35results about How to "Improve extraction accuracy" patented technology

This invention belongs to the field of spectral data processing technology, specifically a spectral data processing system and method based on in-situ data sensing and intelligent analysis. This invention employs in-situ optical imaging, absorption spectroscopy, fluorescence spectroscopy, and PL mapping to acquire real-time three-dimensional spectral data of time, wavelength, and intensity for real-time monitoring of material crystallization, defects, and luminescence properties. It uses an automatic invalid value detection and cleaning algorithm to address data quality issues; it extracts peak position and half-peak width (WHM) characteristic parameters from the spectral data using peak position extraction and WHM calculation methods; it uses a nonlinear optimization algorithm to perform multi-peak Gaussian fitting on the spectral data; and it employs a signal-slot mechanism to achieve real-time synchronization of data presentation and fitting analysis, forming a complete closed loop of in-situ testing, data sensing, processing, analysis, synchronization, and export. This invention achieves real-time acquisition, efficient processing, accurate analysis, and automatic synchronization of spectral data, providing technical support for standardized processing and traceable analysis of spectral data.

The present application relates to a method for extracting an acetabular facies lunata model, in particular to a method for extracting an acetabular facies lunata model based on mixed surface fitting, which solves the technical problem of low precision and robustness of the existing method for extracting an acetabular facies lunata model. The present application realizes rough extraction of the acetabular facies lunata model through spherical surface fitting, and then realizes accurate extraction of the acetabular facies lunata model in combination with ellipsoidal surface fitting, which combines the stability of spherical surface fitting and the anatomical fidelity of ellipsoidal surface fitting. In particular, in the case of complex pathologies such as hip dysplasia, the present application can still maintain high extraction accuracy, and improve the accuracy and reliability of clinical diagnosis and surgical planning. Meanwhile, in the iteration process of ellipsoidal surface fitting, an adaptive fault tolerance threshold is introduced, which effectively solves the problems of sensitivity to noise and strong parameter dependence of traditional methods, and has better robustness in processing complex acetabular morphology.

This invention provides a multimodal fusion-based method for correlation analysis of deep-sea environmental data outside the Yangtze River Estuary, belonging to the field of deep-sea environmental analysis technology. This invention achieves accurate data registration by establishing a spatiotemporal standardization model for multi-source data and employing an adaptive spatiotemporal kriging interpolation algorithm. It utilizes a sparse coding marine signal separation algorithm to construct an overcomplete dictionary to separate mixed signals and extract pure features. Based on an attention mechanism, a feature extraction network is constructed to automatically learn deep feature representations of physical, chemical, and biological parameters. A matrix rank deficiency detection algorithm is used to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism based on wavelet transform is constructed to fuse multi-scale features. A Shapley value interpretability evaluation system is established to quantify the importance of correlated features. This invention solves the technical problem of inaccurate correlated feature extraction during the fusion of multi-source heterogeneous marine environmental data.

The application discloses a water body extraction method based on combined water body index frequency, comprising the following steps: S1, acquiring remote sensing image data and pre-processing the remote sensing image data; S2, constructing a water body index and constructing an instantaneous water body extraction decision tree model according to the water body index; S3, performing instantaneous water body pixel recognition and extraction according to the instantaneous water body extraction decision tree model, discriminating the water body and preliminarily determining the average water body; S4, extracting the water edge line by using a Canny edge detection method, and determining the average water body extraction result according to the output water body pixel value, the edge detection and the boundary elimination result. The application can realize average water body extraction based on dense long-time sequence images, improve the water body extraction precision, improve the effectiveness of water body extraction in the building shadow and terrain shadow noise environment, resist the interference of the cirrus cloud noise in the single image, and make the large-scale and long-time sequence water body extraction more universal.

This invention discloses a method and system for identifying innovative points in academic papers, relating to the field of artificial intelligence technology. The method first processes the paper abstract through a concept path extraction module, including: structured semantic segmentation, concept pair extraction and verification, constraint relation triple generation, hierarchical verification, and path optimization, to construct a complete set of concept paths for the paper. Then, in a rare path discovery module, the popularity index of each concept path in the global path frequency dictionary is calculated and compared with a threshold to identify rare paths as the scientific innovative points of the paper. This invention effectively suppresses the illusion of language models through a knowledge graph constraint mechanism, significantly improving the accuracy of concept path extraction and its coverage of long-tail concepts, achieving accurate and efficient identification of innovative points in academic papers at the path level.

The application is suitable for the technical field of image processing, and provides a battery glue line skeleton extraction method based on an improved ZS thinning algorithm, which comprises the following steps: preprocessing a collected battery glue line image to obtain a binary image; performing improved ZS thinning on the binary image, dividing the image into odd and even subdomains for batch processing, and introducing a constraint condition to iteratively delete redundant pixels to obtain a preliminary skeleton; using a T-shaped 4-neighborhood deletion template to remove T-shaped redundant pixels and realize complete single-pixelization; through 8-chain code tracking, identifying and removing burr branches caused by glue overflow and uneven glue coating, while protecting nodes to obtain a final glue line skeleton. The application solves the problems of skeleton redundancy, over-thinning and burr in existing thinning algorithms, realizes high-precision, single-pixel and burr-free glue line skeleton extraction, and can meet the online detection requirements of battery assembly lines, and has good industrial applicability.

The application provides an aircraft wing skin corrosion depth prediction method based on a GAN and an improved LightGBM algorithm, which comprises the following steps: S1, data enhancement: four fully connected layers are used to extract feature information between columns; S2, an improved condition generator and discriminator are used, and parameters are updated; S3, the LightGBM algorithm is improved, and the aircraft wing skin corrosion depth is predicted. The aircraft wing skin corrosion depth prediction method using the generative adversarial network for data enhancement and the gradient regression model for sample regression can accurately predict small sample data. Meanwhile, the gradient regression model LightGBM algorithm is improved, which is more suitable for the prediction of the aircraft wing skin corrosion depth, and can greatly improve the prediction accuracy of the aircraft wing skin corrosion depth prediction.

This invention discloses a hybrid lunar surface segmentation method, system, device, and storage medium for photogrammetric point clouds in lunar rover exploration areas, belonging to the field of deep space exploration technology. The method includes: denoising and extracting initial lunar surface points from the raw scattered point cloud collected by the lunar rover in its exploration area; refining the extracted initial lunar surface points and labeling them as first lunar surface points; dividing all first lunar surface points into sub-blocks and obtaining terrain scene information for each sub-block; extracting and labeling second lunar surface points from the denoised scattered point cloud based on adaptive slope; extracting third lunar surface points from all unlabeled points based on an irregular triangular network, and labeling other points in the original scattered point cloud as non-lunar surface points; and correcting misclassified non-lunar surface points based on connected component segmentation and slope statistics, achieving accurate segmentation of lunar and non-lunar surface points. This invention can robustly filter out non-lunar surface points while preserving local lunar micro-topographical points.

This invention relates to a flood disaster assessment method based on the fusion of remote sensing imagery and GIS data, belonging to the field of flood disaster monitoring and assessment technology. This method solves the problems of insufficient timeliness, limited coverage, and the inability of a single data source to comprehensively reflect the disaster situation in traditional assessment methods. Its technical solution mainly includes utilizing GIS data to provide spatial semantic background support, employing an improved UMNet++ model to accurately extract water body information before and after the flood from Sentinel-2 remote sensing imagery, and achieving quantitative assessment and hierarchical visualization of disaster severity through multi-source data fusion and spatial overlay analysis. The beneficial effects of this invention are that it significantly improves the accuracy and comprehensiveness of flood disaster assessment, enabling rapid and scientific disaster response and decision support.

The application discloses a solar meridian extraction method, device, equipment, medium and product, relates to the technical field of atmospheric polarized light navigation, and comprises the following steps: acquiring an original polarization image of a target area; in a Cartesian coordinate system, determining a linear polarization degree of an effective data area according to the original polarization image; performing coordinate system conversion on the linear polarization degree and determining an optimal symmetry axis based on a mirror symmetry principle; extracting a polarization angle corresponding to the effective data area based on the linear polarization degree of the effective data area; performing complex conversion and coordinate system conversion on the polarization angle corresponding to the effective data area to determine an antisymmetric polarization angle; extracting a skip line estimation value by using an antisymmetric mode according to the antisymmetric polarization angle; and fusing the optimal symmetry axis and the skip line estimation value through time series filtering to obtain a solar meridian. The application can improve the extraction precision of the solar meridian, thereby improving the precision of heading estimation.

This invention relates to the field of terminology database technology in the construction engineering field, and discloses a method and system for constructing and applying a terminology database in the construction engineering field. The method includes preprocessing unstructured data to obtain structured construction engineering text data; extracting structured construction engineering text data based on a joint extraction architecture to obtain structured terminology data and construction engineering triple information; establishing a standard database and a terminology database; constructing a terminology-standard two-layer knowledge graph based on the inherent relationship between the standard database and the terminology database and the construction engineering triple information; and responding to user queries by using a hybrid decision-making mechanism based on rule-based reasoning and graph neural network learning to call the standard database, terminology database, and terminology-standard two-layer knowledge graph to obtain query results. This invention realizes an intelligent closed loop for the entire lifecycle of construction engineering terminology from extraction and management to application, solving the problems of difficult acquisition, complex management, and inefficient application of industry terminology knowledge.

This application discloses a method, system, device, and storage medium for generating project documents. The method involves acquiring code data, parsing the code data to determine its structural information, and then mapping this structural information to corresponding positions within the code data. Based on the structural information, the code data is split into several code segments. A trained large language model is used to generate corresponding first descriptive text. Based on the first descriptive text for each code segment, the project document corresponding to the code data is obtained. This application generates project documents corresponding to code data automatically, reducing manual costs. Using a large language model to extract information from the code data and obtain the first descriptive text improves the efficiency of project document generation, reduces the probability of errors, and enhances the quality and usability of the project documents. The technical solution of this application can be widely applied in the field of code processing technology.

This invention relates to the field of aircraft assembly technology, and more particularly to an aircraft door repair method based on measured data. It includes: processing the original point cloud data using filtering and denoising algorithms, and filling in sharp boundary missing areas using point cloud interpolation algorithms to enhance point cloud quality; identifying the geometric boundary features of the door and fuselage frame using a feature-aware boundary extraction algorithm; calculating the door repair amount based on the minimum clearance principle, and outputting a precise door repair line. This invention achieves accurate geometric identification and repair trajectory generation for thin-walled, complex curved surface door structures. This method effectively solves the geometric deviation problem caused by manufacturing errors and structural deformation in door repair, significantly improving the automation level, assembly accuracy, and processing efficiency of aircraft door repair, and providing highly reliable data support and technical path for digital manufacturing in aviation assembly.

The present application belongs to the technical field of digital publication processing, and provides a multi-modal PDF content purification and intelligent proofreading system and method based on visual perception enhancement, which comprises a visual perception module, a semantic understanding module and an intelligent decision module; the visual perception module eliminates physical layer interference by generating multi-resolution images, extracting fine structure features and locating invisible characters; the semantic understanding module constructs a knowledge graph and a DST-Transformer model to realize character recognition, semantic coding and image-text association repair; the intelligent decision module outputs a purified document through weighted confidence calculation, dynamic threshold adjustment and cross-platform verification; the method corresponds to the three module steps, realizes full-process processing from physical layer analysis to logical layer reconstruction and then to intelligent output, improves the PDF content purification accuracy and cross-platform compatibility, and is suitable for electronic document deep purification and proofreading.

This invention relates to an adaptive diagnostic method for inter-turn short-circuit faults in a dual-phase three-phase permanent magnet synchronous motor, belonging to the field of motor fault diagnosis technology. By establishing a mathematical model and an adjustable model for inter-turn short-circuit faults in the dual-phase three-phase motor, and combining multi-phase motor space vector decoupling transformation, a short-circuit fault component is introduced into the harmonic subplane of the stator voltage equation. Fault characteristic values ​​are designed using the x-y current residual between the actual motor and the adjustable model. The fundamental amplitude is extracted as a fault severity feature through orthogonal Fourier transform. An observer based on the mapping relationship between the short-circuit current residual and the fault turns ratio is constructed. A model reference adaptive law for the piecewise PI regulator is used to dynamically adjust the PI parameters according to speed and load conditions, achieving adaptive feedback estimation of the short-circuit turns ratio. This improves the accuracy and real-time performance of fault feature extraction, simplifies the fault-tolerant algorithm and optimizes the disturbance observer parameter design, solves the diagnostic distortion problem caused by changes in operating conditions, and provides an optimized solution for motor monitoring.

This invention relates to the field of energy management technology, and more particularly to a method and system for dynamic balance management of enterprise energy supply and demand. The method collects multi-source heterogeneous data from enterprises; extracts key features through spatiotemporal alignment and data fusion, and utilizes a multimodal variational autoencoder; inputs these features and enterprise physical topology parameters into an energy supply and demand balance prediction model constructed by fusing a deep kernel learning neural network based on kernel function improvement and a deep Gaussian process, predicting net energy demand for future periods; and then inputs the prediction results into an energy dispatch optimization decision model constructed based on a dense connection network and attention mechanism to generate the optimal energy allocation strategy. This method achieves closed-loop management of deep multi-source data fusion, accurate demand prediction, and intelligent optimization dispatch, improving the operational efficiency, economy, and dynamic response capability of enterprise energy systems, and is suitable for multi-energy collaborative management in complex industrial scenarios.

The application discloses a farmland plot extraction method in African arid regions based on MAA-BCNet, which comprises the following steps: pre-processing satellite optical images, preparing samples, using RF+TOP-K method to screen spectral features, and using principal component analysis method for data dimension reduction; a MAA-BCNet model is built and trained, a training area and a test area are selected, an image is cropped, a label is prepared to make a data set, and the data set is balanced and enhanced; a double-encoder and a double-loss function are designed, and an AdamW optimizer is used in the model training process; axial attention and edge detection are designed for multi-scale feature fusion; a skip connection is used for up-sampling; and the farmland distribution in the African arid regions is predicted and mapped. The application saves the labor and time cost, guarantees the food safety in the African arid regions, solves the problem of fuzzy farmland plot edges in the arid regions, and provides important technical support for farmland management, agricultural irrigation and social sustainable development.

The invention relates to a map straightening method. The map correction method comprises the following steps: constructing a target map, and carrying out first filtering processing on the target map; extracting and grouping a plurality of straight lines in the target map to obtain a plurality of corresponding straight line groups; determining two adjacent straight line groups meeting a preset condition in the plurality of straight line groups as a target candidate group, and calculating an angle mean value of the target candidate group; and determining a straightening angle based on the angle mean value, and carrying out map straightening processing according to the straightening angle. According to the scheme, the straight line extraction precision can be improved, the optimal straightening angle is determined according to the global straight line, and the straightening angle obtaining accuracy is improved.

The application provides a text topic extraction method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a Bert word vector and a Bert sentence vector of a to-be-processed text; taking the Bert word vector and the Bert sentence vector as nodes to construct a topological graph model; optimizing the nodes of the topological graph model by using a graph autoencoder with an attention mechanism to obtain multiple features of each node; and analyzing the multiple features by using a clustering algorithm to extract topic information of the to-be-processed text. The method can improve the accuracy of text topic extraction.

The application discloses a gravity anomaly calculation method, device, equipment, storage medium and product, relates to the satellite altimetry data processing technical field, and the gravity anomaly calculation method comprises: obtaining sea surface height data observed by an altimetry satellite; according to the sea surface height data, a plurality of residual geoid gradients in different directions are calculated; the plurality of residual geoid gradients in different directions are fused by a Bayesian triangular cap method, and an east-west direction component and a south-north direction component of the residual geoid gradient are obtained; and based on the east-west direction component and the south-north direction component of the residual geoid gradient, the marine gravity anomaly of a target region is calculated by a gravity anomaly inversion algorithm. The application solves the technical problems of low utilization rate of multi-direction gradient information of a single altimetry satellite and insufficient component extraction precision, realizes mining and optimization of multi-direction gradient information of a single satellite, and improves the inversion precision of the marine gravity anomaly.

This invention relates to the field of engineering surveying technology, specifically to a method and system for automatically extracting bridge edge lines from point clouds. The method includes the following steps: acquiring a 3D point cloud dataset of the bridge and its surroundings; determining initial edge line points, filtering the point cloud based on a circular neighborhood and converting to polar coordinates; eliminating interference points through elevation change detection; calculating the initial normal azimuth angle; locating the initial edge line points on the opposite side of the bridge; iteratively searching for adjacent edge line points along a preset bridge direction, using the initial edge line points on both sides of the bridge as seed points; and determining the termination condition of the search through an included angle threshold to generate complete double-sided edge lines of the bridge. The system includes modules for data input, initial settings, direction calculation, opposite-side positioning, iterative detection, and result output. This invention solves the problems of high safety risks and low efficiency in traditional manual surveying, as well as the poor accuracy of point cloud edge line extraction by manual vision. It achieves automated and high-precision extraction of bridge edge lines in complex environments, providing intuitive quantitative basis for construction decisions.

This application relates to the field of fault prediction technology, specifically to a method and system for monitoring and early warning of fault risks in nuclear power plant equipment. Specifically, it includes: constructing a first fluctuation feature value based on the randomness of the peak occurrence time and the fluctuation characteristics of the signal sharpness in the vibration signal of a planetary gearbox bearing in a nuclear power plant; constructing a second fluctuation feature value by analyzing the distribution of sideband features in the envelope spectrum of the bearing vibration signal in each sampling period and comparing it with the center frequency of the previous sampling period; appropriately adjusting the filter length based on both factors, and combining this with a filtering algorithm to extract fault feature signals from the bearing vibration signal in each sampling period, thereby performing fault detection of the planetary gearbox within each sampling period. This solves the problem of inappropriate filter length values ​​when filtering the bearing vibration signal of a nuclear power plant planetary gearbox, improves the extraction accuracy of fault feature signals, and contributes to the accuracy of subsequent fault detection.

The application discloses a full-mouth tooth crown automatic segmentation method based on gum line identification and region growth, relates to the field of dental digital restoration, and comprises the following steps: pre-processing a tooth model obtained by mouth scanning to obtain an initial mesh model; identifying a gum line based on the initial mesh model to obtain gum line region mesh nodes; segmenting a gum and a tooth crown region based on the gum line region mesh nodes to obtain a tooth crown region mesh model; and segmenting the tooth crown region mesh model to obtain mesh models of individual tooth crowns. The application provides the full-mouth tooth crown automatic segmentation method based on the gum line identification and the region growth, so as to solve the problems of inaccurate gum line identification, poor region growth segmentation effect and poor full-mouth adaptability in the prior art, realize accurate extraction and feature reservation of the full-mouth tooth crown, and provide reliable support for automation and standardization of digital oral restoration.

This invention proposes an automatic acquisition and fusion application method and system for multi-source precipitation data from the Internet. The method includes crawling precipitation data from target websites and decrypting encrypted webpage data, performing preprocessing and key information extraction on the raw data, storing the data, removing abnormal data through quality verification, fusing data from the same source, and providing a standard data service interface. The system includes a data crawling module, a data preprocessing module, a data storage and quality control module, and a data service interface module. This method and system can effectively overcome font encryption anti-crawling mechanisms, improve the integrity of precipitation data acquisition, extraction accuracy, and quality reliability, reduce manual intervention, and achieve integrated automated processing from acquisition to service. It can be widely applied in meteorological and hydrological monitoring, flood control and disaster reduction, smart city management, and smart agriculture.

Embodiments of the present application provide an information extraction method and device, applied in the field of artificial intelligence technology, comprising: obtaining a to-be-recognized text, and constructing a word vector sequence of the to-be-recognized text; inputting the word vector sequence into a relation classification layer to obtain a target relation type contained in the to-be-recognized text; for each target relation type, determining at least one entity contained in the to-be-recognized text under the target relation type based on a type feature vector corresponding to the target relation type and the word vector sequence; and constructing a triple information corresponding to the target relation type based on the target relation type and the at least one entity. Through the relation classification layer, at least one target relation type contained in the to-be-recognized text is extracted, and the entity contained in the to-be-recognized text under the target relation type is determined, thereby solving the problem that a relation model cannot be constructed for an incomplete sentence structure, and avoiding errors generated by an entity extraction model from being passed to a relation extraction model, so as to improve information extraction accuracy.

The application relates to a power load prediction method based on a CRKformer model, electronic equipment and a storage medium, which comprises the following steps: acquiring time series data, constructing a data set and performing normalization preprocessing; converting the standardized data to a frequency domain, obtaining embedded features through linear dense operation, performing context shaping filter calculation, and obtaining a time domain optimization feature sequence through inverse Fourier transform; obtaining time series dependent features through the combination of self-attention mechanism and cross-attention mechanism of endogenous variable sequence embedding in the strong position coding weight; fitting a nonlinear relationship through a Kolmogorov-Arnold network, and enhancing the time series dependent features by using a learnable activation function; generating a prediction result by linearly projecting the endogenous output embedding, performing inverse normalization, and outputting a load prediction value. Compared with the prior art, the application has the advantages of inhibiting noise interference, accurately capturing time series dependence, and high prediction accuracy.

This application relates to a method, apparatus, and computer device for extracting vortex core features of a combustion chamber. The method includes: acquiring flow field data of the combustion chamber and extracting three-dimensional vortex core data based on the flow field data; identifying planar vortex core data corresponding to the three-dimensional vortex core data; and extracting vortex core feature information of the combustion chamber based on each planar vortex core data using a vortex core feature extraction strategy. This method improves the efficiency, comprehensiveness, and accuracy of extracting vortex core feature information of the combustion chamber.

This invention proposes a method and system for analyzing cable force in stay cables based on enhanced frequency domain decomposition, relating to the field of bridge engineering technology. Addressing the problem of poor cable force monitoring accuracy in existing technologies, this invention acquires vibration videos of stay cables and preprocesses them. The preprocessed vibration videos undergo multi-scale, multi-directional signal processing, phase analysis, and quality-weighted fusion to extract displacement field data with sub-pixel accuracy. Key points in the displacement field data are selected based on the structural mechanical characteristics of the bridge. A displacement time history matrix is ​​constructed based on the displacement data of these key points over time. Trend terms and DC components are removed from the displacement time history matrix to obtain a power spectral density matrix. Singular value decomposition is performed on the power spectral density matrix to construct single-valued spectral curves. Modal confidence criteria are used to screen modes and frequencies in the single-valued spectral curves to determine the natural vibration frequencies of each order of the stay cable. Cable force is calculated based on these natural vibration frequencies. This invention achieves high accuracy in cable force calculation.

The application discloses a kind of intelligent maintenance suggestion recommendation method, system, equipment and medium, it is related to intelligent maintenance suggestion recommendation field, the method includes: using pre-training and after field data fine-tuning large language model, the intent analysis and component entity extraction of fault description text are carried out;Based on component entity synonym library, maintenance component entity is normalized;Using hybrid retrieval strategy, similar fault cases are recalled from fault knowledge base;Using large language model, information extraction and structured reorganization are carried out on the similar fault cases recalled, generate fault summary report, retrieve associated maintenance procedure items from maintenance procedure knowledge base, filter the relevance of the maintenance procedure items retrieved, select the operation steps directly associated with the current fault scenario and core component entity, generate maintenance suggestion and push to client, the application improves the precision of component entity extraction, reduces the cost of rule maintenance, improves the adaptability of new fault scenario.

The application discloses a kind of self-adapting micro-doppler corner point feature extraction method and device, comprising: it is proposed to use micro-doppler corner point feature to realize through-wall radar human behavior recognition, and gives a kind of self-adapting corner point feature extraction method based on Gauss difference convolution filter and deformable convolution network;Micro-doppler corner point feature is defined as the point that gray scale sharply changes in different directions in radar square distance-time image and square doppler-time image, reflects the inflection point of human body limb node's motion trajectory curve, stationary point, curve intersection and boundary;The corner point feature extraction method proposed uses Gauss difference convolution filter to extract micro-doppler corner point supervision label on simulation data, then trains μD-CornerDet model using these labels;Inference stage, only μD-CornerDet model is used to obtain corner point feature map for measured data;The application verifies the effectiveness and robustness of the proposed method through numerical simulation and measurement.