155 results about "Similarity matching" patented technology

The application discloses a three-dimensional model fast retrieval method, equipment and medium, and relates to the computer technical field. The method comprises the following steps: in response to receiving a part of a two-dimensional sketch of a three-dimensional model drawn by a user, performing image segmentation on the part of the two-dimensional sketch to obtain a plurality of sub-images; performing mapping processing on each sub-image to obtain an initial feature corresponding to each sub-image, and performing attention calculation on the initial features corresponding to the plurality of sub-images to obtain a plurality of first key features; fusing the plurality of first key features to obtain a second key feature corresponding to the part of the two-dimensional sketch; based on the second key feature, performing similarity matching on a feature database to obtain a plurality of target features, and searching a three-dimensional model set corresponding to the plurality of target features from a three-dimensional model database. In this way, the target three-dimensional model meeting the design intention of the user can be quickly and accurately retrieved according to the part of the sketch of the model drawn by the user, so that the design efficiency and the user experience are significantly improved.

This invention discloses a method and system for data fusion of multi-platform commercial outlets based on multi-source heterogeneous data. It relates to the field of data processing technology. The method involves acquiring commercial outlet data from multiple platforms and performing validity verification to generate an initial data foundation for each platform; extracting outlet coordinate information and performing a unified format conversion to obtain a coordinate-standardized commercial outlet dataset; constructing a multi-industry knowledge graph and an industry-wide common affix library; using algorithms to remove common name affixes and retain core feature identifiers to generate a feature-identified dataset; constructing a similarity algorithm to extract multiple features of outlets, calculate their similarity separately, and fuse them to obtain an overall similarity, generating a similarity matching result set; and identifying and removing duplicate data from multiple platforms based on the matching results to generate a full dataset of multi-source fused commercial outlets. Compared to traditional fusion methods, this method achieves accurate feature identification and quantitative determination of duplicate data, improving the completeness and accuracy of the fused data and making more efficient use of computing power.

This invention discloses a method for reusing obstacle avoidance trajectory parameters based on local environmental geometric and motion constraint features. The method includes the following steps: acquiring a local point cloud to construct a local map; calculating the geometric residuals from points to planes based on the local map to obtain residual statistical features; calculating the plane normal distribution based on the local map to obtain structural orientation features; and constructing an information matrix based on the Jacobian matrix optimized by the direct method pose to obtain motion constraint features; combining the residual statistical features, structural orientation features, and motion constraint features into a local environmental feature descriptor; binding the local environmental feature descriptor with trajectory generation parameters of historical obstacle avoidance trajectories and storing it in a database; calculating the similarity between the current local environmental feature descriptor and the historical feature descriptors in the database, and selecting the corresponding historical trajectory generation parameters based on similarity matching; and using the historical trajectory generation parameters as the initial parameters for the current obstacle avoidance trajectory planning.

This invention relates to the field of ischemic injury model construction technology, and particularly to a method for constructing a mouse ischemic injury model for evaluating the protective effect of GDF-15. The method includes acquiring a dataset of mouse physiological parameters to determine physiological feature vectors, thereby determining an individual vulnerability index and performing similarity matching with the vulnerability index of a specific individual. Based on the matching results, a matching sample set is constructed, and then an ischemic injury model is constructed using a deep learning network model. The model is then dynamically simulated using the specific individual vulnerability index, specific intermediate monitoring data, and specific infarct area percentage data to output a simulated protective effect index to determine if the model is qualified. If unqualified, the similarity matching threshold is adjusted based on the degree of deviation, and the matching and model construction are repeated. This invention significantly improves the uniformity and construction success rate of the ischemic injury model through individualized matching and dynamic feedback optimization, providing a reliable model for evaluating the protective effect of GDF-15.

A kind of industrial carbon emission data missing filling method based on process procedure and timing similarity knowledge migration, for input data, increase the descriptive text related to process procedure, utilize large language model to extract industry, product, process route text features and construct vector representation, in the pre-established vector database, based on the similarity matching of industry, product, process route, the first n most relevant data groups are matched, and the similarity of carbon emission related data and input carbon emission related data is further calculated;Comprehensively consider the similarity of industry, product, process route and carbon emission related data similarity, select a deep learning model, and on this basis, utilize input carbon emission related data for training, finally use the model after knowledge migration to complete missing value filling.A kind of industrial carbon emission data missing filling system is provided.The present application improves the accuracy of missing value filling under the condition of insufficient data samples.

A computing system (10) including one or more processing devices (12) configured to receive an ontology (20), receive one or more input documents (28), and, based at least in part on the ontology, extract ontology-mapped data (32) from the one or more input documents. The one or more processing devices compute a hypergraph (62) of the ontology-mapped data. The one or more processing devices receive an input query (70) and perform similarity matching between the hypergraph and the input query to identify one or more relevant hyperedges (88). At a generative language model (30), the one or more processing devices compute a language model output (92) based at least in part on a context (90) that includes the input query, the plurality of relevant hypernodes, and the one or more relevant hyperedges. The one or more processing devices output the language model output.

This invention discloses an automatic business application construction method based on AI semantic analysis, belonging to the field of artificial intelligence semantic analysis and automatic software application generation technology. The method includes: acquiring user-input business requirement description text, performing word segmentation and stop word filtering to form a requirement word sequence; inputting the requirement word sequence into a pre-trained semantic encoding model to generate semantic feature vectors; extracting business intent tags, functional entity sets, and dependency triples; performing similarity matching between the business intent tags and functional entities and component semantic vectors in a component knowledge base to determine the main control component and functional components; constructing a functional component call relationship graph and generating a component topology structure according to topological sorting; and calling an application building engine to instantiate each component sequentially according to the component topology structure, outputting a business application package. This invention enables automatic mapping of business requirements to application structures, reduces manual configuration, and improves the intelligence and consistency of business application construction.

The application relates to the technical field of charging facility operation and maintenance, and discloses an electric vehicle looped network sharing intelligent operation and maintenance method, which comprises the following steps: a cloud server acquires monitoring data and extracts a multi-dimensional fault feature vector representing the space-time operation state of a looped network and a charging module; a detection model fusing a graph neural network and a bidirectional long short-term memory network is used to deeply fuse space and time features to output a fault probability; a fault type is determined based on a probability decision logic and a multi-modal cross-validation mechanism, and a similarity matching algorithm is used to lock a specific fault source; and a hierarchical self-healing control instruction is sent to a power distribution control module and a rectification module based on a fault level, and a derating operation, isolation bypass or full stop protection strategy is respectively executed. Through the multi-dimensional feature fusion and hierarchical response mechanism, the application effectively solves the problem of difficult DC looped network fault positioning, and guarantees system service continuity.

This invention discloses a method and device for auxiliary diagnosis of gas turbine faults, belonging to the field of industrial equipment fault diagnosis technology. Utilizing intelligent retrieval algorithms and efficient database support, it can quickly match relevant cases from a massive database of historical cases and provide diagnostic suggestions when a gas turbine experiences a warning or anomaly, shortening the fault diagnosis time. By characterizing historical fault cases of the gas turbine and combining them with current operating background parameters for multi-dimensional, dynamically weighted similarity matching, it can more accurately identify historical cases most similar to the current abnormal operating conditions, thereby improving the accuracy of fault diagnosis. In the specific application scenario of gas turbine power plants, it demonstrates unique technical contributions and significant practical value, which is of great significance for ensuring the safe and stable operation of gas turbines, improving power generation efficiency, and reducing operation and maintenance costs.

This invention discloses a rapid cost assessment method for engineering changes based on a knowledge graph, comprising: S1, synchronously collecting multi-source heterogeneous data for entity extraction and relation alignment to construct an engineering knowledge graph; S2, inputting change instructions, using a bidirectional graph neural network to identify initial nodes and generate a change impact subgraph; S3, introducing an improved dynamic hierarchical graph attention network with a spatiotemporal decay dependency mechanism, constructing a dynamic decay factor to weight and encode features at each level, and outputting a change feature vector; S4, calling quota standards for cost mapping, performing difference calculation and automated splitting, and outputting a basic cost dataset; S5, combining historical change database similarity matching, and outputting corrected estimated values ​​after deviation calibration and nonlinear correction; S6, encapsulating and generating an assessment report and writing it back to the knowledge graph archive. This invention achieves deep analysis of change propagation paths and refined dynamic cost estimation, improving assessment efficiency and accuracy.

Embodiments of the present application provide an unsupervised visual detection method for assembly abnormalities of industrial structural parts and related equipment, relating to the technical field of industrial visual detection. The method comprises: extracting local patch features and constructing a memory bank through a normal sample training set, reconstructing features based on the memory bank, generating a memory index histogram descriptor for representing local statistical structures, simultaneously constructing a feature similarity graph and performing graph enhancement processing to obtain a graph-enhanced reconstructed feature representation, and then constructing an associated memory index histogram memory bank and a global feature memory bank; performing the same processing on the image to be detected, obtaining the candidate normal sample most similar to the structure of the image to be detected through two-stage candidate sample screening, performing similarity matching based on the global feature memory bank to obtain a logical abnormality score, and fusing it with the local abnormality score obtained based on the local patch memory bank to obtain the final abnormality detection result. The present application has the advantages of high detection accuracy, strong robustness, and no need for abnormal samples.

This invention relates to the field of rubber composite materials technology, and particularly to an intelligent evaluation method for the dispersion uniformity of rubber fillers based on image recognition. The method includes: acquiring images of multiple regions on the sample surface; extracting image features and performing similarity matching with pre-stored standard feature data to obtain the preliminary dispersion level and matching confidence level of each image; determining the effective dispersion level and weight of each image based on the overall statistical distribution of all preliminary levels, combined with the confidence level and level of each image; calculating a weighted average dispersion level based on the effective level and weight, and determining the final dispersion level according to its mapping relationship with a preset level; simultaneously, calculating uniformity evaluation indicators based on the overall statistical distribution, and locating abnormal dispersion areas based on the effective level and weight; and finally outputting an evaluation report containing the above-mentioned level, indicator, and location information. This invention achieves an objective, comprehensive, and interference-resistant intelligent evaluation of the dispersion uniformity of rubber fillers.

This invention relates to a zero-shot Oncomelania snail identification method and system based on a structured knowledge base and attention guidance, belonging to the field of image processing technology. The method includes: acquiring original images of Oncomelania snails; generating an attention map using a pre-trained model to locate and crop discriminative regions; constructing a structured Oncomelania snail knowledge base and guiding a large language model to generate fine-grained text descriptions; extracting image and text features separately, calculating region weights and text weights; and determining the snail species through weighted image-text similarity matching. This invention achieves zero-shot identification without annotating image data, effectively suppresses interference from complex backgrounds, significantly reduces data and annotation costs, and improves identification efficiency and robustness, making it suitable for low-cost Oncomelania snail monitoring in field environments.

This application relates to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for processing wiring diagrams of substations. The method includes: acquiring an image of a substation wiring diagram and performing quality enhancement processing on the image to obtain a processed image; performing optical character recognition (OCR) to obtain a title recognition result and determine the diagram type; based on the diagram type, performing region segmentation on the processed image to identify and locate the wiring diagram area, text area, and table area; parsing to obtain the structural data of each device in the wiring diagram; converting the data into standardized data for the power industry; and, provided the standardized data passes rule review, performing similarity matching between the standardized data and reference standardized data to obtain a matching result; and based on the matching result, outputting the quality review result of the wiring diagram. This method can improve the accuracy of wiring diagram review.

This invention discloses a method and system for predicting converter gas and coordinating oxygen optimization based on trend perception, belonging to the field of intelligent control and energy optimization technology. The method for predicting converter gas and coordinating oxygen optimization includes: data acquisition and preprocessing; constructing a historical trend sample set; performing real-time single-time prediction of gas based on similarity matching; multi-step rolling prediction; and inputting the obtained multi-step prediction result sequence into an oxygen dynamic control model, thereby enabling real-time control of the oxygen supply. This invention is applicable to the energy management system of converter steelmaking processes, achieving dynamic balance between oxygen production and consumption, minimizing emissions, improving energy utilization, and reducing external purchase costs. It features accurate prediction, fast response, and strong adaptability.

The application provides a kind of addressing matrix analysis method for multi-dimensional identification system, by the instruction of terminal input is disassembled into different components, combined into addressing information;Structured data based on multi-dimensional identification attribute, namely addressing matrix, is constructed;Terminal sends addressing request message to access routing device;The addressing request message is forwarded to regional server;K-d tree index is constructed;Using the pre-constructed k-d tree index, the terminal node coordinate C closest to the query point P in Euclidean distance is found;Match appropriate terminal node coordinate;After locking the target terminal through coordinate mapping and similarity matching algorithm, extract the key identifier as the analysis result of query;The method can significantly improve the positioning accuracy and query efficiency of terminal node, can significantly reduce the delay of data transmission, and provide faster response time.

This invention discloses a photovoltaic power generation prediction method based on multidimensional data analysis, specifically relating to the field of new energy power prediction technology. The method includes: multi-source data fusion and field construction: integrating multi-source heterogeneous meteorological data, and generating a spatiotemporally continuous comprehensive meteorological influence factor field through spatiotemporal alignment and dynamic weight fusion; adaptive scene matching prediction: performing multidimensional similarity matching between the current meteorological field sequence and a historical scene database, retrieving similar historical scenes, adaptively selecting and fine-tuning the prediction model online, and generating a preliminary power prediction sequence; and quantified uncertainty output: quantifying three types of uncertainty—input data, model selection, and real-time deviation—and fusing them using a Bayesian model averaging method. This invention improves the quality of prediction input data, enhances the adaptive prediction capability for complex weather, and provides prediction results with quantifiable uncertainty, effectively improving the accuracy and practicality of photovoltaic power prediction.

This invention discloses an AI-based intelligent question-answering method, device, electronic device, and product for games, relating to the field of intelligent question-answering technology. The AI-based intelligent question-answering method for games includes: identifying entity objects in game consultation text through part-of-speech tagging; performing similarity matching between the game consultation text and various question templates in a pre-built question template library to obtain a target question template with the highest matching degree; constructing a graph database query statement based on the question type corresponding to the target question template and the entity objects in the game consultation text; querying data from a pre-built graph database based on game knowledge using the graph database query statement; and generating a response text for the game consultation text based on the query results. The AI-based intelligent question-answering method, device, electronic device, and product disclosed in this invention ensure that the generated response content corresponds to the user's intended question, improving the accuracy of intelligent question-answering for games.

A method and system for optimizing ODN attenuation based on multi-parameter matching, relating to the field of electronic digital data processing, is disclosed. The method includes: reading multiple candidate topology schemes of the ODN network to be planned, generating a multi-dimensional parameter vector set, and performing similarity matching calculations with the parameter vectors of completed networks in a historical engineering database to determine a reference ODN network identifier; extracting real received optical power telemetry data based on the reference ODN network identifier to generate a real optical power dataset; reading original design data, calculating the theoretical estimated optical power of each optical network unit according to a preset standard attenuation linear formula to generate a theoretical optical power dataset; determining multi-parameter joint compensation coefficients, performing basic attenuation calculations on multiple candidate topology schemes based on the standard attenuation linear formula, and calculating corrected attenuation values; and determining the candidate topology scheme as the attenuation optimization scheme for the ODN network to be planned. Implementing this application can improve the accuracy of scheme optimization for actual optical distribution networks.

This invention provides an automated digital printing sample adjustment method and system, including a sample adjustment client that imports a preset pattern file to be printed and performs similarity matching calculations with a local process database or a cloud process database on a cloud server. The local process data and the cloud process database store historical process scenario data examples. The sample adjustment client retrieves examples that meet the similarity criteria, corrects the data, and sends it to the digital printing machine terminal. The digital printing machine terminal drives the digital printing machine to print and saves the process scenario data that meets the finished product effect criteria to the local or cloud process database. The cloud server also communicates remotely with service engineers to manually set process scenario parameters. By storing and managing the printing difference parameters of all digital printing equipment, when a customer adjusts a sample, the system automatically matches and retrieves similar historical examples and makes corrections, improving the sampling efficiency of digital printing plants.

This invention discloses an adaptive vehicle driving control method, system, and computer-readable storage medium based on scene feature matching. The method includes the following steps: real-time acquisition of traffic environment data around the vehicle; recording of the driver's active driving data in various driving scenarios; extraction of key environmental feature parameters in the driving scenarios to construct a scene-behavior mapping database; in autonomous driving mode, real-time calculation of the relative motion state vector of the current traffic environment and similarity matching with historical relative motion state vectors in the scene-behavior mapping database; if the similarity exceeds a preset confidence threshold, calling the active driving operation data corresponding to the historical vector to generate an initial adaptive control strategy and performing safety boundary verification; if successful, sending instructions to the vehicle actuators; if unsuccessful, correcting the initial adaptive control strategy or switching to a default safety control strategy.

This invention discloses a speech interruption decision-making method and system based on multi-granularity semantic integrity prediction, belonging to the field of speech interaction technology. The method includes: extracting multi-granularity semantic features and combining them into a current multi-granularity semantic feature vector; calculating the offset of the current multi-granularity semantic feature vector with a standard semantic pause model to obtain a semantic offset feature vector; performing similarity matching and weighted voting between the semantic offset feature vector and a historical interruption decision case library to obtain the current predicted interruption confidence; and generating an interruption command when the current predicted interruption confidence exceeds a dynamic threshold. This invention solves the problems of existing technologies where speech interruption decisions rely on simple energy thresholds or semantic integrity probabilities, lack utilization of user expression habits and contextual experience, and have low decision accuracy by introducing a standard semantic pause model and a historical case analogy reasoning mechanism, thus achieving more intelligent and accurate speech interruption judgment.

This invention provides a method, system, device, and medium for detecting missing process defects in panel color filters, relating to the field of panel missing process defect detection technology. The method flow is as follows: A matching template is obtained based on the original panel image, the matching template containing all color units; similarity matching is performed on the panel image to be detected based on the matching template to obtain several candidate templates; rectangular regions corresponding to all color units are obtained based on the candidate templates, and color difference comparison is performed based on the rectangular regions to determine whether a missing process defect exists. This invention combines template matching and color difference analysis to solve the problem of limited identification features for missing process defects in CF color filters, making it difficult for target detection algorithms to effectively detect them, thus achieving effective detection of missing process defects in CF filters.

The present application relates to the technical field of railway logistics operation and maintenance, and discloses a logistics intelligent management optimization method fusing multi-source data analysis, which comprises the following steps: obtaining business text and structured equipment monitoring data, combining train working diagram and passenger flow density parameters to extract fault action vocabulary; using train arrival and departure time alignment data to lock effective physical time window containing fault evolution; performing passenger flow load decoupling processing on monitoring data, using a baseline model to remove basic load to generate standard residual waveform; fusing building information model and logical network, constructing spatial logical index based on comprehensive proximity; performing cross-station similar equipment matching based on multi-dimensional working condition feature vector and generating maintenance report. Through effectively stripping the interference of passenger flow environmental noise on equipment monitoring data, combining spatial logical correlation and working condition similarity matching, the accuracy of fault feature extraction and the reuse efficiency of cross-site operation and maintenance knowledge are significantly improved.

The application discloses a knowledge base question answering method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a user query, extracting a structured query element corresponding to a preset query dimension; the preset query dimension at least comprises a domain keyword; based on the structured query element, searching in a preset knowledge base to obtain a candidate knowledge record set; the preset knowledge base comprises a plurality of knowledge records, and each knowledge record at least comprises an identifier field and a domain keyword field, and each identifier is associated with a semantic vector generated based on the content of the corresponding knowledge record; encoding the user query into a query vector, and performing similarity matching between the query vector and the semantic vector associated with the identifier of each knowledge record in the candidate knowledge record set; and filtering a target knowledge record set from the candidate knowledge record set according to the matching result, and generating an answer corresponding to the user query based on the target knowledge record set. Thus, the accuracy of the answer is improved.

This invention discloses a visualization report analysis method based on task discrimination and query generation. It receives user queries, generates a sequence of subtasks through task planning using a large language model, and evaluates and optimizes the subtask sequence using a task planning discriminator. For each subtask, after vectorization, similarity calculation is performed with a tool description vector library to obtain the top K tool descriptions, and the large language model further refines the selection to N tools. When a subtask involves a database query, similarity matching is performed based on a query example library to obtain query examples, which are then combined with table structure information to generate and execute a query statement. Finally, a visualization report is generated based on the subtask processing results. This invention effectively improves the accuracy of the large model in task decomposition, tool invocation, and query statement generation by introducing a task planning discriminator, vectorized tool recommendation technology, and dynamic query statement suggestion technology, thereby enhancing the execution effect of complex data queries.

This application provides a method and system for analyzing mobile game user behavior based on big data analytics, belonging to the field of big data analytics technology. The method includes: collecting massive amounts of historical touch operation data from mobile game users, performing time-series slicing and event alignment processing to construct a behavior sample library; constructing a statistical behavior baseline and a deep behavior pattern library based on the behavior sample library; collecting current user touch operation data in real time, generating the current time-series segment, comparing its deviation with the statistical behavior baseline, and performing similarity matching with the deep behavior pattern library to obtain deviation comparison results and similarity matching results; inputting the current time-series segment into a time-series prediction model to output predicted proficiency level and focus score; and fusing the deviation comparison results, similarity matching results, proficiency level prediction values, and focus score prediction values ​​to obtain the operation proficiency level and focus score. This improves the accuracy of mobile game user behavior analysis.

This invention discloses a finger vein recognition method and system based on deep metric learning and quality enhancement. The method includes: acquiring finger vein images and extracting regions of interest; using a Siamese network to learn the quality ranking relationship of image pairs, automatically evaluating image quality and filtering low-quality images; constructing an FV-FE-Net feature extraction network, training it under dual constraints of Euclidean distance and cosine angle using a joint loss function (triple loss + ArcFace loss), and extracting highly discriminative feature vectors; finally, identity authentication is completed through feature similarity matching. This invention eliminates the need for manual image quality annotation, effectively filters low-quality images, improves generalization ability and recognition accuracy in open-set recognition scenarios, and exhibits strong robustness and scalability, making it suitable for high-security identity authentication scenarios.

This application discloses a method for processing and recognizing image data from a scope, relating to the field of image data processing technology, including the following steps: S1, preprocessing the raw image data acquired by the scope, extracting the RGB values, grayscale values, position information, and gradient features of pixels to obtain preprocessed image data; S2, based on the preprocessed image data, establishing a dynamic background environment model by fusing pixel gradient features through multi-Gaussian distribution, comparing pixel features of newly acquired image data, and decomposing the image data into a background environment part and a suspected target part. This application, through dynamic background modeling, grayscale and contour multi-feature fusion, dual-criteria similarity matching, and trajectory verification mechanisms, can accurately distinguish targets from environmental interference under harsh conditions such as low light, dust, and complex mountain forest backgrounds, effectively filtering out isolated noise and background fluctuations, and significantly reducing the probability of misidentification and missed identification.

This invention discloses a software code optimization method and system based on big data. The method includes the following steps: constructing a code optimization knowledge base; acquiring the target code to be optimized and its corresponding estimated runtime data features; parsing the target code, extracting its structural features, and fusing the structural features with the estimated runtime data features to generate a target code fingerprint; performing similarity matching between the target code fingerprint and historical code fingerprints in the code optimization knowledge base to determine target historical code fingerprints that match the target code fingerprint; and determining a target optimization strategy for the target code based on the optimization strategy corresponding to the target historical code fingerprint. This invention can improve development efficiency, reducing the performance tuning work of senior architects, which can take hours or even days, to automated recommendations at the minute level, greatly improving software iteration efficiency.