72 results about "Dynamic field" patented technology

The invention belongs to the technical field of data processing, and discloses a multi-modal project data analysis method, which comprises the following steps: collecting heterogeneous modal project data, carrying out denoising and timestamp correction on each modal project data based on an adaptive multi-scale filtering technology, carrying out cross-modal time alignment, and outputting a multi-modal signal. Constructing a multi-level Boltzmann machine energy network, and modeling the joint probability distribution of the multi-modal signals; a dynamic complexity measurement mechanism based on topological entropy is designed and used for representing project structure complexity, and a topological entropy dynamic field is generated; the topological entropy dynamic field is used as a constraint condition, a multi-dimensional covariant field frame is used, nonlinear coupling and space-time propagation between multi-modal signals are simulated, the multi-modal signals are abstracted into a string vibration mode, local topological defects in the topological entropy dynamic field are recognized, and an abnormal fluctuation map is generated; and the analysis of the complex multi-modal data in the project operation process is more intelligent and controllable.

The invention relates to the technical field of mineral resource exploration. The prospecting method, device and equipment based on the multi-source geological relation data and the medium are provided, the method comprises the steps that space-time alignment and standardization processing are conducted on obtained geological historical evolution data, geophysical field data, geochemical migration data and remote sensing alteration information, and a dynamic knowledge graph is generated; performing mineralization stage division processing on the geological historical evolution data to obtain a mineralization stage division result; integrating the fluid migration space-time path network, performing three-dimensional dynamic modeling processing, and generating a staged three-dimensional metallogenic evolution model; extracting a stage-specific geological mark combination from the staged three-dimensional metallogenic evolution model, performing knowledge reasoning processing based on a preset historical ore deposit rule base, and outputting an ore prospecting target region and a metallogenic process constraint basis which meet a preset confidence coefficient condition, so as to improve the precision of a structural model, generate a staged fluid dynamic field, and improve the precision of the metallogenic process. And the target region prediction confidence is enhanced.

The present invention discloses a policy traceability dynamic retrieval method based on multi-level intent recognition and comparative learning, which involves the fields of natural language processing, information retrieval and generation technology, and introduces multi-level intent recognition, dynamic field classification, embedded multi-round retrieval, comparative learning mechanism and generation optimization strategy. The present invention can accurately capture query intent, dynamically select the most relevant knowledge base, and generate high-precision traceability results through multi-level verification and optimization, significantly improving the accuracy, relevance and added value of retrieval, and meeting the high-precision scenario requirements such as complex policy tracing and compliance inspection.

The invention discloses a cross-system service data processing method, device and equipment, a medium and a product. The cross-system business data processing method comprises the following steps: establishing a dynamic field mapping relationship between an integration layer and a plurality of target business systems; extracting capital construction business data from the target business system through the integration layer according to the dynamic field mapping relationship, and performing standardization processing to obtain standard business data; aiming at each stage of the capital construction project, constructing corresponding index data to obtain an index system; on the basis of an index system, index penetration query is carried out on standard business data, and a linkage management and control mechanism of an index abnormal item and an infrastructure project three-dimensional model is established; on the basis of the multiple access roles, corresponding visual billboards are distributed, and the visual billboards support index display; and based on a preset data quality rule base, performing quality evaluation on the standard business data, and identifying data abnormal items. According to the technical scheme provided by the embodiment of the invention, integrated management and control of cross-system business data are realized.

The invention relates to the technical field of port storage yard cargo management and distribution, in particular to a port cargo allocation management and optimal distribution method and system. The method comprises the steps of generating an initial storage yard dynamic field graph based on a GIS technology in combination with storage yard operation data; updating and correcting the dynamic field graph in real time; carrying out candidate filtering on the goods allocation to obtain a candidate goods allocation set; a multi-objective optimization model is constructed, an optimization algorithm is called within a preset time limit for solving, and the distribution relation between the goods and the goods locations is generated; generating an operation instruction according to the distribution relation, issuing the operation instruction to the field terminal, and updating the dynamic field graph; when a trigger event occurs, only the affected cargo subsets are modeled and solved again, and the distribution result is updated in a minimum disturbance mode. By means of the scheme, dynamic visualization, scientific optimization distribution and event-driven rapid adjustment of the goods allocation state are achieved, the storage yard utilization rate can be effectively increased, the goods carrying frequency is reduced, and the operation efficiency and the intelligent level of the system are improved.

The invention discloses an unmanned aerial vehicle path planning method, device and equipment and an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle flight control. Extracting risk description features from the environment image, calculating a first maximum cosine similarity between the risk description features and text features of a dynamic field semantic tag library, and outputting semantic tags and confidence; when the confidence meets a confidence constraint condition, projecting the semantic tag to a three-dimensional voxel space, and generating a three-dimensional risk map with a risk weight; constructing a target cost function associated with the risk weight; and by taking minimization of the target cost function as a target, searching an optimal flight path from the starting point to the target point in the three-dimensional risk map. The sensing generalization of the unmanned aerial vehicle in a complex low-altitude environment can be improved, and the obstacle recognition accuracy and the flight safety are improved.

The invention relates to a cross-size wind tunnel Mach number prediction method based on adversarial field self-adaption, and relates to the technical field of hydrodynamic testing and artificial intelligence crossing. The method comprises the steps of performing time sequence dynamic feature enhancement on source domain and target domain data, constructing an adversarial time sequence feature alignment network, and performing time sequence feature alignment; comprising the steps that a bidirectional time sequence encoder captures bidirectional time dependence of a control quantity sequence; the dynamic domain discriminator identifies the dynamic difference of the cross-size wind tunnel control response; a gradient inversion layer is inserted between the bidirectional time sequence encoder and the dynamic field discriminator, a gradient inversion confrontation mechanism is formed, and the dynamic field discriminator gradient is multiplied by confrontation strength during training, so that the encoder is forced to generate field-independent universal features; a small sample layering fine tuning strategy is introduced, and aligned features are predicted through a predictor; and under the condition that the target domain data volume is remarkably reduced, the prediction precision is greatly improved compared with a traditional model, and the data acquisition cost and time consumption of the large-size wind tunnel are remarkably reduced.

The present application belongs to the technical field of data processing, and discloses a multi-modal project data analysis method, which comprises the following steps: collecting heterogeneous modal project data; based on adaptive multi-scale filtering technology, denoising and timestamp correction are performed on each modal project data, and cross-modal time alignment is performed, and a multi-modal signal is output; a multi-level Boltzmann machine energy network is constructed, and a joint probability distribution of the multi-modal signal is modeled; a dynamic complexity measurement mechanism based on topological entropy is designed, which is used for representing project structure complexity, and a topological entropy dynamic field is generated; the topological entropy dynamic field is used as a constraint condition, a multi-dimensional covariant field framework is used, nonlinear coupling and space-time propagation among the multi-modal signals are simulated, the multi-modal signals are abstracted into string vibration modes, local topological defects in the topological entropy dynamic field are identified, and an abnormal fluctuation atlas is generated; and the analysis of complex multi-modal data in the project running process is more intelligent and controllable.

The application relates to the technical field of data processing, and provides an excel-based automatic testing method and device, electronic equipment and a computer readable storage medium, wherein the method comprises the following steps: sending a target user query request; when receiving return information with a target user name, extracting a user report corresponding to the target user name in a preset baffle library according to the target user name, wherein the user report is in an xml format; formatting the user report in the xml format into a user report in a json object format; combining the user report in the json object format with solid fields and dynamic fields in an expected test result of a test case read from a preset excel table to form a standard test result; comparing the standard test result with a pre-acquired actual test result; and generating an automatic test report according to a comparison result. The main purpose of the application is to compare the generated standard test result with the pre-acquired actual test result to generate a test report, so that the test efficiency is improved.

Embodiments provide techniques for emitting structured and dynamic fields from an accelerated data model. The method comprises evaluating a query to search a data model, wherein the data model is defined by a set of events and at least one structured field from fields associated with the set of events. A summarization table is associated with the data model and comprises a plurality of entries comprising reference values, wherein a respective summarization table entry comprises: the at least one structured field; a respective field value; and a reference value. The method further comprises accessing the set of events from the field searchable data store using the reference values in the summarization table and annotating the set of events with the at least one structured field and with at least one dynamic field from the fields associated with the set of events.

The application relates to the technical field of satellite data processing, and provides a satellite data simulation generation method, system, medium and equipment, which comprises the following steps: parsing an XML configuration file used for defining satellite transmission frames, virtual channel data units, user frames / space packets and load fields to obtain a memory protocol object tree; recursively traversing the memory protocol object tree according to an output period to generate data frames of each layer, writing a configuration value into a fixed value field, increasing a count field by a step, converting a time field into a time code specified by a satellite protocol, continuously intercepting real load data according to a file offset modulo and a tail wrap mode for an external data field, recursively assembling a nested subframe after inheriting a parent frame context, and performing length alignment, check sum output. The protocol structure, dynamic fields and real load injection rules of satellite simulation data are configured, which is different from a scheme only facing communication coding and decoding or protocol packet assembly and analysis, and can generate continuous and high-fidelity satellite simulation data streams.

The invention discloses a large model optimization method based on multi-round diagnosis and treatment experience learning. The method comprises the steps that variable-length multi-modal time sequence modeling and unified embedded representation learning are carried out on dynamic domain experience through a heterogeneous tense multi-graph expression model; the disease course evolution is constructed into a heterogeneous, multi-modal, multi-scale and uncertainty weighted signal graph network cluster with a time sequence concept; carrying out strategic random walk resampling with a time concept on the network cluster; and performing large model optimization according to the sampling and multi-round diagnosis and treatment experience. According to the method, through a multi-modal domain experience unified representation modeling technology based on heterogeneous multi-graph progressive embedding learning, higher-quality feature expression is learned from multi-modal input data.

The present application belongs to the technical field of tracking model test, and specifically discloses a kind of single target tracking model test evaluation method, system, terminal and medium, comprising: deploying single target tracking model to be evaluated in field test environment;Obtain the tracking box information of model on continuous image frame, including target pixel center coordinates, size parameters and time stamp;Tracking box information is structured and processed, and continuous tracking result sequence is formed;Based on the sequence, a multi-dimensional performance evaluation system is constructed;Each index is normalized, and weighted fusion is obtained according to the experience weight, and the comprehensive performance score is obtained.The evaluation method does not need to rely on test set label, can truly reflect the tracking performance of model in dynamic field environment, realize the comprehensive quantitative evaluation of model stability, smoothness, robustness and real-time response ability, improve the objectivity, engineering adaptability and automation level of model test.

Multi-tenancy system to perform tactical and permanent database and communication operations including secure handling of personally identifiable and / or health information (PII / PHI), data collection, data management, reporting, data analytics, secure communications, document sharing and microservices (e.g., capturing biomarkers, determining presence of certain conditions by comparing captured biomarkers to biometrics associated with condition). System includes security platform meeting stringent data protection mandates including firewall with extensive security protocols, encrypting communications between components of system (in transit) and information within each of the components (at rest). PII / PHI information is further encrypted and only visible with appropriate decryption key. System utilizes low code / no code database platform to address increasing demand for rapid, iterative and collaborative application development. System includes form builder to easily add dynamic fields. System includes a collaborative database development with a community structure approach of “who” data is needed from rather than “what” data is needed. Community structure controls operation thereof.

Embodiments of the present disclosure provide techniques for emitting structured and dynamic fields from an accelerated data model. The method comprises evaluating a query to search a data model, wherein the data model is defined by a set of events and at least one structured field from fields associated with the set of events. Each event comprises a time-stamped portion of raw machine data and is stored in a field searchable data store. A summarization table is associated with the data model and comprises a plurality of entries comprising reference values, wherein a respective summarization table entry comprises: the at least one structured field; a respective field value; and a reference value. The method further comprises accessing the set of events from the field searchable data store using the reference values in the summarization table and annotating the set of events with the at least one structured field and with at least one dynamic field from the fields associated with the set of events, wherein the at least one dynamic field is not defined in the data model.

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.

This application relates to the field of data processing technology and discloses an integrated sky-ground geological environment monitoring and assessment method and system. The method includes: integrating sky remote sensing, surface monitoring, and underground exploration data into a monitoring matrix, processing the data to generate a raw database; constructing a spatiotemporal standard field based on the database and fusing it to generate a correlation spectrum; decomposing the correlation spectrum to obtain element feature chains; constructing a coupled dynamic field based on the feature chains and analytically obtaining an evolutionary parameter set; establishing a risk assessment matrix based on the parameter set and analyzing to generate an early warning indicator system; and designing a governance plan by combining the early warning system and historical cases. This application achieves deep integration of space-based remote sensing data, surface monitoring data, and underground exploration data by constructing a unified spatiotemporal standard field, a multi-level feature transfer network, and a dynamic coupling model, thereby improving the accuracy and reliability of geological environment monitoring and assessment.

This application discloses a data processing method, apparatus, and storage medium based on dynamic resource adaptation, relating to the field of data processing technology. The method includes: accessing rule execution result data under different rule development modes through a pre-configured unified data service registration interface; obtaining business source fields and establishing a mapping relationship between them and preset physical storage fields in the database using a dynamic field mapping algorithm. This algorithm allocates target physical fields based on the physical field resource pool status, combined with the business field type and length characteristics, while ensuring the continuity of historical data; initiating a rule trial run early warning process, calling the summary data query service, and intercepting anomalies in the summary record data according to monitoring thresholds; and dynamically generating rule execution task packages based on the data volume when no interception is triggered, calling the detailed data query service to obtain, parse, and display the data. This achieves efficient data adaptation and stable system operation in complex environments.

This invention discloses a data management and control system for the entire production process of silicone rubber products based on digital twins, belonging to the field of silicone rubber production management and control technology. It includes a data acquisition module, a twin construction module, a simulation driving module, and a quality field module. The data acquisition module collects real-time physical data of the entire production chain of silicone rubber products from raw materials to finished products. The twin construction module establishes a virtual digital twin of the physical production line. The simulation driving module injects real-time production data into the twin and drives synchronous simulation to generate a sequence of state parameters. The quality field module performs dynamic field analysis on the state parameter sequence, constructs an adaptive mesh topology that dynamically deforms with the parameters, and generates dynamic quality streamlines representing the quality transfer path between the topology nodes. This system realizes synchronous simulation of the entire silicone rubber production process and digital representation of the quality transfer process.

The invention relates to the technical field of data processing, in particular to a bill merging method and system based on text generation immutable codes, and the method comprises the following steps: in a Spring framework, defining fields participating in merging in a bill table by means of a configuration file, specifically including a cloud center, an order code, a resource id and resource configuration, resource configuration is definitely set as a key dynamic field, and configuration information is stored in a micro-service configuration center; connecting a MySQL database by using a Java data access layer, acquiring the defined field value, and performing format unification preprocessing operation on the acquired field value so as to ensure the accuracy of the current value of the resource configuration field; the method has the beneficial effects that the generated codes are based on the field values including the resource configuration, and when fields such as the resource configuration are adjusted, the codes change accordingly, so that the codes can accurately reflect the current field state, and the problem of inaccurate merging time caused by field change is avoided.

The invention discloses a data processing method, device and equipment and a computer readable storage medium, which are applied to the technical field of data processing, and comprise the following steps: receiving a business object type submitted by a user through a configuration page; determining database table information corresponding to each business object type; based on the data processing information, utilizing an analyzer to generate a structured statement, and utilizing a database adaptation method to generate a target data processing statement corresponding to the current database; the analyzer is a component for automatically generating a structured query language; and processing each business object type and the database table information corresponding to the business object type by utilizing the target data processing statement. Compared with the situation that dynamic field management, multi-data type support and cross-database compatibility cannot be met at the same time at present, the method has the advantages that the structured statement can be directly generated through the analyzer, the target data processing statement corresponding to the current database is generated through the database adaptation method, all databases can be adapted, and the data processing efficiency is improved. Therefore, the data processing efficiency is improved.

The invention relates to the technical field of testing interface boards, and discloses an optimized wiring method for testing the signal integrity of an interface board. Comprising the following steps of test interface board TIB layout pre-analysis and forced coupling channel determination, forced coupling channel region multi-layer parameterization modeling, forced coupling channel bearing bus data coding mode and weight acquisition, dynamic field calculation and parameterization crosstalk model construction, field phase collaborative optimization and test interface board physical wiring implementation. According to the method, physical geometry and time delay control parameters are generated through S2 multi-layer parameterized modeling, S4, a dynamic field solver is driven to calculate a coupling matrix in real time and construct a parameterized crosstalk model in combination with a data coding mode and weight extracted in S3, then S5, the model is called to start a global optimization algorithm, the physical geometry and time delay parameters are synchronously adjusted, and therefore the crosstalk performance is improved. The algorithm linkage of parameter modeling, field resolving, model building and collaborative optimization is realized, and the traditional crosstalk control limitation only depending on geometric spacing is broken through.

System and techniques may be adapted for use in composite field sequencing for proton therapy. A technique may include generating a proton therapy plan in a treatment planning system, the proton therapy plan including a plurality of static fields. The technique may include creating a single data file of a single dynamic field representing the plurality of static fields. The single data file may be sent to a proton therapy system for delivery of the single dynamic field. The technique may include receiving a response information related to a dose delivered to a patient by the single dynamic field.

The invention relates to the technical field of railway engineering line selection design, and discloses a complex environment railway intelligent line selection gravitational field dynamic modeling and self-adaptive guiding optimization method. The method comprises the following steps: constructing a multi-criterion index system, establishing an adaptation degree space field hierarchical model, and identifying high and low adaptation environment patches by using a DBSCAN density clustering algorithm; constructing an intelligent line selection environment static field model; a kinetic equation of gravitational propagation is established and solved, and intelligent line selection environment dynamic field modeling is achieved; and a Transform neural network model is introduced, gravitational field feature situation awareness is completed, a dynamic adaptive alignment method is put forward, and an optimal line scheme for railway line selection is output. According to the method, by constructing a line selection environment adaptation degree space field and converting the line selection environment adaptation degree space field into a gravitational field and combining dynamic evolution mechanism analysis and a self-adaptive oriented intelligent search strategy, efficient optimization design of a railway line in a dense constraint environment is achieved, the strain capacity of a line determination decision is improved, and the line selection efficiency is improved. And the dynamic optimization requirement of engineering line selection in a complex environment can be met.

The invention relates to the technical field of deformation research of an atomic system, and particularly provides an atomic strain calculation method based on a dynamic neighborhood and a deformation gradient tensor, and the method comprises the steps: determining a region in which atomic strain needs to be calculated; constructing a dynamic field; and constructing a deformation gradient tensor to calculate an atomic strain tensor. The method has the advantages that the accuracy of strain calculation is high, the calculation efficiency is remarkably improved, and the applicability and expansibility are high.

The invention discloses an expert classification and grading method based on artificial intelligence driving and related equipment, and can be applied to the technical field of artificial intelligence. According to the method, after the first expert classification system is expanded based on the dynamic field expansion rule to obtain the target classification system, feature extraction is performed on the unstructured text data of the to-be-classified and graded experts based on the preset weighted statistical algorithm to obtain the weighted feature vectors; and then calculating the cosine similarity between the weighted feature vector and all domain vectors in the target classification system, and determining a target classification result corresponding to the to-be-classified and graded expert in the target classification system according to the cosine similarity, thereby effectively improving the expert classification accuracy. Meanwhile, according to the unstructured text data, after the multi-dimensional comprehensive score corresponding to the expert to be classified and graded is calculated through the multi-dimensional comprehensive evaluation system, the expert grading result corresponding to the expert to be classified and graded is analyzed according to the multi-dimensional comprehensive score, and therefore the expert grading accuracy can be effectively improved.

This invention pertains to computational fluid dynamics and machine learning technologies, specifically a physical mechanism-guided heterogeneous extrapolation method for high-resolution, meter-level dynamic fields of urban buildings. The method includes the following steps: selecting representative urban blocks to form a sample block set; using a WRF model to provide a regional-scale meteorological background field for the target city; driving a LES model to perform flow field calculations on the sample block set, generating high spatiotemporal resolution flow field data for the sample blocks, and pairing this data with corresponding meteorological background data to generate a training database; constructing and training a deep learning model for latent space injection of meteorological information, establishing an end-to-end nonlinear mapping relationship from the coupling characteristics of urban geometry and meteorological boundaries to the LES fine flow field through a dual-path encoding path and latent space injection mechanism; and dividing the target urban area into multiple local computational units to extrapolate the high-resolution dynamic field of the entire urban area. This invention balances computational efficiency, prediction accuracy, and physical consistency, enabling rapid response to urban dynamic fields.

The invention records a double-flow NeRF method for real-time reconstruction of a dynamic environment, and the method comprises the steps: S1, obtaining the dynamic environment data of a vehicle, including a four-way polarization image of the dynamic environment, a near-infrared image of the dynamic environment and the like, carrying out the multispectral fusion of the four-way polarization image and the near-infrared image, and outputting a feature map after fusion; s2, generating a dynamic mask based on the theoretical optical flow of the fused feature map; fusing the transient field and the dynamic field and outputting a final dynamic mask of the fused feature map; s3, constructing a three-dimensional reconstruction space taking the vehicle as the center, and dispersing the three-dimensional reconstruction space into a plurality of blocks; block feature vectors are loaded for the blocks needing to be updated; implicit scene representation of the three-dimensional reconstruction space is constructed, and graph-free semantic representation is output; s4, converting the three-dimensional reconstruction space into semantic understanding, segmenting a drivable domain of the three-dimensional reconstruction space, and generating a skeleton path of the three-dimensional reconstruction space; and optimizing a skeleton path through an energy functional minimization framework, and identifying and classifying a lane center line.

This invention provides an intelligent method and system for extracting and analyzing invoice information using deep learning, relating to the field of deep learning technology. First, based on the field flow and association logic of invoice business scenarios, it generates semantic traceability tracing trajectories for fields, collects scenario-related features of the invoice carrier to generate scenario feature guidance signals, and uses these signals to locate the physical presentation areas of key fields and extract their original information to form a set. Next, it constructs a dynamic field association model, inputting the set of original information for key fields and scenario-related features into the model, and uses deep learning algorithms to model dynamic dependency relationships to generate a dynamic field association graph. Finally, based on this graph, it integrates information to generate scenario-based structured invoice analysis results, including core field content, scenario association logic, and dynamic association descriptions, enabling efficient and accurate processing of invoice information.