31results about How to "Accurate division" patented technology

The present application relates to the technical field of image state recognition, in particular to a kind of based on pattern recognition's picking and replacing hook AI accurate identification and capture system and method, in the present application, the outline change of hook assembly in image sequence frame, boundary difference and gray dynamic are carried out node construction, and combined with edge displacement accumulation analysis, while through graph neural network, cosine value between nodes and coordinate difference are compared jointly, construct path jump sequence, to enhance the response sensitivity of state mutation, under the condition of complex background interference or local occlusion, still can stably extract the key path of morphological evolution, effectively improve the anti-interference and fault tolerance of spatial path recognition, further statistical modeling is carried out on state rate mutation point by hidden Markov model, by matching standard state mode, paragraph merging and invalid segment rejection operation are carried out to abnormal point section, construct state label sequence, realize the accurate division of high confidence, multi-section continuous state.

The invention discloses a power supply network region division method and device for IP cores, and a storage medium. The method comprises the following steps: acquiring a position region of a power supply pin of each IP core in a circuit design drawing; the power supply pins comprise a power supply pin and a ground end pin; combining the position areas corresponding to the power supply pins of the same type to obtain a power supply area where the power supply pins are located and a ground end area where the ground end pins are located; and wiring the power supply pins of each IP core based on the wiring mode of the power supply pins in the circuit design drawing, the power supply area and the ground end area. According to the scheme, the power supply network area of the IP core can be automatically and accurately divided, and the design efficiency and accuracy are improved.

The embodiment of the application provides a fracturing implementation deployment optimization method and an electronic device, and relates to the technical field of fracturing reconstruction. The method comprises the following steps: performing spatial division according to a borehole trajectory of a region to be analyzed and preset reconstruction information, and obtaining a plurality of sub-regions to be analyzed; obtaining a first coordinate of a model grid unit based on a three-dimensional reservoir sweet spot distribution model that has been constructed, and mapping the first coordinate to a current borehole local coordinate system by using a preset coordinate conversion algorithm to obtain a second coordinate of the model grid unit; obtaining a sweet spot index set corresponding to a current sub-region to be analyzed by position screening; and outputting fracturing implementation deployment information according to a plurality of sweet spot index sets corresponding to the region to be analyzed. By combining the borehole trajectory and the preset reconstruction information, the fracturing influence range is divided, and the three-dimensional reservoir sweet spot distribution model is mapped to the borehole local coordinate system, so that the analysis and effective identification of the recoverable potential of the far-well region fracturing are realized, and the accuracy of fracturing deployment is improved.

This invention relates to the field of data processing technology and discloses a method, system, terminal, and storage medium for block partitioning based on a three-dimensional spatial model. The method includes: partitioning input parameters to obtain basic parameters and intensity parameters, and integrating them to obtain a three-dimensional spatial model; acquiring preset three-level intensive elements; calculating the target area based on the preset three-level intensive elements and preset functions to obtain mandatory constraint indicators, development control indicators, and intensive optimization indicators; dividing the target area into plots and arranging buildings based on the three-dimensional spatial model to obtain a three-dimensional spatial partitioning scheme; quantitatively evaluating the three-dimensional spatial partitioning scheme to obtain an evaluation score; and optimizing the three-dimensional spatial partitioning scheme when the evaluation score does not reach a preset threshold to obtain the target three-dimensional spatial partitioning scheme. This invention, based on a three-dimensional spatial model, divides plots in an area and generates schemes, achieving accurate partitioning of plots in an area.

This invention discloses a near-zero carbon port multi-energy integrated system and its self-consistent operation method and medium, specifically relating to the field of wind power monitoring technology. By comprehensively analyzing load variation values, comprehensive wind power conversion values, and wind power conversion turbulence values, a wind power operation status assessment coefficient is calculated. This quantitatively analyzes the operating status of wind turbines to detect potential fault risks in advance, which is beneficial for the management of self-consistent operation of wind turbines. By considering the number of acceptable wind power operation signals generated within the comprehensive early warning set and the time interval between adjacent acceptable wind power operation signals, the reliability of fault prediction can be improved. By comprehensively analyzing and calculating the comprehensive wind power early warning value using the number of acceptable wind power operation signals generated within the comprehensive early warning set and the time interval between adjacent acceptable wind power operation signals, the operating status of wind turbines can be more comprehensively assessed, ensuring the normal operation of the wind power system in the near-zero carbon port multi-energy integrated system.

The application provides a kind of overhead power line surveying and mapping image key area identification processing method and system, wherein the method comprises: obtaining the original image data collected by camera and the geographic position data of camera shooting position;Match the geographic position data with the preset geographic position database, obtain the natural material prior probability data set corresponding to the camera shooting position;Extract polarization feature and image content feature from the original image data, use double-branch attention network, establish material optical property table based on polarization feature in the first branch processing path, fuse natural material prior probability data set and image content feature in the second branch processing path;Based on material optical property table and fusion result, identify key area from original image data;Conduct confidence assessment on key area, generate key area confidence map.The application improves the identification accuracy of natural material key area in outdoor complex scene.

This invention proposes a method for spatial domain identification based on data interpolation and cell type deconvolution, belonging to the field of bioinformatics. This invention addresses the problems of traditional methods failing to utilize spatial gap information between adjacent points and insufficient integration of prior information about cell types at the tissue spatial structure level in low-resolution spatial transcriptome data. The method includes: acquiring spatial transcriptome datasets and single-cell RNA sequencing datasets, and preprocessing the acquired datasets; interpolating the preprocessed spatial transcriptome data and performing cell type deconvolution in conjunction with the single-cell RNA sequencing data; constructing a deep learning model based on a graph convolutional network; training the deep learning model using a self-supervised contrastive learning strategy based on gene expression information, spatial location information, and cell type information from the deconvolved spatial transcriptome data; and performing spatial domain identification on the test data based on the trained model.

The present disclosure relates to a partition method and device for joint excitation of well gun and controllable source, the method comprising: obtaining elevation data, surface feature data and slope data of a target mountain work area and climbing parameters of a controllable source vehicle; superimposing the elevation data, surface feature data and slope data of the target mountain work area to obtain three-dimensional image data; determining a first connected region on the three-dimensional image data according to the climbing parameters of the controllable source vehicle, and adjusting the first connected region to obtain a second connected region; determining a controllable source construction area and a well gun construction area according to the second connected region on the three-dimensional image data and the unconnected area outside the second connected region, respectively, which can accurately divide the mountain well gun and controllable source construction areas, improve the controllable source mountain construction proportion, ensure the safety of mountain seismic exploration acquisition projects, and achieve the purpose of reducing cost and increasing efficiency.

The application provides a building space segmentation method and system based on a maximum inscribed rectangle, comprising: acquiring a building space image to be segmented, reading the number of marked text points in the building space image to be segmented; solving the maximum inscribed rectangle of the building space image to be segmented based on the marked text points, obtaining the maximum inscribed rectangle of the marked text points; for the building space image to be segmented with different numbers of marked text points, different processing is performed on the maximum inscribed rectangle of each marked text point to obtain a space segmentation result, and a building space segmentation image is output; the method performs multi-space division based on the maximum inscribed rectangle, turns the abstract space division problem into an actual image processing problem, and accurately divides the building space in various marked text point situations in accordance with the building specification.

The invention discloses a method for grading geomagnetic storm disasters caused by CME, and relates to the technical field of space weather disaster monitoring, and the method specifically comprises the steps of data collaborative collection, data standardization preprocessing, parameter fusion inversion, trigger source positioning and grade pre-judgment and correction. According to the method, multi-source satellite data are synchronously acquired through a solar dynamics observatory, a sun-earth relation observatory and a Parker solar detector, and through a standardized preprocessing process, a CME comprehensive parameter inversion formula is fused with the multi-source satellite data; comprehensive inversion of multi-dimensional key parameters such as CME explosion time, source region position, three-dimensional propagation direction, initial speed, acceleration, mass and magnetic flux is realized, the innovation point directly aims at the defects that a traditional method is single in data source and incomplete in inversion parameter, and through a multi-source data fusion and mutual verification mechanism, the multi-dimensional key parameters of the CME are obtained. The precision and reliability of CME parameter inversion are improved, and data support is provided for subsequent geomagnetic storm trigger source positioning and disaster grading.

The application discloses a monitoring point layout optimization method and system based on regional scale nitrogen leaching, and relates to the field of agricultural environmental protection.The method comprises the following steps: acquiring a regional area and regional data; based on the regional data, drawing a slope grade map, a groundwater level grade map and a nitrogen accumulation map of the region respectively; performing pixel-to-pixel alignment, superposition and combination calculation on the slope grade map, the groundwater level grade map and the nitrogen accumulation map of the region to generate a plurality of basic units; under a constraint condition, performing initial layout of monitoring points in each basic unit according to the regional area, an obstacle layer and a preset monitoring point spacing; based on an average distance minimization criterion, constructing a target function of the monitoring points; and based on the target function, optimizing the monitoring points in the initial layout by using a space simulated annealing algorithm to obtain an optimized layout of the monitoring points.The application can improve the monitoring accuracy of regional scale nitrogen leaching and the layout efficiency of monitoring well points.

The application relates to the technical field of computers and discloses an address mapping table manager, an address mapping table management method and a computer device.The address mapping table manager comprises a table changing processor, a displacement calculator and a heat manager.The table changing processor is used for receiving a table changing command, acquiring a comparison address and a logical address in the table changing command, determining the source of the table changing command based on the comparison address, and sending the logical address to the displacement calculator if the source is a host.The displacement calculator is used for determining a target partition based on the logical address and a preset partition granularity, and sending the target partition to the heat manager.The heat manager is used for determining a first destination address based on the target partition and a start address of a heat histogram, increasing the heat of a corresponding partition of the heat histogram based on the first destination address, acquiring the heat of each partition in the heat histogram every interval of a preset time period, and determining a hot area and a cold area based on the heat of each partition.The application reduces the computing power and power consumption of a processor core.

The invention relates to the technical field of image segmentation, in particular to a tongue coating segmentation image and digestive disease classification method. According to the method, the position of a particle center point is determined by introducing multi-scale LoG filtering, and tongue particles and tongue coating particles are distinguished according to the law of spatial distribution and density change characteristics; according to the method, local adaptive threshold adjustment is carried out on other pixel points through the change of uneven particle density of different parts, more accurate tongue coating areas and tongue quality areas are obtained through division, and subsequent classification is carried out based on the tongue coating areas and the tongue quality areas. According to the method, the tongue coating area is divided more accurately through multi-scale LoG filtering and spatial statistical characteristics, a reliable data basis is provided for subsequent auxiliary classification of digestive diseases, and the classification accuracy is improved.

The invention discloses an intelligent voltage regulating transformer fault diagnosis method and system based on an improved CNN-BiLSTM model. The method comprises the following steps: firstly, collecting historical data of a voltage regulating transformer for preprocessing; then training is carried out based on historical data of the voltage regulating transformer to obtain a transformer fault diagnosis model, the transformer fault diagnosis model is an improved CNN-BiLSTM model, and an ECA-TAM attention mechanism is introduced into the CNN-BiLSTM model; and finally, inputting the current operation data of the voltage regulating transformer into the transformer fault diagnosis model to obtain a fault diagnosis result of the voltage regulating transformer. According to the method, an ECA-TAM attention mechanism is introduced into the CNN-BiLSTM network model for voltage regulating transformer fault diagnosis, purer and more representative feature input can be provided, interference of redundant information on time sequence modeling is reduced, the key dynamic learning ability is improved, efficient and accurate diagnosis of voltage regulating transformer fault types is achieved, and the fault diagnosis efficiency is improved. The accuracy and timeliness of transformer fault prediction are improved, and stable and safe operation of an electric power system is guaranteed.

The application provides an AI intelligent-based intelligent teaching method, system, device and medium, relates to the technical field of intelligent teaching, and first collects learning track data, teaching feedback data and image data of students in a teaching process; then a dataset is constructed based on the learning track data and the teaching feedback data, meanwhile, the image data is converted into feature points and encoded to obtain feature coding data; subsequently, the K nearest neighbor algorithm is used for collaborative analysis of the dataset and the feature coding data, so as to divide sample clusters of different learning states and extract typical features therefrom; further, the long short-term memory network is used for time series analysis of the typical features, so as to obtain an evaluation result of teaching matching degree and learning efficiency; finally, the teaching resource pushing strategy of the platform is optimized based on the evaluation result. The method can realize accurate profiling and dynamic evaluation of the learning state of students, so as to drive adaptive optimization of the teaching resource pushing strategy.

The application provides a two-stage mapping method and system for driving a 6-color module by a 1-bit chip, acquires 6-color original image data including black, white, yellow, red, blue and green, performs neighborhood dithering processing on the 6-color original image data, divides pixels into foreground color and background color regions according to a weight threshold, encodes the 6-color data into 4-color foreground encoding in the first stage, loads a matching waveform to complete yellow, red and green color display, and then performs hardware drive shutdown and voltage retention on the colored pixels; in the second stage, 4-color background encoding is generated for the uncolored black, blue and white pixels and corresponding drive voltages are applied, while the colored regions are prevented from being disturbed; and stable 6-color display is realized. The application can reuse the 1-bit chip and the existing backplane, greatly reduces the cost, improves the display uniformity and environmental adaptability, and effectively suppresses defects such as color mixing and residual image.

The application provides a method and system for dividing tumor perfusion sub-regions based on dynamic ultrasound contrast data, the method comprising obtaining pre-processed dynamic ultrasound contrast images and pixelizing, so as to obtain time-intensity curves of each pixel point of tumor tissue and average time-intensity curves of normal tissue, obtain perfusion characteristic parameter ratios of each pixel point of tumor tissue, generate perfusion sub-regions of the tumor through clustering results of clustering of all pixel points in the interval, and map information thereof back to the original image. The application maximizes the use of dynamic image data through a non-invasive diagnostic method, comprehensively captures perfusion characteristics of the tumor from the pixel level, visualizes and quantifies tumor perfusion heterogeneity, improves the readability of the dynamic contrast video, helps to explore the correlation between tumor sub-regions and benignity and malignancy and construct a diagnostic model accordingly, improves the diagnostic accuracy of breast cancer, and provides more information support for personalized treatment of patients.

The application discloses a port hinterland division method, device, equipment and medium, relates to the field of transportation network planning, and the method comprises the following steps: acquiring the cumulative transportation cost, cumulative time and time value of each section of transportation route in all feasible paths from each starting city to each port, the feasible path comprising at least one of highway, railway and river network transportation, the cumulative transportation cost comprising the total cost of conversion of transportation mode, and the cumulative time comprising the total waiting time of conversion of transportation mode; determining the minimum generalized cost from each starting city to each port based on the cumulative transportation cost, cumulative time and time value of all feasible paths; determining the target probability of selecting each port for the corresponding starting city based on the minimum generalized cost from any starting city to each port and the comprehensive attraction of each port to the corresponding starting city; and dividing the port hinterland of each port based on the target probability of selecting each port for each starting city.

The application relates to the field of remote sensing image processing, in particular to a remote sensing image data acquisition method for farmland soil type classification, which comprises the following steps: periodically acquiring remote sensing image data of a target region according to a preset period; obtaining distance measurement between any two pixel points in each remote sensing image, segmenting each remote sensing image to obtain a ground object region; analyzing the trend and amplitude of the spectrum curve of each pixel point to determine the red edge performance degree of each pixel point; determining the vegetation growth performance degree of each pixel point; determining the farmland soil segmentation quality of each remote sensing image; screening a to-be-classified image from all remote sensing images of the target region, screening a farmland soil region to construct a bare soil mask image, and combining a neural network to perform farmland soil classification on the ground object region in the to-be-classified image. The application aims to accurately divide the farmland soil region in the remote sensing image and improve the accuracy of farmland soil type classification.

The application discloses a vehicle CAN bus reverse method, system, device and medium based on first-order difference. The method comprises the following steps: acquiring CAN bus communication data of a target vehicle under normal driving conditions, and recording all IDs in the CAN bus communication data to form an ID white list of the CAN bus; extracting ID data tracks corresponding to each ID in the ID white list from the CAN bus communication data; calculating the bit flip rate of each bit of the ID data track; dividing the signal boundary of the ID data track according to a preset signal boundary division rule according to the bit flip rate; extracting the signal track corresponding to each signal from the ID data track according to the signal boundary, and performing first-order difference analysis on the signal track to obtain the first-order difference feature of the signal; and classifying the signal according to the first-order difference feature to obtain the category of the signal. The application can more accurately divide the signal boundary, use a pure mathematical method to classify the signal, and automatically identify and correct the signal format.

The application discloses a power system load curve clustering analysis method, determines the target and requirement of power system load curve clustering analysis, carries out data preprocessing, uses a self-organizing feature mapping neural network to construct a feature extraction model, uses an MAML algorithm to carry out multi-task learning, carries out rapid adjustment through meta learning, applies a Gaussian mixture model to cluster the extracted features, uses indexes to evaluate the clustering effect, carries out clustering result analysis, determines whether the predetermined performance standard is met, and further carries out iterative optimization, so that the self-organizing feature mapping neural network, meta learning and the Gaussian mixture model are combined, and greater value is brought to power system operation and energy management.

The application provides a slope map generation method, system, terminal and medium; wherein the slope map generation method comprises: obtaining elevation raster data based on the spatial range of a target area; calculating the slope value of each pixel based on the elevation raster data, and dividing into each slope level to generate each initial slope area; obtaining the initial boundary of each initial slope area; performing an interpolation operation on each initial boundary to generate corresponding each interpolation line, and simplifying each interpolation line to form each interpolation boundary; dividing each slope area based on each interpolation boundary to generate the slope map corresponding to the target area. By interpolating each initial boundary, obtaining each interpolation line, and forming smooth each interpolation boundary after simplification, each slope area is divided based on each interpolation boundary, so that the generated slope map has smooth boundary of each slope area, good continuity, and high precision, and the display effect of the slope map is improved.

The application discloses a building point cloud layered reconstruction method fusing multiple feature constraints and belongs to the technical field of multiple feature constraints. After original point cloud data is acquired, indoor point cloud data sets are obtained by preprocessing, building a point cloud down-sampling data set, posture correction and extraction after screening. Point cloud space indexes are constructed, the curvatures of each point of the indoor point cloud data sets are calculated and sorted, the point with the minimum curvature is taken as an initial seed point, the neighborhood feature extraction is completed after the normal vector consistency and height difference constraints, the clustering and segmentation of the full point cloud are carried out, the point cloud cluster class attributes are obtained, the ground and ceiling attributes of the point cloud are divided by combining the support, level and topology three-factor coupling. Finally, the accurate extraction of the non-regular floor surface is realized through the progressive process of floor interval division and bidirectional cloth simulation. The application significantly improves the integrity and robustness of the layered reconstruction of the non-Manhattan building, and adapts to the layered requirements of complex scenes such as curved facades and inclined structures.

The present application relates to the technical field of coal underground in-situ gasification, and particularly relates to a high-gas coal seam coal underground in-situ gasification safety ignition method. The present application accurately divides the ignition area based on the length, width and coal seam thickness of the gasification channel; meanwhile, the present application adopts a double-monitoring-unit setting mode of the ignition area and the gas transmission direction to realize blind area-free monitoring of the gasification channel, which not only meets the partition monitoring requirement, but also guarantees the continuity and accuracy of parameter collection, and provides reliable data support for subsequent gasification channel pressure maintenance, purging and ignition point selection. The present application adopts gas introduction for pressure maintenance treatment in the gasification channel, so that the gas adsorbed in the coal seam fissures can be separated out and mixed with air, and the distribution of the gas in the whole channel and the surrounding fissure network is more uniform; meanwhile, the gasification channel is purged after pressure maintenance, so that the gas in the gasification channel can be quickly discharged, and the efficiency of gas discharge is increased.

The present application relates to the technical field of soil data analysis, and particularly relates to a soil organic pollutant content determination method and system; comprising: step S1: a three-dimensional sampling grid is established through the soil to be measured, a plurality of sampling points are set, and monitoring data of physical matrix parameters and multi-dimensional organic matter concentration are collected correspondingly; step S2: a percolation reference sampling point set corresponding to each sampling point is constructed, the physical matrix parameters and multi-dimensional organic matter concentration of each sampling point in the current sampling point and the corresponding percolation reference sampling point set are analyzed, and a sampling point dynamic diffusion influence degree based on percolation topology is obtained; step S3: a high-dimensional joint index vector set is established and input into an initialized neural network, a penalty function is embedded and the neural network is updated through the diffusion influence degree, all sampling points are distinguished by using the updated neural network, it is judged whether the sampling points are stable or change, and the organic pollutant concentration data of each sampling point is output correspondingly; false positive determination errors are overcome.

The application relates to the technical field of vehicle control, and discloses a vehicle lane-changing method, a vehicle lane-changing system, a vehicle and a storage medium, the method comprising the following steps: acquiring vehicle information of a lane-changing vehicle, all lane information of a current driving road and a target detection result, the target detection result comprising obstacle targets on each lane; performing regional division on each lane based on the target detection result, so as to obtain a plurality of feasible regions; determining a lane-changing safety distance based on the vehicle information and the lane information; determining adjacent feasible regions and corresponding lane-changing weights based on all feasible regions, the lane-changing safety distance and the lane information; screening a lane-changing path of the lane-changing vehicle based on the vehicle information, the adjacent feasible regions and the corresponding lane-changing weights; determining a lane-changing path of the lane-changing vehicle based on the lane-changing path and the lane information; and controlling the lane-changing vehicle to drive along the lane-changing path. According to the application, the pose requirement of vehicle lane-changing can be considered, the rationality of lane-changing decision is improved, and the safety of vehicle lane-changing is ensured.

A kind of user segmentation method based on high-speed ETC charging data, the pre-processing of highway toll data is carried out, the field information required for highway user classification is extracted, and the basic information is stored with the license plate number of highway user as key field, to form the travel basic data of highway user;The high-speed toll records of each highway user are sorted according to time, and the data is cleaned according to the abnormal state of time and space, to obtain the high-speed toll data after data cleaning;According to the cleaned data, the information of three dimensions of highway user time index, space index and personal attribute index is extracted respectively, to form the user classification evaluation index system, and the classification of highway user is completed;According to the time index and space index of highway user travel, the classification is carried out in month cycle, to identify various travels such as commuting travel, operation travel, sporadic travel and business travel.The present application has complete information and high precision, and provides basis for highway planning and construction.

This invention discloses a method for analyzing cold seep methane activity by combining benthic foraminifera isotope analysis. This invention relates to the field of Earth science and technology. It involves collecting and preparing sediment columns from cold seep activity areas, covering different activity periods; meticulously separating individual benthic foraminifera from the sediment columns and treating them to eliminate secondary influences; using mass spectrometry to determine the oxygen and carbon isotope values ​​of the benthic foraminifera, constructing continuous isotope time series data; and analyzing the degree of shift in the oxygen and carbon isotope values ​​of the benthic foraminifera based on the continuous isotope time series data. This invention achieves precise quantification of cold seep activity by measuring the oxygen and carbon isotope values ​​of the benthic foraminifera shells and combining sliding window technology and K-means clustering algorithm. It can identify short-term anomalous shift events and, combined with indicators such as isotope range and the number of zero crossover points, accurately classify cold seep activity types, providing a basis for understanding the dynamic changes of cold seep methane leakage.

The application relates to the terminal technical field and discloses a system resource loading method and device, electronic equipment and computer storage medium, which comprises the following steps: acquiring system resources required to be loaded in a target starting stage of a system, dividing the system resources according to resource types of the system resources to obtain a plurality of grouping units; collecting loading time lengths of the grouping units, dividing the grouping units according to the loading time lengths to obtain at least two resource groups, and the resource groups comprise a first resource group and a second resource group; starting a loading process of the system, and performing multi-thread loading on the system resources in the loading process based on the first resource group and the second resource group. The application realizes accurate and efficient division of the system resources, ensures stable operation of the system, improves the starting speed of the system and reduces the starting time length of the system.