided, the diagnosis accuracy is improved, and the diagnosis efficiency is improved. Therefore, the problems that disease diagnosis in an existing medical system is high in subjectivity, complex change trends are difficult to find, and timeliness is insufficient are solved.

The invention discloses an earth surface exposed geologic body reality sense three-dimensional reconstruction method based on a neural radiation field. The method comprises the steps that an earth surface geologic body image data set is acquired; performing feature matching on the image data set by using a feature matching strategy based on a nearest neighbor algorithm and a LightGlue neural network to generate feature point matching information and a feature description file; sparse three-dimensional point cloud data and camera pose information are obtained based on incremental SfM; and obtaining depth information of an image data set based on sparse three-dimensional point cloud data and camera pose information, and establishing a geologic body realistic three-dimensional reconstruction model by using a neural radiation field optimization method fusing the depth information and Gaussian position coding. According to the method, the feature matching precision and the camera pose calculation accuracy are improved, the texture detail expression ability of a geological structure can be improved, the reconstruction quality of a surface geologic body model is enhanced, and geological information support can be provided for the fields of geological research and engineering application.

The invention relates to the technical field of insurance risk assessment, and particularly provides an insurance strategy generation method and system based on reinforcement learning, a terminal and a medium, and the method comprises the steps: building an authorization connection relation between a user and an insurance company, and enabling the insurance company to obtain the multi-modal data of the user; constructing a deep learning model, and training a risk assessment model based on the multi-modal data in the plurality of preset time windows; configuring an insurance strategy for the user based on the user state and the risk probability, and training a reinforcement learning model based on the user state, the risk probability and the insurance strategy; and obtaining current multi-modal data in the adjusted time window based on the adjusted data acquisition frequency and acquisition priority, inputting the current multi-modal data into a risk assessment model to obtain a current predicted user state and risk probability, and inputting the current predicted user state and risk probability into a reinforcement learning model to obtain a current insurance strategy. The scientificity and adaptability of insurance services are improved, and the influence caused by inverse selection risks is reduced.

The invention belongs to a computer vision technology, mainly relates to the field of laser weeding, and particularly relates to a pixel coordinate and galvanometer scanner offset mapping method based on laser point detection and application. The method is mainly used in the field of laser weeding, and is used for calculating galvanometer offset through weed pixel position information acquired by a camera and controlling laser to accurately reach a weed point. The invention provides a method for directly mapping a target from pixel coordinates to galvanometer offset. According to tests, the average precision error of the method is within 2 mm, the maximum error does not exceed 5 mm, the error does not exceed 3 mm under the 88% condition, and the requirement for precise weeding can be met.