20 results about "Statistical classification" patented technology

This invention provides a comprehensive digital and intelligent operation and maintenance management method and system for power distribution networks, relating to the field of computer data processing technology. The method includes: S1, obtaining pole and tower information collected by drones during line inspections, performing defect mining and analysis on the pole and tower information, and integrating the analyzed defect information with the pole and tower information to form a pole and tower information collection table; S2, selecting and extracting corresponding data from the pole and tower information collection table, and visualizing the data on a GIS map containing the lines obtained from the pole and tower information collection table using preset markers to generate an inspection status map; S3, statistically classifying the analyzed defect information and matching it through a big data platform to generate a defect repair and management summary table; S4, analyzing the faults using an AI model and a big data platform, combining the inspection status map and the defect repair and management summary table, obtaining priority-ranked repair tasks, and proposing corresponding solutions.

The invention provides an inspection data processing method, device and equipment, belongs to the technical field of information processing, and solves the problems that the inspection data processing efficiency is low and the execution process is difficult to control. The method comprises the following steps: acquiring inspection target data, wherein the inspection target data comprises inspection time data, inspection execution equipment data and inspection object data; according to the inspection target data, performing traversal filling processing on the inspection form database to obtain inspection work order data; sending the inspection work order data to the client; receiving a plurality of inspection feedback data sent by the client, wherein the inspection feedback data is obtained by the client by generating an operation instruction according to the inspection work order data and executing the operation instruction; and performing statistical classification processing on the plurality of inspection result data to obtain inspection report data. According to the scheme, automatic triggering and accurate execution of the inspection task are realized.

A dynamic statistics and result analysis system for watershed river and lake shoreline development and utilization comprises a remote sensing data acquisition module, a data preprocessing and classification module, a database construction module, a change trend analysis module, a river and lake directory and association retrieval module and an interaction management module. The data preprocessing and classification module is used for data preprocessing and statistical classification, the database construction unit is used for constructing a system database, the variation trend analysis module is used for variation trend analysis and statistical report generation, and the river and lake directory and association retrieval module is used for directory maintenance and result association. According to the dynamic statistics and result analysis system for watershed river and lake shoreline development and utilization, a remote sensing data statistical classification algorithm based on a neural network is proposed to classify remote sensing data; and a river-lake shoreline development and utilization change trend analysis algorithm based on deep learning is proposed to analyze the change trend.

The application provides a data collection method, device, equipment, medium and computer product, and relates to the technical field of flow collection. The method comprises the following steps: grouping the to-be-collected data according to statistical information obtained by statistical classification according to preset elements, obtaining at least one feature flow data and a corresponding analysis window; wherein each group of to-be-collected data corresponds to one feature flow data; meanwhile, each analysis window is moved from a first moving time node, and the first step length of the at least one feature flow data is obtained; and the data of each feature flow data in the time period corresponding to the analysis window is collected to obtain collected data. By moving the analysis window according to the step length of the feature flow data, the data of different feature flow data in the time period corresponding to the corresponding analysis window is collected, so that the system burden caused by a large amount of redundant data due to full collection can be avoided, and the collection and analysis resources can be dynamically allocated according to different flows.

This invention relates to the field of oil and gas drilling engineering technology, specifically to a rapid directional drilling method for deep coal and gas horizontal wells based on real-time logging data, comprising: real-time acquisition of multi-source logging data; establishment of the functional relationship between idle friction torque and well depth; real-time calculation of effective rock-breaking torque of the drill bit; and MSE (Mean Separation of Forms). b Model building and real-time calculation; establishment and dynamic correction of lithology identification threshold: using logging and well logging data from adjacent wells, a statistical classification model for lithology identification is established; real-time guidance decision-making and trajectory adjustment: this application realizes real-time lithology identification, formation early warning and working condition judgment, thereby guiding precise adjustment of wellbore trajectory. This solution does not require additional equipment, is adaptable to complex drilling conditions, completely solves the data lag problem, significantly improves reservoir encounter rate and drilling efficiency, reduces operating costs and risks, and provides reliable technical support for the efficient development of deep coal and gas formations.

The invention relates to the technical field of power electronic components, and discloses a high-frequency transformer winding coil testing method, which comprises the following steps of: 1, measuring the initial temperature of a coil to be tested, measuring the initial high-frequency impedance of the coil to be tested under a specific high frequency, and acquiring an initial state reference; 2, collecting long-period operation data of the high-frequency transformer in practical application, carrying out statistical classification on the operation data, and constructing a compression working condition test sequence containing a high-load working condition and a light-load working condition; and 3, based on the compression working condition test sequence, applying the compression working condition test sequence to the to-be-tested coil. The technical scheme of constructing and applying the compression working condition test sequence from the real working condition is adopted, the technical effect of truly reproducing the composite working state of the coil in the test stage is achieved, and compared with the technical scheme of testing under the static or low-frequency condition in the prior art, the defect that the test result is seriously disjointed from the actual service performance is overcome.

The application provides a rock mass discontinuity three-dimensional Gaussian mixture model statistical classification and recognition method, and belongs to the field of mining engineering. On the basis of drawing the density mapping of the three-dimensional polar projection of the rock mass, the application utilizes a fast decision density peak value algorithm to automatically decide the optimal grouping number of the rock mass discontinuity. Then, the application utilizes a three-dimensional Gaussian mixture model to statistically analyze the size of the posterior probability of each point belonging to each three-dimensional Gaussian, and through a soft clustering mode, each point is distributed to the three-dimensional Gaussian mixture model with the maximum posterior probability, so as to realize the optimal soft clustering recognition of the number of the three-dimensional Gaussian mixture model, that is, the optimal grouping number, thereby realizing the rock mass discontinuity three-dimensional Gaussian mixture model statistical classification and recognition. The application is simple to realize, has a remarkable effect, and meets the application requirements.

This invention relates to the field of data recognition technology, specifically to a data classification and management system based on core features of data statistical comparison. It includes a contract scanning unit, an image digitization unit, a text feature recognition unit, a statistical classification unit, and a fusion storage unit. The invention uses the contract scanning unit to scan paper contracts into image files, facilitating preprocessing of these image files before the text feature recognition unit identifies the text and extracts the contract data. This avoids the time-consuming and laborious process of manual data entry by staff, improving convenience. Then, the statistical classification unit categorizes the contract data, creating datasets that correspond one-to-one with each contract. Finally, the fusion storage unit stores these datasets in a mesh storage device, enabling quick and easy retrieval of company data based on customers and categories, further enhancing management convenience.

This invention concerns an innovative method and device for recording and analyzing road surface smoothness, implemented via a telematics device-main unit (1) installed on a transport vehicle [e.g., truck, bus, etc.] (7) performing independent tasks, such as waste collection, goods transportation, passenger transport, or surveillance. The telematics device - main unit (1) records acceleration [vertical - longitudinal - lateral] (8) and angular velocity through the integrated three-axis accelerometer (2), gyroscope (3), and GPS receiver. Subsequently, the processor-controller (6) correlates the data with geographic coordinates and transmits them via the cellular communication module (5) to the cloud-based computing platform (9), where data is visualized on a GIS map with color-coded smoothness indicators, alert algorithm output, and administrative classification [Municipality, Region, Highway] (10). The device automatically calculates the vertical axis when the vehicle is stationary, regardless of the mounting orientation. It further applies corrections in cases of high longitudinal or lateral acceleration by filtering out vibrations unrelated to road surface degradation. The platform displays the latest measurements for each point, maintains historical records, and activates alerts only when new wear or damage is detected. The data is categorized into geographic units (municipalities, regions, highways), enabling the production of statistical and comparative reports per area, thereby supporting evidence-based planning and prioritization of maintenance interventions.

The embodiment of the invention discloses an intelligent statistical analysis method and device for traditional Chinese medicine clinical research, equipment and a medium, and the method comprises the steps: cleaning traditional Chinese medicine clinical research data, and obtaining normalized clinical research data; performing identification processing on the standardized clinical research data to obtain standardized clinical research data; classifying and labeling the standardized clinical research data to obtain labeled clinical research data; inputting the labeled clinical research data into a statistical classification model for processing to obtain a multi-task statistical analysis result; performing code generation and calling processing based on the multi-task statistical analysis result to obtain an executed statistical analysis code; performing multi-task cooperative processing on the executed statistical analysis result to obtain an integrated cooperative analysis result; and performing visual display processing on the integrated collaborative analysis result through a traditional Chinese medicine clinical research statistical data interaction platform.

The invention provides a method for identifying and eliminating pollutants during quantification of microbe cfDNA in peripheral blood, which comprises the following steps: S1, screening common bacteria of peripheral blood and esophageal-gastric junction tumor, and extracting bacterial nucleic acid; s2, designing a corresponding primer probe combination according to the specific nucleic acid sequence of the bacteria, and carrying out multiple amplification on the bacterial nucleic acid by utilizing fluorescent quantitative PCR (Polymerase Chain Reaction); s3, carrying out statistical classification on the amplified specific nucleic acid sequence in the step S2 by utilizing R statistical software decontam to obtain a statistical classification program; the method comprises the following steps: adding artificially synthesized exogenous DNA during preparation of a sample of microorganism cfDNA in peripheral blood, and setting an identification sample confusion method; and S4, identifying and eliminating pollutants through a statistical classification program, and quantifying the microbe cfDNA in the peripheral blood. The method disclosed by the invention can be used for accurately, quickly and conveniently detecting the bacterial nucleic acid in the peripheral blood, identifying and eliminating polluted samples at the same time, and avoiding false positive during detection.

This invention discloses a morphology-based method and system for classifying pores in tight reservoir porous media, comprising: acquiring microstructural images of rock tight reservoir samples using field emission scanning electron microscopy; labeling the SEM images with two types of samples, pores and matrix / background, as training sets, and training a segmentation model for rock samples; segmenting the sample SEM images using the trained segmentation model to generate binary images that identify the background and pores; automatically measuring pore morphology parameters based on the binary images to obtain pore roundness and aspect ratio; classifying pore shapes according to preset quantitative classification thresholds for pore roundness and aspect ratio, and outputting statistical classification results; this invention achieves a systematic and objective characterization of pore cross-sectional shape, transforming the traditional subjective judgment-dependent pore morphology description into a quantifiable and comparable structural index, solving the problem that traditional pore morphology classification relies on subjective judgment and lacks unified quantitative standards.

The invention provides a data acquisition method, device and equipment, a medium and a computer product, and relates to the technical field of flow acquisition. The method comprises the steps of grouping to-be-collected data according to statistical information obtained after statistical classification is performed according to preset elements, and obtaining at least one piece of feature stream data and analysis windows corresponding to the feature stream data; wherein each group of to-be-collected data corresponds to one feature stream data; meanwhile, each analysis window is made to move from the first moving time node, a first step length is obtained according to at least one piece of feature flow data, data of each piece of feature flow data in a time period corresponding to the analysis window are collected, and collected data are obtained. According to the method, the analysis window is moved according to the changed step length of the feature flow data, and data acquisition is performed on different feature flow data in the time period corresponding to the corresponding analysis window, so that the situation that the system burden is increased due to a large amount of redundant data caused by full-amount acquisition can be avoided, and acquisition and analysis resources can be dynamically allocated for different flows.

The present application relates to the field of wheat image analysis, and specifically discloses a kind of wintering period wheat seedling distinguishing method based on remote sensing image data, for solving the existing wintering period winter wheat seedling identification method more depends on artificial investigation or single color, vegetation index threshold, difficult to fuse multidimensional key parameters, and easily be disturbed by shadow, bare soil and frost residue, leading to strong and weak seedling recognition unstable, partition is not continuous, risk positioning is not accurate Problem, including sample plot layout and remote sensing data acquisition, remote sensing image radiation geometry correction and pixel level registration, vegetation mask extraction and single plant object segmentation, single plant multidimensional characterization extraction and strong seedling potential value construction and sample plot statistical classification and global extrapolation output;The present application constructs seedling potential value and classifies extrapolation by multi-source remote sensing single plant segmentation and C, V, H, L, B fusion, and stably outputs global strong seedling partition and vigorous seedling partition, weak seedling risk area.

The invention belongs to the technical field of intelligent detection, and provides an anti-vibration intelligent detection system and method for precision equipment, and the system comprises a data collection module, a data communication module and an intelligent processing module. The data acquisition module is used for acquiring vibration data and environment data in the operation environment of the precision equipment, and sending the data to the intelligent processing module through the data communication module by using an encryption channel; the intelligent processing module is used for carrying out space-time alignment on the vibration data and the environment data, constructing a fusion data set containing environment correlation features, establishing a statistical classification model and a deep learning model, respectively inputting the fusion data set into the statistical classification model and the deep learning model to obtain a first anomaly detection result and a second anomaly detection result, and outputting the first anomaly detection result and the second anomaly detection result; and fusing the first abnormal detection result and the second abnormal detection result to obtain a vibration detection result. According to the scheme, the accuracy, the high efficiency and the convenience of a vibration detection link are improved according to the vibration data and the environment data and in combination with various analysis models.

The utility model belongs to the technical field of statistical boxes, and provides a classification statistical box for statistics, which comprises a bearing unit and a separation unit, the bearing unit comprises a box body, one side of the box body is fixedly connected with a splicing rail, the other side of the box body is provided with a splicing groove, and a mounting plate is mounted in the box body; the separation unit comprises a separation plate which is located in the box body and located at the top of the mounting plate, a storage groove is formed in one side of the separation plate, a connecting shaft is movably connected to the inner side of the storage groove, and an extrusion plate and a torsional spring are movably connected to the outer side of the connecting shaft; by means of the splicing rails, the splicing grooves, the mounting plates and the partition plates, the flexibility and adaptability of the statistical box are improved, and the statistical box can meet the requirement for classified statistics of different types of data.

The application discloses a kind of based on LMKE's analytic electronic medical record auxiliary hospital inventory management method, comprising the following steps: by image recognition algorithm, the medical record scanned copy is converted into free text and is stored into existing electronic medical record system library;The personnel basic information in electronic medical record, disease, use medicine and medical instrument are extracted;By the word item score calculation method of LMKE, the front as keyword is sorted;Obtain the basic information of character;Generate character basic label;Establish character basic label library;Compare patient basic label library;Compare corresponding chronic disease medical pathological knowledge graph, calculate the consumption of such drugs and instruments by patient number and treatment scheme;Carry out the statistical classification of medicine, calculate the number of existing drug varieties in inventory;Calculate the annual consumption of medicine, and generate a report periodically to submit inventory manager.The application solves the effective information extraction problem caused by a large amount of unstructured information extraction in hospital system electronic medical record.

The invention relates to a CDN (Content Delivery Network) server configuration cleaning method and device, equipment, a medium and a program product. The method comprises the following steps: maintaining domain name information, resource pool information, IP (Internet Protocol) information and a preset mapping relationship; receiving target configuration file information reported by the edge machine according to a preset period; according to the target configuration file information and the mapping relation between the domain name and the component configuration file, verifying and identifying a preliminary redundant configuration file; classifying the preliminary redundant configuration files according to the domain name state and the resource pool information to obtain to-be-cleaned configuration files; and according to a secondary confirmation rule corresponding to the type of the to-be-cleaned configuration file, identifying and deleting a target redundant configuration file in the to-be-cleaned configuration file. Through full-process automatic design of basic data maintenance, bottom layer reporting, center comparison verification, statistical classification, secondary confirmation and deletion cleaning, rapid identification and accurate cleaning of redundant configuration files of the CDN server are realized, and stability and operation and maintenance efficiency of CDN services are effectively improved.

The invention relates to a three-dimensional modeling database service platform for important geological drilling data, and the platform comprises a data quality inspection module which carries out the quality inspection of converged drilling data of all regions, stores the data passing the quality inspection in a drilling database, and analyzes the data not passing the quality inspection, and stores the data in the drilling database; the data management module is used for performing level classification on the data in the drilling database for users with different permissions to retrieve and updating the data in the drilling database; the data modeling module is used for performing three-dimensional modeling on the drilling data; the data service module is used for issuing drilling data in a three-dimensional model form; the drilling data retrieval module is used for providing retrieval and display functions of published data for the user; the special product module is used for providing retrieval and display functions of special products associated with drilling for the user; and the data statistics module is used for displaying drilling data statistics results under various statistical classifications to the user. Unified storage and management of geological drilling data are realized.