85results about How to "Reduce data processing" patented technology

The invention discloses an industrial park net load prediction method and system based on a multilayer perceptron, and the method comprises the following steps: dividing historical industrial park operation data according to an audio frequency collection region, and obtaining region historical operation data corresponding to the audio frequency collection region; performing clustering analysis on the historical operation data of each region based on the audio frequency fluctuation, and obtaining audio frequency-aging correlation according to a clustering result; training by using historical industrial park operation data, historical distributed energy operation data and audio frequency-aging correlation to obtain an industrial park net load prediction model; and obtaining industrial park net load prediction data according to the current industrial park operation data, the current distributed energy operation data, the industrial park load net prediction model and the audio frequency-aging correlation. The method has the beneficial effects that an aging model does not need to be constructed for each industrial device, the overall model structure is simplified, and meanwhile, the prediction efficiency and prediction accuracy of the load of the industrial park are improved.

The invention discloses a chamfer defect detection method, device and equipment and a storage medium, and relates to the technical field of defect detection.The method comprises the steps that an obtained to-be-detected device image is preprocessed, and chamfer contour points and chamfer contour point pixel coordinates are determined in the preprocessed image; correcting the pixel coordinates of the chamfer contour points, and fitting a chamfer edge straight line by using the corrected pixel coordinates of the chamfer contour points; according to the chamfer edge straight line, screening the corrected chamfer contour point pixel coordinates, and determining a target chamfer end point; and calculating the actual chamfer length based on the target chamfer endpoint, and comparing the actual chamfer length with the preset chamfer length to judge whether the chamfer has defects or not. According to the method, the detection requirements of chamfers of different shapes and sizes can be met by preprocessing and correcting the images, fatigue and subjective judgment errors possibly existing in traditional manual detection are avoided through automatic image processing and data analysis processes, and the detection efficiency is improved.

The embodiment of the invention discloses a power equipment abnormity identification method and device, electronic equipment and a medium. A specific embodiment of the method comprises the following steps: for each piece of power equipment acquisition information in a power equipment acquisition information set, executing the following exception identification steps: performing feature extraction on each power equipment image in a power equipment image group included in the power equipment acquisition information to generate power equipment image features; inputting the electrical equipment image feature group into a pre-trained electrical equipment appearance anomaly detection model to obtain an electrical equipment appearance anomaly detection result; performing anomaly detection on a power equipment operation data set included in the power equipment acquisition information to generate an operation data anomaly detection result; and in response to determining that the appearance anomaly detection result of the power equipment meets the appearance anomaly alarm condition, sending equipment anomaly alarm information to an associated power equipment maintenance terminal. According to the embodiment, the efficiency and accuracy of detecting the operation data of the power equipment are improved.

The invention relates to a multi-scene safety production supervision method, system and device based on intelligent positioning. The method comprises the steps that operation and maintenance monitoring is carried out on an application corresponding to each production scene through an enterprise side safety production risk monitoring and early warning subsystem, and production related information is acquired. Different source data in the production related information are integrally processed, a standard data set is generated, a label is added to each piece of source data in the standard data set, and a labeled data set is obtained. And constructing a safety production monitoring model according to the danger attributes, and inputting the labeled data set as a sample data set into the safety production monitoring model for optimization training to obtain an optimized safety production monitoring model. And deploying the optimized safety production monitoring model to the edge computing device in a distributed manner, so that the operation and maintenance monitoring subsystem carries out supervision processing according to the position information transmitted by the personnel positioning system and the production process information. By adopting the method, the real-time performance and accuracy of production safety monitoring in the dangerous chemical environment can be improved.

The invention discloses a rail transit operation safety event monitoring system and method based on the Internet of Things, and relates to the technical field of rail transit operation safety event monitoring, and the system comprises a plurality of sensor units, a plurality of edge preliminary analysis modules, a plurality of ad hoc network modules, and a rail transit operation central safety analysis module. According to the invention, the side cloud is combined with a main framework to realize acquisition of sensors and visual data, a plurality of sensor units can realize real-time monitoring of different monitoring items, the visual monitor has a generalization monitoring capability, and visual identification of different abnormal features is realized based on a visual feature comparison algorithm; the edge preliminary analysis module is arranged, through preliminary screening of the edge preliminary analysis module, the data processing amount of the rail transit operation central safety analysis module can be greatly reduced, the computing power requirement and the hardware arrangement cost of a server are reduced, and finally the rail transit operation central safety analysis module only carries out safety evaluation on data with large risks. And the safety assessment efficiency is high.

The invention discloses a data classification and grading method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring application program interface (API) data to be processed; sampling and filtering the to-be-processed API data according to the user identification information and the interface identification information by taking a preset time period as a period to obtain sampled and filtered API data; and classifying and grading the sampled and filtered API data, and storing the classified and graded API data in a first data index database. In the whole data classification and grading process, before the API data is classified and graded, periodic sampling and filtering are performed on the to-be-processed API data according to the user identification information and the interface identification information, so that repeated interface calling data when the same user calls the same interface within the preset time period is effectively removed, and the data processing efficiency is improved. According to the method, the data processing amount when the system classifies and grades the API data is reduced, the classification and grading efficiency of the API data is improved, and then the security risk detection efficiency of the API data is improved.

The invention discloses a data processing method and device, a nonvolatile storage medium and electronic equipment. The method comprises the steps that input information is obtained, the input information comprises table data and user requirements, and the user requirements are used for indicating requirements met by texts generated according to the table data; the user demand is rewritten according to the table data, a target user demand is obtained, and the target user demand comprises a newly-added field generated according to the table data; performing multi-stage screening in the table fragments according to a target user demand to obtain a target table fragment; a target text is generated according to the target table fragment and the target user requirement, and the target text comprises data corresponding to the newly-added field. According to the method and the device, the technical problem that a result obtained by performing content recreation based on the table data is inaccurate due to small association degree between the input user demand and the table data when the table data is analyzed and the content is recreated in the related technology is solved.

The invention provides a low-code system for data analysis and data cleaning based on Internet of Vehicles data. The low-code system comprises a multi-protocol adapter, a user-defined analysis rule writing interface, a dragging type rule configuration interface, a data processing module, a forwarding mechanism unit, a monitoring and log tracking unit and a message labeling and fingerprint generation unit. Wherein the multi-protocol adapter is used for supporting log data acquisition of various network protocols; the user-defined analysis rule writing interface allows a user to write specific analysis logic according to a data format and a service requirement; meanwhile, for compatibility of various data codes and formats, rule templates and examples are provided to guide a user to compile analysis rules, and the user is helped to quickly position and correct problems in the analysis rules by integrating corresponding error detection and debugging tools; and a user carries out graphical operation combination input, output and analysis on rule nodes through the drag-and-drop rule configuration interface.

The invention provides a virtual object control method and device, electronic equipment and a readable storage medium, and the method comprises the steps: providing a game scene corresponding to a game match in response to a match start instruction, and the game scene comprises a first game role and a second game role which respectively play a first game identity; in response to the situation that the first game role in the game scene is corrupted by the second game role, the first game role is controlled to be converted into the second game identity from the first game identity, so that the first game role continues the current game with the second game identity. Therefore, the data processing amount of the server can be reduced, and the performance overhead of the game server can be reduced. Meanwhile, for the player controlling the first game role which is corrupted, the player cannot quit the current game immediately after being corrupted, the chance that the player continuously participates in the current game to corrupt the second game role to pick up falling materials can be obtained again, and the game experience of the player is further improved.

The application provides a code modification method and device based on semantic update fragment generation. The code modification method comprises the following steps: generating a semantic update fragment and a first reconstruction code according to original code and modification description information; performing code modification verification on the semantic update fragment according to the code difference between the original code and the first reconstruction code; when the code modification verification is passed, generating a second reconstruction code by modifying the original code according to the semantic update fragment, and determining whether the code modification of the second code modification model is correct according to the code comparison result between the second reconstruction code and the first reconstruction code; taking the original code, the semantic update fragment and the first reconstruction code corresponding to the second code modification model with code modification errors as model training data to perform model training to obtain a target code modification model; and modifying the to-be-modified code by using the target code modification model to obtain a complete code. The application can reduce inference delay and improve code modification efficiency.

The invention relates to an edge calculation method and system of an edge server. The method comprises the following steps: sending to-be-processed data generated by terminal equipment to a nearest edge server for data complexity calculation; when the complexity is not greater than a preset complexity threshold, sending the to-be-processed data to a matched edge server for processing, otherwise, performing data decomposition to obtain data blocks with different complexities; according to the data type and the corresponding complexity, different data blocks are transmitted to a matched edge server for processing and sent to the nearest edge server for fusion processing, and the fusion processing is returned to the terminal equipment; data prediction is carried out through the data prediction model, a prediction result is transmitted to the data decomposition module for pre-decomposition, and after decomposition is carried out according to a pre-decomposition scheme, the prediction result is sent to a matched edge server for data processing; and the matched edge server transmits the data processing result to the nearest edge server for data fusion and then returns the data processing result to the terminal equipment, so that processing of large-scale data and complex calculation tasks is realized.

The present invention proposes a radar condensation point quality assessment method and system. The method includes: using the attribute value of the point track to calculate the standard deviation of the attribute, and then calculating the discrete degree assessment score of the attribute according to the standard deviation of the attribute; then performing weighted summation on different attributes according to the attribute importance to obtain the attribute discrete degree score; calculating the azimuth distribution score according to the number of scattered point azimuth gaps and the total number of scattered points whose front position difference of the front and rear points is less than or equal to the radar rotation azimuth; taking the minimum number of scattered points and the maximum number of scattered points according to engineering experience, and then applying the method of the first step to calculate the point track quantity score; adding the attribute discrete degree score, azimuth distribution score and point track quantity score to obtain the point track quality total score. In the scheme proposed by the present invention, the condensation point quality score is the basis of track quality assessment, which is conducive to improving the accuracy of track quality assessment, reducing the false alarm rate, and increasing the life cycle of the target track.

The invention provides a dual-frequency phase-comparison underwater acoustic ranging method, which comprises the following steps that: step 1, a sonar transmitter transmits a dual-frequency continuous wave signal to a target, and a sonar receiver receives a target echo; 2, for one frame of data of the target echo, two line spectrum peak values with the maximum amplitude and the second maximum amplitude in a power spectrum are searched, and a frequency difference is obtained; according to the frequency difference range and the amplitude threshold, carrying out availability confirmation on the two line spectrum peak values; and 3, comparing phases corresponding to peak points of the peak values of the two line spectrums, and determining a target distance of the current frame through a phase difference. According to the method, the continuous wave system sonar is matched with the multi-frequency phase comparison technology for target distance measurement, the precision of phase measurement is higher than that of time delay measurement, and the sensitivity of the phase difference of double-frequency signals to random noise is low, so that the influence of a multi-path effect and noise can be effectively reduced, and the accuracy and reliability of distance measurement are remarkably improved.

The application provides a workpiece tightening defect classification method, system, controller and storage medium, wherein the classification method comprises: acquiring a first tightening defect curve and preprocessing the first tightening defect curve; cutting the preprocessed first tightening defect curve based on a preset rule to obtain a target tightening defect curve; extracting time domain features in the target tightening defect curve; and inputting the time domain features into a plurality of pre-trained defect recognition models respectively to obtain recognition results, wherein the recognition results comprise a target defect type corresponding to the first tightening defect curve or a defect type that the first tightening defect curve belongs to is not determined. The application solves the problem in the prior art that workpiece tightening defect classification cannot identify new defect types, resulting in defect classification errors.

The application relates to a plane circle center point-based SolidWorks standard part automatic installation method for a parameter-free model, and belongs to the field of computer-aided design and three-dimensional mechanical design automation. The method first selects any part plane and any assembly hole on the part plane through a point selection mode; a sketch is created based on the geometric boundary of the part plane, and the coordinates of the sketch are determined according to the geometric boundary position information of the part plane; all assembly holes with the same hole feature on the part plane are automatically identified according to the extracted selected assembly hole feature, and corresponding sketch coordinates are established; sketch points are established for all sketch coordinates under the part plane; and the sketch-driven part array function is called, after manually assembling a standard part at any sketch point, the standard part assembly is automatically executed at all sketch points. The application can automatically batch install standard parts by using the sketch-driven part array function of an assembly body.

A data processing method and device for a centralized station terminal access line loss collection module, wherein the data processing module sends a command message to the line loss collection module according to a polling cycle; receives a serial port message sent by the line loss collection module according to the command message; parses and processes the serial port message to obtain real-time electricity data contained in the serial port message; writes the real-time electricity data into a shared memory and sends a message to notify other modules of the station terminal, the other modules including a main module and / or a communication module. Through the shared memory and message mechanism, the main module and the communication module can fetch data from the shared memory when needed, thereby reducing the data processing amount of the main module and solving the problem of data sharing and cooperation between modules when multiple software modules of the centralized DTU are running simultaneously.

The present invention provides a single-line communication output multiplexing driving circuit, display system and method, the driving circuit includes: a controller, at least one driver group; each driver group includes: a plurality of drivers that are sequentially connected from the first-level driver to the last-level driver; the controller includes: an output port and a readback port; the output port is connected to the first driver, and the readback port is connected to the last driver; the output port is used to send the communication signal and interrupt signal of the controller to the first driver, so that the communication signal and interrupt signal pass through each driver of the driver group in sequence; the last-level driver is used to generate readback data and interrupt information in response to the communication signal and interrupt signal, and transmit it back to the readback port. According to the technical solution of the present invention, the last-level driver can not only be a slave, but also a host, which reduces the data processing amount of the controller, thereby reducing the selection restrictions on the controller and reducing the cost.

The embodiment of the invention provides a symbol synchronization method, a symbol synchronization device, computer equipment and a computer storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring a to-be-processed signal, and performing segmentation processing on the to-be-processed signal to obtain a plurality of to-be-processed sub-signals; for each target to-be-processed sub-signal in the plurality of to-be-processed sub-signals, performing conjugate product on the data difference of the adjacent sampling points corresponding to the current sampling point and the target data corresponding to the current sampling point to obtain a clock error corresponding to the target to-be-processed sub-signal; error correction is carried out on the clock error, and the sampling clock deviation of the target to-be-processed sub-signal is determined based on the corrected clock error value; and performing interpolation filtering operation on the target to-be-processed sub-signal based on the sampling clock deviation to obtain a target signal after symbol synchronization of each to-be-processed sub-signal. According to the method, the symbol synchronization performance can be improved while the algorithm complexity is reduced.

The present application relates to a rack beam detection method for a forklift, comprising: acquiring depth data collected by a depth camera, and converting the depth data into point clouds in a preset coordinate system; acquiring a mast lifting height of the forklift, and extracting target point clouds from the point clouds based on the mast lifting height; orthogonally projecting the target point clouds to a vertical plane along a forking direction to generate a two-dimensional occupancy grid image; counting the number of occupancy grids of each row in the height direction of the occupancy grid image to generate a one-dimensional height-density histogram; performing difference calculation on the height-density histogram, and traversing from bottom to top along the height direction, and determining the first position meeting a preset negative peak value condition as an upper edge height value of a to-be-detected rack beam; and outputting a detection value based on the upper edge height value of the to-be-detected rack beam. The present application also relates to a forklift, a computer storage medium and a computer program product.

The application relates to a high-speed small target extraction method using an infrared event stream, which obtains infrared event stream information by processing adjacent frames of images acquired by a high-frame-frequency infrared camera, and detects high-speed moving target information in the infrared event stream information by using the characteristic that the infrared event stream information is sensitive to moving targets. The original infrared images are subjected to frame extraction processing, the target position in the original image frame is located by using the detected moving target information, local target characteristics are extracted for processing, and the target is confirmed and recognized. The method avoids the problem that the calculation complexity is high when target detection is performed on the original high-frame-frequency infrared images, uses the obtained event frame image which only contains the moving target information of the coefficient, removes a large amount of redundant useless background and static information, reduces the calculation amount, improves the detection sensitivity of high-speed infrared moving small targets, simultaneously reduces the energy consumption of the system, and can be widely applied to infrared detection systems with limited processing resources.

The invention discloses a method for filtering webpage access based on a kernel driver, which belongs to the technical field of internet communication and comprises the following steps: step 1, a user inputs an access website for a user browser to generate a DNS (Domain Name Server) query request message; 2, judging whether a DNS query request message exists in a local DNS cache or not, if yes, obtaining an IP address for access, and if not, executing a step 3; and step 3, sending a query request to a DNS server, constructing a complete DNS query request network packet according to a network protocol standard, capturing all DNS query request network packets sent to the 53 port by a kernel driving program, and then analyzing target domain names of the DNS query request network packets through a DNS protocol. Centralized and automatic management and control are achieved, the system is particularly suitable for scenes such as machine rooms and classrooms needing unified network behavior management, and the operation and maintenance cost is greatly reduced.

The invention relates to the field of seismic wave data processing, provides an intelligent analysis and identification method for three-dimensional seismic wave point cloud data in order to realize automatic forecasting, and performs machine intelligent geological object identification and automatic forecasting conclusion generation by directly performing standardization processing on point cloud data generated by a seismic wave method and through a corresponding relation in engineering experience. According to the method, the process from original data to images and then to manual interpretation is avoided, many problems in manual image analysis are avoided, meanwhile, a large amount of test original data is subjected to simplification and structured processing, the storage space and the data processing amount of subsequent work are saved, and the efficiency is improved. And a foundation is laid for machine intelligent fusion analysis among data under different forecasting methods.

The utility model discloses an industrial waste heat inspection system based on a three-dimensional positioning technology. The industrial waste heat inspection system comprises an inspection robot and a PC (Personal Computer), wherein the inspection robot is used for collecting operation information of each device in a waste heat recovery device and monitoring information monitored by a sensor arranged on each device; the PC is provided with a DCS (Distributed Control System); a positioning module and an NFC module are arranged on each of the inspection robot and each device; each device is also provided with a data acquisition module, and the output ends of the data acquisition module and the positioning module on each device are respectively connected with the input end of the NFC module on each device; the inspection robot is further provided with a comparison module connected with the output end of the NFC module on the inspection robot, an inspection controller connected with the output end of the comparison module and the output end of the positioning module arranged on the inspection robot, and a wireless communication module connected with the inspection controller. The PC is provided with a three-dimensional scene module connected with the DCS system. According to the utility model, the workload of waste heat inspection personnel can be reduced, and the inspection efficiency can be improved.

The invention relates to the field of power marketing business search, in particular to a power marketing common data set preprocessing method based on a weighted principal component analysis method. The data set preprocessing method comprises the following steps: standardizing original data; solving a correlation coefficient matrix V; assigning a weight to each sample; solving a feature root and a feature vector of the covariance matrix; calculating the contribution rate and the cumulative contribution rate of the principal component; and projecting the sample points to the selected feature vectors to obtain a new data set. According to the method, a multivariable problem in a high-dimensional space is converted into a low-latitude and few-variable problem, and corresponding weights are set due to diversified characteristics of power data, different characteristics in the same data table and different effects of samples in the recognition process, so that the recognition rate of sample data at different degrees is enhanced, and the recognition efficiency is improved. Therefore, effective feature extraction is performed on the sample, and the influence of outliers is eliminated, so that the recognition rate of sample data is improved.

This invention discloses a method for detecting paper tube fireworks, including shaping the paper tube fireworks, first photographic detection, and deformation of the outer perimeter. The deformation component squeezes or stretches the outer perimeter, causing the fuses inside the fireworks tube to move. A second photographic detection is then performed, followed by comprehensive data analysis. First, the paper tube fireworks, just assembled mechanically, are shaped to ensure a regular shape and accurate arrangement of all paper tubes during photographing. This allows for accurate capture of the fuses inside each individual tube, avoiding interference between tubes and significantly reducing the amount of data processing required. Second, after the first photograph, the outer perimeter is deformed, and a second photograph is taken. This deformation causes a slight shift in the two fuses inside each tube, and a second photograph is taken, causing misalignment of overlapping fuses and reducing the false positive rate.

This application provides a method, device, electronic device, and readable storage medium for distributing rewards in games. It adjusts the long and short game scores of a target player based on their game interaction behavior. When the short score settlement period meets the score settlement conditions, short-term rewards are distributed to the target player based on the target score interval to which their short game score belongs in the historical score interval snapshot. When the long score settlement period meets the score settlement conditions, long-term rewards corresponding to the target ranking are distributed to the target player based on their target ranking. By using the same game score adjustment strategy for both the long and short score settlement periods to calculate game scores, and distributing rewards based on historical score interval snapshots during the short score settlement period, the amount of data processed by the server at any given time can be effectively reduced, thus improving reward distribution efficiency.

The invention provides a retransmission data processing method and device, and the method comprises the steps: receiving initially transmitted coding block data, recording the position information of a coding block with a wrong initial interpretation code, and storing a decoding result of the coding block with a correct initial interpretation code; and when retransmission corresponding to the initial transmission occurs, calculating time domain and frequency domain resources and pilot frequency resources corresponding to the coding block of the initial interpretation code error according to the position information of the coding block of the initial interpretation code error and configuration information of retransmission, so that only time domain and frequency domain resource data and pilot frequency data corresponding to the initial interpretation code error are transmitted when data are transmitted forwards. The retransmission efficiency can be improved, the transmission reliability is guaranteed, and the processing performance is optimized.

The present application relates to a user data processing method, device, equipment, storage medium and program product. The method includes: receiving a business processing request, and obtaining corresponding user data according to the business processing request; performing differential processing on the user data; uploading the user data after differential processing to a main server, and the main server is used to generate business processing results according to the user data after differential processing. The use of this method does not require the main server to pre-process a large amount of data, etc., thereby reducing the data processing volume of the main server, and because the data uploaded is differentially processed data, the main server only needs to store a unified set of general rules, which also reduces the storage of rules, reduces the pressure on the main server, and improves the rule reuse rate.

The invention provides a laser-assisted heating metal beryllium plastic cutting control method based on a chip form. The laser-assisted heating metal beryllium plastic cutting control method comprises the following steps that the real-time dust concentration in the laser-assisted heating metal beryllium plastic cutting process is obtained in real time; identifying a real-time cutting form by using the real-time dust concentration based on a corresponding relation between the dust concentration and the cutting form of a calibration database; and according to the real-time cutting form, laser energy input control is adjusted through a fuzzy PID control algorithm. The plasticity of cuttings is remarkably improved by maintaining the plastic cutting state, it is guaranteed that generation of powder cuttings is reduced, and the safety of the machining environment and machining personnel is guaranteed; the dust concentration sensor has the remarkable advantages of low cost, simple arrangement and small data processing amount, and is beneficial to popularization and application of the technology; and finally, laser energy input parameters are dynamically optimized through a fuzzy PID control algorithm, so that the system can automatically adapt to material characteristic fluctuation, and the machining stability is improved.

The embodiment of the invention discloses a question and answer model training method and device. The question and answer model training method comprises the steps that an initial system instruction is acquired; the initial system instruction is a natural language description used for indicating a model to answer a question of a user in a specified role; performing compression processing on the initial system instruction according to a preset compression mode to obtain a compressed system instruction; the character length of the compressed system instruction is smaller than the character length of the initial system instruction; obtaining training data according to the compressed system instruction and sample question and answer information; the sample question and answer information comprises sample question information and answer information corresponding to the sample question information; and training a preset language model according to the training data to obtain a question and answer model.