41results about How to "Strong correlation" patented technology

The invention relates to the technical field of oil field oil production engineering, in particular to an underground data acquisition unit with flow, pressure and temperature monitoring functions and a method. The method is suitable for underground working condition monitoring of submersible motor type lifting equipment such as submersible screw pumps, submersible plunger pumps and submersible centrifugal pumps. The unit comprises a pressure-resistant shell, wherein a central pipe, an electromagnetic flowmeter, two pressure and temperature sensors and an underground parameter collector are integrated in the pressure-resistant shell; the two sensors are used for measuring the temperature and pressure of liquid flow of the central pipe and the temperature and pressure of an oil casing annulus respectively; the electromagnetic flowmeter measures the flow, and real-time temperature and pressure data are used for compensation to improve the precision. The unit is further provided with a collecting pipe, an upper end, a lower end, a connecting sliding ring, an annulus / oil pipe inner testing channel, a sealing rubber ring and the like. Through the integrated design, synchronous high-precision in-situ monitoring of underground key parameters is achieved, the problem that underground data of multiple instruments are not synchronous is solved, and a reliable data terminal is provided for an intelligent oil field.

The application relates to a business processing method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of cloud computing. The method comprises the following steps: determining a target group according to attribute data of a target object; obtaining group correlation degrees of each control group and the target group from a group correlation graph; determining the correlation degrees of each second historical business and the target object according to the group correlation degrees of the target group and the control group and the business correlation degrees of each second historical business and each first historical business; and determining a target business according to the correlation degrees of each second historical business and the target object in each control group. By using the method, the control groups having the correlation with the target object and the historical business data of the control groups having the correlation with the historical business data of the target object are fully referenced, so that the target object can be recommended with the business having a stronger correlation with the historical business, and the accuracy and reliability of business recommendation are improved.

The application discloses an advertisement conversion rate calibration method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a parameter cumulative value related to an estimated conversion rate of target advertisement data within a preset time length, each set of target advertisement data having the same dimension information under at least one dimension object and corresponding to the same identifier combination, and the target advertisement data being selected from M advertisement data; selecting a target parameter cumulative value from the parameter cumulative values of the multiple sets of target advertisement data corresponding to the preset time length according to the to-be-put advertisement data and the identifier combination corresponding to the to-be-put advertisement data; obtaining a calibration coefficient of the to-be-put advertisement data according to the target parameter cumulative value; and calibrating the estimated conversion rate of the to-be-put advertisement data by using the calibration coefficient to obtain a calibrated estimated conversion rate. By using the calibration method, the calibrated estimated conversion rate is more accurate.

The invention relates to the technical field of tunnel engineering, in particular to a cold region operation tunnel lining frost heaving influence test device and method.The device comprises a walk-in test box used for providing a uniform and controllable low-temperature environment, and a model box is arranged in the walk-in test box; a surrounding rock similar material, a tunnel lining model and a ponding simulation mechanism for simulating a ponding structure are arranged in the model box, the tunnel lining model and the ponding simulation mechanism are surrounded by the surrounding rock similar material, stress loading mechanisms are arranged on the top and the side wall of the model box, and a detection mechanism for detecting stress deformation displacement of the tunnel lining model is further included. According to the test device and the test method adopting the test device, the whole model is uniformly and controllably cooled through the step-in test box, a real temperature field where the tunnel in the cold region is located is accurately simulated, and the problems of uneven temperature and frost heaving simulation distortion caused by local refrigeration in the prior art are solved.

The invention relates to the technical field of integrated navigation, in particular to a positioning method and system based on optical angle measurement and astronomical-inertial integrated navigation. According to the method, firstly, a star image and a navigational satellite image are obtained at the same time by shooting a star map, after recognition and processing, the attitude of a camera relative to a geocentric inertial coordinate system is calculated by utilizing the star, and then the coordinate of the navigational satellite in the coordinate system is determined. And obtaining angle information of the navigation satellite relative to the observer under the earth coordinate system through coordinate transformation. Optical angle measurement information is fused with attitude, speed and position information output by an inertial navigation system, a Kalman filtering state equation and an observation equation are constructed, and finally real-time high-precision calculation and updating of the position of the observer are achieved. According to the method, the accuracy of optical angle measurement, the limited distance reference of celestial navigation and the autonomous continuity of inertial navigation are fused, and the navigation positioning accuracy and reliability under the complex environment and the satellite denial condition are effectively improved.

This invention provides KASP primer pairs, kits, methods, and applications for detecting SNP combinations related to soybean protein content. The SNP combinations related to soybean protein content include SNP1 at position 4903434 on chromosome Chr11, SNP2 at position 47558915 on chromosome Chr10, and SNP3 at position 47559046. This invention also provides three sets of KASP primer pairs for detecting SNP1, SNP2, and SNP3, used to detect soybean genetic DNA and genotype the three SNP loci to determine whether the species has high protein content. The detection method provided by this invention is fast, low-cost, and suitable for large-scale sample testing. This detection method can be applied to soybean molecular marker-assisted breeding selection, variety improvement, and germplasm resource evaluation.

The invention relates to the technical field of material informatics, and discloses a material data management method and system based on artificial intelligence, and the method comprises the following steps: S1, carrying out the first-level classification according to the purposes corresponding to collected material data; s2, on the basis of the first-level classification, performing second-level classification on the material data according to the main performance of the material; s3, on the basis of the second-stage classification, performing third-stage classification on the material data according to the preparation process of the material; and S4, on the basis of the three-stage classification, performing four-stage classification on the material data according to the auxiliary performance of the material. Through four-level hierarchical association, a complete link of application-main performance-preparation process-auxiliary performance is established, data of ten types of polymer fine processing products is effectively planned and managed, and efficient support is provided for research and development links such as formula screening, process matching and performance prediction, so that the speed of research and development and iterative optimization of new materials is accelerated.

The invention discloses a load prediction method and device considering cumulative temperature effect and heat island effect coupling, and the method comprises the training and use of a load prediction model, and the training process comprises the steps: determining a heat island effect temperature and a heat island reference temperature in the temperatures of a plurality of urban sub-regions in a target time period, taking the difference value between the two as a heat island effect; determining a sampling moment when the rising amplitude of the urban load capacity is about to enter a rising trend, taking a corresponding target urban temperature as a sensitive temperature, and calculating a temperature accumulation effect in a target time period based on the sensitive temperature; and taking the accumulated temperature effect, the heat island effect, the target city temperature and the city load capacity as training data for training a load prediction model. By adopting the above technical scheme, the relevance between the temperature rise and the load data is strong especially in summer, the change trend of the load data can be reflected, and a more accurate prediction result of the load data can be obtained.

The invention discloses an outpatient department accurate shunting and appointment guiding method based on AI pre-inquiry analysis. The method comprises the following steps that S1, a patient initiates pre-inquiry: the patient initiates a pre-inquiry request through a hospital APP, a self-service machine or an applet terminal; and S2: pushing the standardized inquiry questionnaire: the hospital APP, the self-service machine or the applet end pushes the standardized inquiry questionnaire through the shunting reservation system. By integrating multi-dimensional information such as texts, images, audios, patient ages and medical histories and by means of BERT semantic understanding, a medical knowledge graph and an XGBoost algorithm, the department matching accuracy is larger than or equal to 95%, the wrong number hanging rate is reduced to 3% or below, the limitation of single symptom matching is broken through, the cross-specialist differential diagnosis ability is improved, AI model driving replaces a rigid rule base, and the accuracy of diagnosis is improved. And iterative optimization is carried out through 1-20 thousand newly added data in each month, and rapid updating of the adaptive medical knowledge is realized.

The invention relates to a disturbance scene-oriented load response strategy modeling and evaluation method and system, belongs to the technical field of intelligent power systems, and solves the problems of insufficient load prediction precision, user response modeling precision and strategy robustness evaluation. The method comprises the following steps: predicting a multi-scale prediction load sequence and high-frequency disturbance characteristics based on an original electric vehicle load and related auxiliary data; obtaining a response score based on the predicted load sequence and the high-frequency disturbance characteristics; constructing a double-layer master-slave game model to calculate an electricity price excitation strategy and a multi-microgrid adjustment power path based on the response score, the prediction load sequence, the system economic parameters and the constraint parameters; and in a multi-class extreme electric vehicle load scene, calculating a robustness index to evaluate a unified robustness score, and taking the unified robustness score as a feedback signal to adjust a response score or an electricity price excitation strategy and a multi-microgrid adjustment power path. And closed-loop linkage of prediction-behavior-economic game and robustness evaluation is realized.

The present application relates to the technical field of integrated navigation, in particular to a positioning method and system based on optical angle measurement and astronomical-inertial integrated navigation. The method first acquires star and navigation satellite images by shooting a star map, and then calculates the attitude of the camera relative to the geocentric inertial coordinate system by identifying and processing the stars, and further determines the coordinates of the navigation satellite in the coordinate system. Through coordinate conversion, the angle information of the navigation satellite relative to the observer in the earth coordinate system is obtained. The optical angle measurement information is fused with the attitude, speed and position information output by the inertial navigation system, the Kalman filter state equation and observation equation are constructed, and finally the real-time high-precision solution and update of the observer's position are realized. The present application combines the accuracy of optical angle measurement, the limited distance reference of astronomical navigation and the autonomous continuity of inertial navigation, effectively improving the navigation and positioning accuracy and reliability under complex environment and satellite denial conditions.

The invention provides a safety verification method and system for a camera image and electronic equipment, and belongs to the technical field of image data processing, and the method comprises the following steps executed by an image sensor chip: responding to a frame synchronization signal, and synchronously triggering to collect original image data and environment parameters of a current frame; obtaining a pre-stored sensor chip identifier, and generating a dynamic watermark according to the environment parameter of the current frame and the sensor chip identifier and a preset rule; embedding the dynamic watermark into the original image data to obtain an image with a watermark; and outputting the image with the watermark and the environment parameters of the current frame to a rear-end image processing module. According to the invention, the reliability of verifying the authenticity and integrity of the camera image is improved.

The invention relates to a crank of a vacuum circuit breaker. The crank comprises a handle and a meshing head, the handle is a crank operating part; the crank further comprises a rotating drum, the handle is installed on the rotating drum carrier, the handle and the rotating drum are connected through meshing of a bevel gear, and the meshing head is installed at the front end of the rotating drum. The design is reasonable, the structure is simple, the rotating drum is designed, and the bevel gear is assisted to change the operation direction; during operation, 1) an operator directly faces the switch cabinet, the switch state can be observed in real time through the glass window, and an in-place indicating lamp on the cabinet door of the switch cabinet can also be seen, 2) the switch is pushed when the handle is swung towards the cabinet door, the switch is pulled out when the handle is swung towards the handle, the operation action has strong correlation with the actual switch motion, and the operation is easy.

This invention discloses an intelligent PDF document retrieval method and system combining OCR recognition, belonging to the field of optical character recognition technology. The method includes: inputting search terms into an information platform, performing term conversion and OCR enhancement to determine the enhanced term system; setting a look-skip retrieval mechanism to generate a dynamic retrieval chain based on concept change paths; and finally writing the results to a register via an interactive thread, performing dynamic OCR retrieval in the document database, and displaying the PDF retrieval form in a pop-up window. This invention solves the technical problem that traditional PDF document retrieval methods struggle to handle image-based text and other content in multi-source heterogeneous PDFs, resulting in one-sided and weakly correlated retrieval results that fail to meet the requirements of accurate and efficient retrieval. It achieves effective processing of image-based text and other content in multi-source heterogeneous PDFs, making the retrieval results more comprehensive and correlated, thus achieving the technical effect of accurate and efficient retrieval.

The application relates to the fields of molecular biological technology and livestock breeding technology, in particular to a SNP molecular marker related to a total number of piglets character, a detection primer pair, a kit and application of the SNP molecular marker in a method for breeding large white pigs with high number of piglets, the SNP molecular marker is located on a pig 9th chromosome, a physical position is located at chr9:65633096 of a genome version Ensembl Sscrofa11.1, a polymorphism site is C or A, and the C allele is positively correlated with the high number of piglets character; through genotype discrimination, selection breeding can be carried out: an individual with a genotype of C / C is preferentially selected or reserved as a breeding pig, because the total number of piglets has the highest potential, so that the genetic improvement speed of a population breeding performance is accelerated.

The embodiment of the invention discloses a scene reconstruction method and device, equipment and a storage medium, and the method comprises the steps: carrying out the scene reconstruction through a preset scene reconstruction mode if a current moment is a first three-dimensional scene relative to a target scene, and obtaining a current three-dimensional scene; otherwise, acquiring a plurality of first image frames and second image frames formed by acquiring the target scene at different visual angles, and acquiring a previous three-dimensional scene reconstructed based on the target scene; according to the first image frames and the second image frames, performing pose adjustment on Gaussian points in the previous three-dimensional scene to obtain a deformed three-dimensional scene; performing Gaussian point addition and deletion and Gaussian point feature optimization processing on the deformed three-dimensional scene according to each second image frame to obtain a processed optimized three-dimensional scene; and determining the optimized three-dimensional scene as a current three-dimensional scene at the current moment. According to the method, the current three-dimensional scene with higher relevance with the previous three-dimensional scene can be obtained in the time domain, so that the smoothness and continuity from the previous three-dimensional scene to the current three-dimensional scene in the time domain are ensured.

An oil, gas and water holdup and related flow sensor, an insulating shell is sealingly arranged on a wire-through pressure-sealing base, two parallel and coaxial capacitor columns are arranged in the insulating shell, a wire-through hole is arranged in the center of the capacitor column, a probe shell is sealingly arranged at the end of the insulating shell, the measuring ends of two optical fibers enter from the center of the wire-through pressure-sealing base, pass through the wire-through holes of the two capacitor columns and the probe shell in sequence and extend out of the probe shell by a certain length, one of the optical fibers extends out by a length greater than that of the other optical fiber, the two optical fibers are fixedly packaged in the probe shell, wires are connected to the two capacitor columns respectively, and the wires pass out of the center of the wire-through pressure-sealing base. The present application realizes the measurement of oil, gas and water three-phase holdup and the flow rate of each phase on the same sensor, and the electrical flow and the optical fiber flow can also be complementary and verified, improving the accuracy and reliability of the measurement, and the correlation of holdup and flow rate is stronger. The present application has the advantages of small size, simple structure, green environmental protection and high precision.

The invention relates to the technical field of digital economic risk management, and discloses a digital economic risk intelligent management evaluation system and method. According to the method, source tracing marking is carried out on an original behavior flow obtained from a heterogeneous data source, and a traceable initial behavior sequence is formed. And processing the sequence in parallel by using a multi-channel sensing mechanism, extracting and crossly fusing the features of different abstract levels, and generating a composite feature spectrum. Performing map embedding mapping based on the risk knowledge map, and matching risk nodes and paths to construct a preliminary risk situation map; injecting a plurality of environmental disturbance factors into the dynamic calculation sand table, simulating the dynamic evolution trajectory of the risk situation, and recording the end point state of each trajectory to form a risk evolution set. And through evaluation and convergence of an end point state, a stable risk state is screened out, and a deterministic conclusion is generated. According to the method, through multi-level fusion and dynamic deduction of the features, the comprehensiveness of risk feature characterization and the dynamic prediction capability of risk assessment are improved.

The invention discloses a VLA-based low-speed park automatic driving method, and relates to the technical field of automatic driving, and the method comprises the steps: collecting a plurality of park environment data, generating a panoramic park environment perception tensor, executing semantic element recognition and dynamic subject motion trend pre-judgment, and generating a park environment semantic analysis topology with a dynamic motion trend; performing advance obstacle avoidance path planning and stationary path optimization on the park environment semantic analysis topology with the dynamic motion trend and the preset driving path, and generating a park automatic driving control instruction set with dynamic safety redundancy; and executing the instruction set and collecting vehicle driving state feedback data to generate a multi-mode-path planning collaborative optimization parameter tensor, and continuously adjusting automatic driving execution logic. Therefore, automatic driving can continuously adapt to scene changes in long-term operation, and the operation stability and robustness are improved.

The method and system for recommending college entrance examination volunteer based on multi-dimension analysis have the following process: 1) data on an education consultation website is collected in JSON format through a crawler technology, and is stored in a MySQL database through data conversion; 2) redundant and irrelevant data is removed, only characteristic indexes related to college enrollment are reserved, data types are unified, missing information is discarded, and the validity of the data is ensured; 3) the characteristic data is input into a GM(1, 1) prediction model of a grey prediction algorithm to predict the enrollment ranking of each college, and a normal distribution algorithm is used to predict the possibility that a candidate can enter a college; and 4) the enrollment probability is weighted and calculated, and the analytic hierarchy process is used to recommend a college entrance examination volunteer for a candidate according to the weight value. Through the above process, the college entrance examination volunteer recommendation system is realized, the scientificity and rationality of examination volunteer filling are improved, and a significant reference is provided for candidates to fill in the college entrance examination volunteer.

The invention discloses a fan blade load prediction method and device, and the method does not need to install real sensors at all required to-be-detected positions of a fan blade, and determines the correlation between a to-be-predicted position and an installed position through obtaining the to-be-predicted position and the installed position. And if the correlation is greater than or equal to a correlation threshold, obtaining a regression model, and performing fitting through the regression model according to the blade load data of the installed position to obtain the blade load data of the to-be-predicted position. And if the correlation is smaller than a correlation threshold value, obtaining a prediction model, and performing prediction through the prediction model according to the environment data of the installed position to obtain blade load data of the position to be predicted. And corresponding to different correlation conditions, the blade load data of the to-be-predicted position under the condition of relatively strong correlation is obtained through the regression model, and the blade load data of the to-be-predicted position under the condition of relatively weak correlation is obtained through the prediction model, so that the accuracy of fan blade load prediction is improved.

The invention discloses an anti-dry-burning control method and device and a cooking utensil, the cooking utensil comprises a pot body base body, an electromagnetic heating device and a bottom temperature detection device, the pot body comprises a non-magnetic pot body base body and a magnetic layer arranged on the inner side of the pot body base body, and the magnetic layer is arranged on the inner side of the pot body base body. The bottom temperature detection device is used for detecting the pot bottom temperature of a preset bottom position on the outer side of the pot body base body, and the dry burning prevention control method comprises the steps that after a cooking starting instruction is received, the pot bottom temperature is obtained to be the first pot bottom temperature; the electromagnetic heating device is controlled to heat for a first preset duration in a first preset power range, and the pot bottom temperature at the end of the first preset duration is obtained as a second pot bottom temperature; if the difference value between the second pot bottom temperature and the first pot bottom temperature is larger than or equal to a temperature change threshold value, it is determined that dry burning occurs.

The present application relates to a kind of text to structured query implementation method, device and storage medium, it is related to structured query generation technical field.The present application trains language model using text to structured query reinforcement dataset;When applying, the data table knowledge graph of the total data table of application database is constructed, according to the proposed target natural language question and data table knowledge graph, the most relevant several data tables are identified;The overall logical chain natural language explanation of the structured query of target natural language question is directly predicted according to target natural language question by trained language model in the scope of relevant knowledge table and its knowledge graph;And according to target natural language question and the most relevant table, multiple candidate structured queries are predicted;The natural language explanation of the overall logical chain of candidate structured query is obtained using operation explanation template;According to the similarity of two overall logical chain natural language explanations, the optimal candidate structured query is selected.

A few-shot graph classification method and system based on graphical decoupling meta-learning. The method comprises: explicitly modeling the many-to-many relationship between molecules and attributes by constructing a multi-relation molecular graph (MMG), and separating task-specific and task-invariant features by using a decoupling graph learning strategy, and combining a meta-learning framework to realize molecular attribute prediction in a few-shot scenario. The scheme improves the sample prediction accuracy and enhances the interpretability of the features.

The application is suitable for the field of image processing, and provides a no-reference color image quality evaluation method based on color and structure distortion, comprising the following steps: performing a blocking operation on a color image to form a color distortion image block data set, and forming a training set and a test set; a group of two-dimensional Scharr detection operators are constructed, and convolution processing is performed on the input image block by using the two-dimensional Scharr detection operators to obtain gradient feature information of the distortion image block; the obtained image block data set is converted into an HSV color space; a no-reference image quality evaluation convolutional neural network model based on color and structure distortion is constructed according to the existing image block data set; and the divided training set is input into the constructed no-reference image quality evaluation convolutional neural network model to obtain a trained no-reference image quality evaluation model. The application has reasonable design, the simulated quality score and the real quality score have strong correlation and small error, and is worth promoting.

This invention provides a method and system for explaining misclassified samples in an IoT device identification model based on random forests, belonging to the field of machine learning interpretability technology. The core of this method lies in locating the key features leading to misclassification of individual samples through a two-level interpretation framework combining fine-grained and coarse-grained approaches. First, for each misclassified sample, the fine-grained importance contribution value of that feature within a single tree is obtained by calculating the change in the proportion of samples of the true class caused by feature splitting along the decision path of each decision tree. Then, the results of all decision trees in the random forest are aggregated, and the average importance contribution value of each feature at the model level is calculated as the final importance score. Based on this, the key features leading to misclassification are identified and output. This invention does not require reconstruction of the original model and can achieve accurate explanation of the causes of sample-level misclassification, providing support for the optimization of IoT device identification models, network asset management, and security protection.

The utility model discloses a teaching aid for displaying a binary system and decimal system conversion process in the technical field of teaching aids, which comprises a bottom plate, a handwriting board, a standard number board, a counting turning board and a counting strip, decimal system numerical values are displayed through the handwriting board, and the total number value splitting and combining states of the decimal systems are displayed through the counting strip and the standard number board. The counting turning plate and the marks are matched to form binary digits, so that the teaching aid for binary and decimal conversion can be displayed more conveniently, and students can understand the change process and the change principle of the binary and the decimal more easily; meanwhile, students can more easily understand how the decimal numerical values are split and then combined into the binary system, the whole process is completely displayed, the operation is simple, the whole display steps are completely displayed in the same teaching aid, the whole conversion process is synchronously and completely embodied instead of only displaying the change of one number, and the teaching efficiency is improved. And the teaching thought can be displayed more completely.

The application discloses a pancreas disease multi-time window risk prediction system based on routine physical examination queue data and relates to the technical field of medical big data and disease risk prediction. The system comprises data acquisition, preprocessing, feature fusion, risk calculation and model optimization modules; the acquisition module acquires and integrates data to output a structured original data set; the preprocessing module processes the original data set into a personal longitudinal time sequence feature vector set; the feature fusion module outputs a unified feature vector; the risk calculation module obtains a multi-time window disease probability; and the model optimization module constructs a label, calculates a loss and optimizes and updates parameters of each module. The application integrates routine physical examination and pancreas disease outcome data to construct a data set, mines data value through standardization preprocessing and the like, inputs a unified feature vector into a multi-layer perception machine, constructs an incremental risk vector, realizes multi-time window disease probability stratified prediction, breaks through single limitation, introduces L2 regularity to improve performance, and helps early screening and intervention of pancreas disease based on routine physical examination data.

This invention discloses a fault prediction method for tension roller groups based on anomaly detection and classification algorithms. The method involves installing vibration sensors on both sides of the motor and rollers of the tension roller group to collect vibration data at different measuring points and frequencies within the shaft system. Time-frequency domain data, frequency band proportions, and trend characteristic data are calculated. Through clustering, anomaly, and classification algorithms, combined with fault inspection and maintenance record data, an optimal fault identification model is formed. The latest real-time vibration data of the tension roller group is obtained, and the optimal fault identification model is used to predict the real-time vibration data, deriving the fault risk probability value. This method employs dimensionality reduction and anomaly detection algorithms to extract features, ensuring a strong correlation between features and faults. By pre-constructing a fault identification model, the accuracy of predicting potential faults and the efficiency of supporting maintenance decisions are improved.

The present application relates to a kind of test methods of permeable crystallization masterbatch, in particular to a kind of test method of fast testing permeable crystallization masterbatch catalytic crystallization performance, activity, by adding liquid sodium silicate, calcium hydroxide to carry out the gelation time determination, gel amount determination and surface tension determination of permeable crystallization masterbatch.The permeable crystallization masterbatch test method, fast, 1d time can be detected result, compared with the method according to traditional GB18445-2012 "cement-based permeable crystalline waterproof material", save 87d time, and test amount is far less than traditional method;Result is accurate and reliable, and it has strong correlation with the result tested according to GB18445-2012 "cement-based permeable crystalline waterproof material" method.