76 results about "Field based" patented technology

This application discloses a master data integration method, apparatus, electronic device, and storage medium. The method includes: acquiring multi-source heterogeneous master data; standardizing and cleaning the multi-source heterogeneous master data to generate multiple block keys and inverted index lists, and constructing a candidate comparison set; extracting and normalizing the multi-level similarity of each pair of candidate records in the candidate comparison set, and constructing a standardized feature vector; inputting the standardized feature vector into a learning model to obtain the matching probability of each pair of candidate records, and making hierarchical decisions based on the matching probability and at least one matching threshold; constructing an undirected matching graph and generating entity clusters from the undirected matching graph; determining the data quality score of each field of each candidate record within the entity cluster, determining the optimal value of each field based on the data quality score, and generating the integrated master data. This application significantly reduces the number of comparisons, improves comparison efficiency, eliminates the need for manually writing matching rules, and can adapt to various data types and new data sources.

This application relates to the field of information technology, specifically to a natural language query method and system based on a low-code platform. The method includes the following steps: reading the creation context of a data table and fields on the low-code platform, and generating a related thesaurus of the data table and fields based on the creation context; receiving a natural language query statement input by a user, extracting the action words and predicate words of the natural language query statement to obtain the user's query intent; comparing the predicate words with the related thesaurus to obtain matching related words; replacing the corresponding predicate words with the matching related words, and generating an SQL query statement based on a pre-connected Text-to-SQL module; performing syntax and security checks, executing the SQL query statement to obtain query results; selecting a visualization component to load and display the query results according to the user's query intent, and changing the display method of the query results in response to user actions.

This invention discloses a method for aligning fields based on structured parsing of overseas open-source information, relating to the field of data fusion and parsing. The method includes: acquiring raw data packets from overseas open-source platforms; performing structured parsing and field extraction on the raw data packets to generate a candidate field set; performing semantic recognition and field mapping on the fields in the candidate field set based on a dynamic cognitive network to generate a field mapping decision result; resolving and correcting the consistency of conflicting field values ​​mapped to the same standard field based on the field mapping decision result to obtain an aligned field set; and organizing the aligned field set into a unified structured record and outputting it according to the standard field model. This method achieves intelligent mapping and conflict resolution of cross-platform fields through an evolvable semantic network, possessing the ability to adaptively learn unknown fields, achieve deep semantic understanding, and output interpretable decisions, significantly improving the intelligence level and accuracy of multi-source information fusion.

This specification discloses a method, apparatus, and device for identifying multimodal self-certifying materials. The scheme includes: acquiring image information corresponding to the self-certifying material and preprocessing the image information; determining the required key fields based on the material type corresponding to the self-certifying material; generating a corresponding number of cross-validation tasks for each key field based on the corresponding task window length and redundant validation coverage; independently executing each corresponding cross-validation task using multiple multimodal large models, outputting local recognition results for some key fields included in the cross-validation task; and fusing the local recognition results to obtain the overall recognition result for the key fields.

This application discloses a method, apparatus, and device for optimizing a large model targeting a specific vertical domain, belonging to the field of artificial intelligence. The method includes: acquiring a sample pool, which includes general domain data and vertical domain data; constructing current-round training data based on the sample pool, and training an initial large model based on the current-round training data to obtain a target large model; constructing test questions for the vertical domain data based on the technical standards of the target vertical domain; generating response results for the test questions using the target large model; determining domain knowledge blind spots from the vertical domain data based on the understanding of the technical standards based on the response results; updating the current-round training data based on the domain knowledge blind spots to obtain the next-round training data, and training the target large model again based on the updated next-round training data.

The application discloses an automatic driving behavior decision-making method based on double heuristic tree search, and belongs to the technical field of automatic driving.The method is as follows: actions are abstracted as a combination of lateral lane-changing decision and longitudinal acceleration-deceleration decision, a decision time domain and a decision tree depth are set, and an initial behavior decision tree is constructed; a heuristic search strategy is designed by fusing field knowledge priori and data-driven priori, a reference action sequence is generated to guide the search process; a decision tree pruning mechanism based on field knowledge is proposed, and the tree structure is dynamically reconstructed with the last period optimal decision as a root node; the comprehensive cost of the candidate decision sequence after pruning is evaluated, and the sequence with the minimum cost is selected as the optimal decision sequence.The application effectively solves the technical problems of high computational complexity, poor real-time performance and insufficient decision rationality of traditional methods in a long decision time domain by constructing a semantic action decision tree and fusing a double heuristic guide and a field knowledge pruning mechanism.

Embodiments of the present application disclose a kind of group adaptive integrated control method, device, electronic equipment and storage medium, involve embodied intelligent technical field, wherein, the method includes: according to target scene characteristic, utilize physical modeling and domain randomization technology to generate diversified environment task set, and pre-processing is carried out to ensure data quality, train reinforcement learning coach based on these tasks, combine decoupling and backtracking policy distillation technology to synthesize training sequence, enhance the generalization and adaptive ability of model, adopt long-time memory model structure design base model, integrate multi-agent observation module to capture time sequence and spatial correlation, dynamic noise injection and asynchronous optimization are carried out in training process, the trained field base model is deployed to target scene, form collaborative network, and set fault-tolerant mechanism to deal with agent offline and other sudden situations, continuously collect actual data to optimize model parameters.The present application effectively solves the problems of high customization, weak migration and high maintenance cost in the prior art.

Embodiments of the application disclose a multi-modal knowledge graph construction method and device, equipment and a medium; embodiments of the application can acquire multi-modal data of a target field, and construct a field ontology based on the multi-modal data; based on the field ontology, target entities, attribute values contained in the target entities and relationships between the target entities are extracted from the multi-modal data to obtain a plurality of relationship triplets and attribute triplets; the attribute triplets comprise target entities, attribute types and attribute values, the attribute types comprise specific attributes, and the attribute values of the specific attributes are feature vectors of non-text modal data corresponding to the target entities; based on the plurality of relationship triplets and the attribute triplets, a knowledge graph is constructed. Thus, by assigning the features of non-text modal data as string values to the corresponding specific attributes of the nodes, multi-modal data can be effectively fused and utilized, and a knowledge graph with higher integrity, accuracy and practicality can be constructed.

To provide a work vehicle that can prevent a decrease in work accuracy, etc., even if a malfunction occurs in the positioning device during autonomous driving. [Solution] The above problem is solved by a work vehicle 1 configured to be able to drive automatically in a field, comprising: a shooting device that acquires field image data by shooting the area in front of the work vehicle; an uncultivated area extraction unit that extracts uncultivated areas from the field image data; a cultivated area extraction unit that extracts cultivated areas; a boundary line calculation unit that calculates the boundary line between uncultivated and cultivated areas of the field based on the extracted uncultivated and cultivated areas; a boundary line analysis unit 57 that analyzes the boundary line calculated by the boundary line calculation unit; and a boundary line information recording unit that records the analysis information regarding the boundary line from the boundary line analysis unit as boundary line recording information; and a driving means that automatically steers the work vehicle during automatic driving based on the field image data and boundary line recording information acquired by the shooting device.

This invention relates to the field of machine learning technology, and discloses a method and system for training a large-scale medical language model based on knowledge graph enhancement. The method includes: acquiring a medical corpus and knowledge graph; generating entity sequences through fine-grained semantic parsing; extracting multi-hop subgraphs through multi-dimensional association path reasoning; dynamically injecting text into the graph based on dynamic weights to generate enhanced training samples; parsing and encoding into a standardized instruction set; and iteratively optimizing to obtain the target model. This invention improves the training efficiency and professional reasoning capabilities of a large-scale medical language model through adaptive knowledge fusion and standardized instruction encoding.

This invention discloses a method and system for dynamically visualizing topic numerical fields based on the ROS2 system. It enumerates all active topics in the ROS2 system; performs static field recursive parsing on the message type of the user-selected topic to obtain a set of candidate numerical field paths; and marks fields containing key-value pair sub-message arrays as runtime placeholders. Based on the first arriving message, it performs dynamic field scanning, generating unique identifiers by array index and element name; applies a regular expression numerical extraction algorithm to the string values ​​in the key-value pairs to discover the visual numerical fields hidden within the strings; and extracts values ​​from each arriving message according to the user-selected fields, transmitting them to the graphical interface thread for real-time plotting in the form of an automatically scrolling time window curve. This invention solves the problems of existing visualization tools failing to automatically discover complex nested messages and hidden numerical fields, and the loss of user interaction status in scenarios with frequent refreshes of the topic list.

Methods, systems, and devices are described for wireless communication. A user equipment (UE) can transmit channel state information to a network entity, where the channel state information indicates a first precoding matrix index for a first antenna panel of a set of antenna panels of the network entity and a second precoding matrix index for a second antenna panel of the set of antenna panels, and where the second precoding matrix index is offset from the first precoding matrix index according to an angular parameter associated with an angular separation between the first antenna panel and the second antenna panel relative to the UE. The UE can receive a message from the network entity according to the channel state information.

This invention discloses a field search method, electronic device, medium, and program based on alarm information. The method includes: responding to a dropdown query list trigger request for a target field, obtaining alarm field association information for the target field; calculating a multi-dimensional alarm association score for each field value of the target field based on the alarm field association information; sorting each field value of the target field according to the multi-dimensional alarm association score; and displaying the sorting results of each field value in the dropdown query list of the target field. The technical solution of this invention can improve the efficiency and accuracy of querying and searching for abnormal field values.

This invention discloses a field search method, device, medium, and program based on time trend information. The method includes: in response to a dropdown query list trigger request for a target field, obtaining time feature association information of the target field; calculating a time trend pattern score for each field value of the target field based on the time feature association information; sorting each field value of the target field according to the time trend pattern score; and displaying the sorting results of each field value in the dropdown query list of the target field. The technical solution of this invention can improve the efficiency and accuracy of querying and searching field values ​​with regular changes.

This invention relates to the field of meteorological forecasting technology, and more particularly to a meteorological forecasting system based on a geographic prior enhancement and differential constraint attention mechanism. The system includes: a data acquisition module to construct a training dataset; a model construction module to construct a meteorological forecasting model containing geographic prior enhancement attention units, multi-scale feature preservation units, and differential constraint units; a geographic prior attention calculation module to obtain geographically sensed encoded features by injecting latitudinal weights and latitude-longitude anisotropy biases; a multi-scale feature fusion module to perform multi-scale downsampling of historical data and gating fusion with the encoded features to obtain decoded features; a prediction field generation module to generate a predicted meteorological field based on the decoded features; a model training module to construct a total loss function and iteratively train the model using content loss and spatial gradient loss; and a real-time prediction module to input real-time data into the trained model to generate meteorological forecast results. This invention improves the intensity prediction accuracy and physical consistency of extreme weather systems through geographic prior injection and gradient constraints.

This application relates to a spatial downscaling method for meteorological element fields based on a retrieval and diffusion generation model. This method generates corresponding high-resolution meteorological element fields from low-resolution meteorological element field sequence samples. By constructing a retrieval mechanism, a high-resolution reference meteorological element field related to the current input sample is obtained from a historical high-resolution meteorological element field database. The target high-resolution meteorological element field is then progressively reconstructed using a diffusion generation process. Simultaneously, physical consistency constraints are introduced to achieve spatial downscaling of the meteorological element field while balancing generation quality and physical plausibility, thus improving the refinement, stability, and physical plausibility of the spatial downscaling results. This method is applicable to various meteorological element fields, multi-source meteorological data, and various complex regional scenarios. It has strong scalability and application value, and can be used for refined weather forecasting, meteorological analysis of complex terrain, monitoring and early warning of severe weather, aviation meteorological support, and related intelligent meteorological operational scenarios.

A computer system may be programmed to: (1) receive a first home inspection report associated with a first home; (2) extract, using an artificial intelligence model, home data from the first home inspection report, the artificial intelligence model including extraction tools and trained using correlations between historical home inspection reports and historical home data; (3) store the extracted home data for the first home in a data structure including a plurality of data fields; (4) identify at least one data field of the plurality of data fields that is missing a data value; (5) generate, using the artificial intelligence model, at least one predicted data value for the identified at least one data field based upon the historical home data; and / or (6) store the at least one predicted data value in the identified at least one data field.

This invention provides a probabilistic model compilation system and method for the AI ​​field based on multi-level intermediate representations, comprising: a front-end conversion layer: taking the model described in Python as input, traversing the abstract syntax tree to map the operation nodes to operation nodes in the MLIR dialect and outputting them; a compilation layer: taking the IR represented in the MLIR dialect as input, decomposing, downgrading, and optimizing the operations; and a back-end layer: integrating two back-ends, LLVM JIT and IREE, receiving the final form of the IR as input, generating corresponding code according to the target platform, and performing calculations. This invention's probabilistic model compilation method based on multi-level intermediate representations uses static univariate assignment as the intermediate representation result for compiling and running probabilistic programming code, converting it into corresponding back-end code according to front-end configuration requirements, thus increasing the portability of the probabilistic model.

The application provides a large model-based vertical field data construction method, and belongs to the technical fields of data processing and artificial intelligence, and comprises the following steps: converting a vertical field source document into an intermediate format text and dividing the intermediate format text into multiple text blocks; inputting the text blocks into a pre-trained generative language model, guiding the pre-trained generative language model to generate a plurality of candidate questions according to the contents of the text blocks according to a pre-designed prompt word, and performing preliminary screening and fine screening on each candidate question to obtain a question set; predefining a mode of a knowledge graph according to the field characteristics of the vertical field, processing all the text blocks based on an information extraction model, and constructing a field knowledge graph; and performing local context retrieval based on the text blocks of the source of each final question in the question set, performing global knowledge retrieval based on the field knowledge graph, and generating a final answer and a final thinking chain. The application is suitable for different vertical fields, and can effectively improve the quality of data and ensure the accuracy of question generation.

This invention discloses a method for dynamic reconstruction and monitoring of unsteady flow fields based on sparse measurement points. The method first acquires snapshot data of physical quantities of the target flow field at continuous time steps; selects a small number of snapshots and extracts a reference frequency set through dynamic mode decomposition (DMD); forms a candidate measurement point set through high-order moment feature construction and K-means clustering; performs DMD fine screening on the candidate measurement point combination based on frequency domain consistency constraints to determine the optimal sparse measurement point set; constructs a measurement matrix to achieve sparse observation, and combines compressed dynamic mode decomposition (cDMD) to complete the full-field flow field reconstruction and time-domain evolution monitoring. This invention achieves robust capture of dominant dynamic frequencies with very few observation channels, reduces sensing costs and computational load, and improves the stability and real-time performance of reconstruction under complex conditions. It is applicable to flow field monitoring needs in aerospace, marine observation, and other fields.

This invention discloses a quantitative method for the dynamic consistency of temperature field based on thermal field analysis. Temperature measurement points are set up upstream and downstream of the filter. During the isothermal stage, a set disturbance is applied and multiple temperature sequences are collected. The preprocessed temperature data is obtained after detrending and bandpass filtering. Frequency domain analysis is used to calculate the average phase value of the upstream and downstream temperature sequences within a preset frequency band, and the results are grouped into the principal value region to form a downstream phase set. Based on this set, the absolute value of the phase mean and circular statistical parameters are obtained. By calculating the complementary value of the absolute value of the phase mean and the exponential decay result of the circular statistical parameters, a comprehensive score reflecting the temperature uniformity of the extinguishing effect is obtained, thus achieving a quantitative evaluation of the dynamic consistency of the extinguishing temperature field.

This invention discloses a collaborative sensing asynchronous feature alignment method and system, relating to the field of collaborative sensing technology. The method includes: acquiring a sequence of historical feature maps of collaborative vehicles and calculating the time delay information of each frame of the feature map relative to the current moment; mapping the time delay information to a time embedding vector and performing frame-by-frame correction of the sequence through time-aware feature modulation; constructing a continuous-time state-space model, dynamically adjusting the state decay coefficient based on the physical time difference to achieve temporal feature aggregation under non-uniform delay, and obtaining the hidden state features at the current moment; using a hybrid spatial gating module to extract motion features and static background features in parallel, and generating spatially corrected features through gating fusion; predicting the offset field based on a multi-scale strategy for feature resampling, and outputting the final aligned features through an artifact repair module. Through continuous-time modeling, motion-static separation correction, and multi-scale alignment, the accuracy and robustness of asynchronous collaborative sensing are effectively improved.

This invention provides a data spatial query method, apparatus, electronic device, and computer-readable storage medium. The data spatial query method provided by this invention includes: acquiring target business data; constructing a spatial field based on the latitude and longitude data of the target business data; importing the spatial field into a preset index; acquiring the latitude and longitude data of two diagonal vertices within a visualized map area; determining a data query range based on the latitude and longitude data of the two diagonal vertices; acquiring a geographic grid based on the data query range and the shrinkage ratio of the visualized map; and aggregating and statistically analyzing the target business data within the geographic grid area based on the spatial field to obtain query results. The data spatial query method provided by this invention can aggregate points on a large number of maps and respond promptly to the aggregation.

An imaging system usable with an agricultural operations vehicle as the agricultural operations vehicle moves through a field includes a stereoscopic multispectral imaging sensor configured to capture images of the field in real time; a processor; and a memory. The memory includes instructions, stored thereon, which when executed by the processor cause the imaging system to: capture a real-time image by the stereoscopic multispectral imaging sensor; determine characteristics of field elements within the field based on the real-time image, wherein one of the determined characteristics of the field elements is a vegetation index; determine a morphology of the field in which the agricultural operations vehicle is moving based on the captured real-time image; combine as data the real-time image, the determined characteristics of the detected field elements, and the determined field morphology; and determine a location of the detected field elements based on the combined data.

This invention discloses a high-speed sparse flow field prediction method and system based on a masked autoencoder, belonging to the interdisciplinary field of hypersonic aerodynamics and artificial intelligence. The invention mainly includes: constructing a cross-basin multi-scale flow field database; constructing and pre-training a multi-scale masked autoencoder model, forcing the model to learn to reconstruct the entire flow field from sparse information through a random masking strategy; introducing physical information constraints to fine-tune the model, including Chapman-Enskog distribution function constraints, moment equation conservation residuals, and wall Maxwell slip boundary conditions; introducing a Knudsen number adaptive inference mechanism, automatically adjusting feature weights through a gating network; and using the trained model for flow field prediction. This invention achieves unified and rapid cross-basin prediction covering a wide range of Knudsen numbers, significantly improving computational efficiency while ensuring prediction accuracy, and possessing good physical consistency and generalization ability.

This invention discloses a method, apparatus, device, medium, and program for field search based on business information. The method includes: responding to a dropdown query list trigger request for a target field, obtaining business data association information of the target field; calculating a business importance score for each field value of the target field based on the business data association information; sorting the field values ​​of the target field according to the business importance scores; and displaying the sorting results of each field value in the dropdown query list of the target field. The technical solution of this invention can improve the efficiency and accuracy of querying and searching key business field values.

The application discloses a kind of positioning of long-distance magnetic target and its design method, belong to the target positioning technical field based on magnetic field.It includes: S100, the position coordinates and magnetic moment of magnetic interference source are inverted using short baseline magnetic detection system, then real-time stripping interference magnetic field generated by magnetic interference source at long baseline magnetic detection system using inversion result, finally realize long-distance magnetic target positioning using long baseline magnetic detection system, obtain the magnetic moment vector m2 of magnetic target;S200, according to actual working condition and detection demand, the design method of each parameter of magnetic detection system is proposed in combination with the magnetic moment vector m2.The application uses short baseline magnetic detection system to real-time strip platform magnetic interference, and realizes long-distance magnetic target positioning using long baseline magnetic detection system.

The application discloses a visible light remote sensing image thin cloud correction method, comprising the following steps: obtaining a to-be-corrected thin cloud image and a cloud-free reference image, and pre-processing the two images; constructing a difference field based on the pre-processed to-be-corrected thin cloud image and the cloud-free reference image, independently analyzing the difference field data, and obtaining a plurality of independent components and a mixing coefficient matrix; calculating the low-frequency energy proportion of each independent component, identifying a thin cloud independent component according to the low-frequency energy proportion, and extracting a cross-band coefficient vector corresponding to the thin cloud independent component from the mixing coefficient matrix; performing thin cloud stripping processing on the to-be-corrected thin cloud image based on the cross-band coefficient vector, and obtaining a cloud-free clear image after thin cloud correction. The application effectively solves the problems of image blurring and ground information distortion caused by thin clouds, significantly improves the clarity and usability of thin cloud images, and improves the quality and application value of remote sensing images.

This invention provides an object recognition method, apparatus, device, storage medium, and program product, relating to the field of data processing technology. The method includes: acquiring image data and first voice data of an object to be recognized, wherein the first voice data describes a target field in the object to be recognized; recognizing a first field value of the target field based on the image data, and a first confidence level corresponding to the first field value; recognizing a second field value of the target field based on the first voice data, and a second confidence level corresponding to the second field value; and generating a third field value of the target field based on the first field value, the first confidence level, the second field value, and the second confidence level. This invention can improve the accuracy of field recognition on invoices.