40 results about "Structure mapping" patented technology

The application discloses a kind of based on whitelist occupation monero network topology structure mapping method, the method includes: for each reachable node in monero network, the address in address set A is used to the white list of the reachable node is occupied, and after waiting for set time period, the white list of the reachable node is obtained;The address in the white list obtained is compared with address set A, and the first difference address set is obtained;According to the first difference address set, the outgoing connection node of the reachable node is determined;According to the outgoing connection node of each reachable node determined, the topology structure of the monero network mapped out is obtained.The application can not be necessary to send a large number of transactions to the network, avoid the invasiveness to network, and monero network topology structure can be accurately obtained at high speed.

This invention relates to the field of iron and steel metallurgy technology, and discloses a digital short-process steelmaking quality prediction method and system. The method includes: acquiring standard temperature deviation data and standard chemical fluctuation data; obtaining an initial disturbance distribution map using a correlation propagation model; constructing a global coupling matrix through graph structure mapping; determining the disturbance accumulation trend through time-series analysis and fusing it with chemical fluctuation analysis to obtain a fluctuation state identifier; adaptively correcting the global coupling matrix based on the fluctuation state identifier to obtain an optimized description of the disturbance influence range; and finally determining the final quantified value of steel quality by combining quality index mapping logic. This invention achieves accurate quantification and forward-looking prediction of the dynamic propagation and nonlinear accumulation effects of disturbances in short-process steelmaking by dynamically correcting the coupling matrix.

The application discloses a text content verification method and device, a storage medium and equipment, relates to the technical field of natural language processing, and mainly aims to solve the problems of poor accuracy and poor effectiveness of compliance verification of the text content of the existing financial product. The method comprises the following steps: obtaining the text content to be verified and the compliance standard text content; determining the text structured mapping and the first prompt word and the second prompt word based on the text content, and performing structured extraction on the text structured mapping, the first prompt word and the compliance standard text content based on a first large language model to obtain a text extraction result, wherein the first prompt word is used to represent a word indicating that the text content matches a clause sentence, and the second prompt word is used to represent a word indicating that the text content matches a consistency comparison sentence; and performing difference detection on the text extraction result and the second prompt word based on a second large language model to obtain a verification result of the text content.

The application discloses a coal water-structure state recognition method based on terahertz spectroscopy, and relates to the technical field of material property characterization. The method prepares a characteristic state coal sample containing raw coal, collects a terahertz frequency band transmission spectrum and constructs a difference spectrum; three typical mechanism spectra of water-induced polarization absorption, structure scattering enhancement and cavity polarization nonlinearity are extracted through non-negative matrix decomposition to construct a frequency spectrum-mechanism-structure mapping model; the spectrum of a coal sample to be measured is collected and a difference spectrum is constructed, and after solving an activation weight vector, the difference spectrum is matched with characteristic samples to inverse the water-structure state thereof. The method can realize nondestructive and accurate recognition of the water-structure state of coal, adapt to disaster precursor warning such as water inrush in coal mines, and expand the engineering practical value of terahertz technology.

The application relates to the technical field of fatigue experiment precision calibration, in particular to a high-precision fatigue experiment calibration method and related equipment. The method comprises the following steps: constructing an experimental structure response measurement system through a set of multi-point strain sensing array to obtain a structure sensitivity matrix; inversely calculating the real load of the structure through the structure sensitivity matrix to obtain six components of the real load at the structure end; calibrating the relationship between actuators and the structure through the six components of the real load at the structure end to obtain an actuator-structure mapping matrix; decoupling and controlling and distributing the actions of multiple actuators through the actuator-structure mapping matrix to obtain six components required to be input by each actuator; and synchronously correcting the dynamic loading phase according to the six components required to be input by each actuator and the six components of the real load at the structure end to obtain a high-precision dynamic load control signal. The method can eliminate errors such as loading path flexibility and coupling interference, and ensure the load independence and dynamic synchronism.

The present application relates to a kind of Sketch file analysis and layout conversion method, by structure mapping, style and layout adaptation, layout conversion, reshape element hierarchy, realize the conversion of Sketch file to structured JSON description file.Solve the conversion bottleneck of Sketch design file to low-code platform development, greatly improve the development efficiency and design draft restoration quality, also reserve space for future technology iteration.All algorithm parameters in the present application can be adjusted, with more hatching times, conversion restoration degree will be constantly improved.The conversion result is more in line with programmer thinking, realizes the automatic delivery link, eliminates the design-development fault in traditional development process.Structured data mapping, visual layer is directly mapped to business layer component, greatly reduces the workload of artificial configuration.Expected product iteration cycle is shortened by 40%, greatly improves the development efficiency.Reduce the communication cost between design and development, improve team collaboration efficiency.It has the ability to generate DSL across different development platforms, only need to adapt the mapping protocol of target platform.

The present application takes the position closed structure and the orthogonal component difference as the core, converts the information to be processed into the residual structure representation under the background reference state constraint, the background reference state is constructed by the receiving and transmitting parties according to the consistent generation rule, and can be used as the structural key or the key derivation reference in the safe scene, so that the transmission and storage load can be concentrated on the residual field and the necessary auxiliary field. The framework uniformly carries the encoding, compression, encryption, inversion, decoding and structured domain calculation and topological consistency reasoning, realizes the integration of compression and encryption, storage and calculation. The system improves the equivalent storage density and energy efficiency performance through structured aggregation, and provides consistent logical pointing and calculation basis for reconstruction and reasoning.

The application discloses a compliance file generation method based on OpenXml analysis and template deep configuration, and relates to the technical field of file generation.The compliance file generation method based on OpenXml analysis and template deep configuration comprises the following steps: S1, collecting and preprocessing structure mapping data, node positioning data and binding rule data in a file audit process, and constructing a standardized audit state data set; S2, analyzing the information integrity of the structured audit, and adjusting an audit description generation process; S3, evaluating the mapping redundancy degree of the audit chain, and adjusting a redundancy writing strategy; S4, evaluating the consistency of the audit data, and identifying the matching accuracy of the annotation insertion and the structure binding relationship; and S5, completing interface annotation reservation and audit content embedding, and generating a compliance file.The method solves the problem that the audit information recording mechanism lacks unified mapping capability of the structure layer and the interface layer, and the audit chain is prone to be broken, so that the whole-process audit management cannot be supported.

The application discloses a kind of electric spindle thermal error modeling methods based on physical and data hybrid drive, it is related to numerical control machine tool high-end equipment manufacturing field, including: the structure and thermal analysis of electric spindle, constructs the thermal network model of electric spindle;According to the thermal network model, the temperature of thermal node is calculated, and then the thermal elongation deformation of electric spindle is calculated based on temperature-structure mapping model;Thermal error residual prediction model based on XGBoost is constructed;With preprocessed temperature signal and working condition parameter as input, the real residual error of thermal error is used as label, and the residual prediction model is trained;The residual prediction model is updated by recursive least squares method, and the dynamically adjusted residual model is output, and the self-adaptive dynamically updated thermal error model is further obtained.By the application, data model optimization under the guidance of physical mechanism is realized, the dependence of data-driven model on training data volume is reduced, and the prediction accuracy, physical consistency and stability are improved.

The present application relates to the technical field of human resource management, in particular to a human resource archive storage management system based on a knowledge graph, which comprises a post identification module, a path modeling module, a node linkage module, a fracture identification module and an access control module.In the present application, through the normalized mapping of post description and skill combination, the standardization processing capability of unstructured archive content is improved, a stage label system that conforms to the post responsibility process is constructed in combination with the jump frequency and span characteristics of the multi-stage path nodes in the task record, the cross correlation of the responsibility fields between the nodes is identified by using the tenure cycle division result, the path structure mapping sequence is dynamically adjusted, the change situation of the responsibility transmission relationship in the structure path is accurately identified, and in the continuous vacancy path identification, the responsibility chain interruption range is judged by the field group difference, and based on the sensitive field distribution characteristics and the role field coverage ratio in the access path, the access permission judgment and the permission checking control at the path level are realized.

The application discloses a coal rock dynamic permeability detection method and system, comprising the following steps: collecting seepage response data in the process of stress disturbance or loading evolution of a coal rock sample, and performing pretreatment; constructing a pressure difference sequence, generating a seepage response state set; constructing a seepage path node set, establishing a path connection relationship set; calculating the path transmission contribution value of each seepage path, forming a seepage path probability field; constructing a path topological structure matrix according to the seepage path probability field, and calculating a path concentration index sequence; calculating a topological entropy sequence and a topological entropy change rate sequence; inputting the topological entropy sequence, the topological entropy change rate sequence and the path concentration index sequence into a permeability structure mapping model to generate a coal rock dynamic permeability detection result. The application adopts a path structure probability modeling method, realizes coal rock dynamic permeability detection, and has the advantages of strong structure sensitivity and high detection precision.

The application discloses a kind of fast texture mapping methods for bridge section components, belong to bridge infrastructure detection maintenance technical field.For the prior art cannot make full use of geometric prior, reconstructs pixel by pixel for a large number of geometric shape highly repeated components, there is serious calculation redundancy, and the quality of reconstructed surface is not good, by sparse point cloud reconstruction positioning, multi-stage geometric prior registration, structured grid generation, high-fidelity texture mapping lightweight reconstruction method, output high-resolution texture mapping model with real appearance.Compared with the existing "sparse reconstruction-dense reconstruction-general grid generation-mapping" traditional process, the application skips time-consuming dense reconstruction process, by making full use of the strong geometric constraint of component, realize the fast conversion from sparse point cloud to structured mapping grid model, so as to provide a high-fidelity digital base for management personnel to support disease interactive quantification and labeling.

This invention discloses a method for responding to and assessing risks in a complex network subject to indiscriminate propagation attacks. The method includes constructing an information network topology model and a control network topology model, and establishing a structural mapping relationship between them. Based on the above and combined with multiple preset attack methods, a cascading failure model for the complex network to respond to a series of attacks is constructed. The network is attacked based on preset attack methods. A fast-process simulation of short-term fault response and handling is performed, followed by a slow-process long-term evolution and optimization, with optimal power flow models called to optimize the network's operating state. Iterative execution continues until preset conditions are met. Based on the operational data during the iteration process, the dynamic evolution results and risk assessment results of the network under the series of attacks are output. This invention solves the technical problems of fragmented analysis of two-layer networks, incomplete coverage of attack methods, lack of dynamic evolution capabilities, and inaccurate risk assessment in existing technologies.

The application relates to the technical field of software engineering design, in particular to an interactive protocol for automatically disassembling sub-agents of an agent in a multi-agent scene, which comprises a label structure construction module, a sequence behavior derivation module, an action statement definition module, a protocol content arrangement module and an instruction resource archiving module.In the application, the state identification in the task flow of the main agent is subjected to field disassembly and structure mapping, the state transition sequence is constructed in combination with time sequence, the continuity of the attribute change path is judged, the behavior link with logical constraints can be formed, the semantic expression of the task control instruction and the accurate definition of the state mapping structure are realized through classification marking, the action elements and feedback fields are subjected to sequential optimization and structure screening, the instruction statement is ensured to have unified logic and response adaptation capability, the protocol content is ensured to have consistent support of efficient execution and function correspondence, and the protocol adaptability and semantic structure stability in the multi-task promotion process are enhanced.

The application discloses a kind of adaptive control optimization methods of manipulator, it is related to intelligent control technical field, utilize manipulator ontology perception network to obtain the real-time time series signal stream of driving pressure and current, real-time time series signal stream is converted into continuous time sequence characteristic matrix, and equivalent rigid body dynamics model is constructed by physical structure data, and state variable and error variable are defined, continuous time sequence characteristic matrix is input into echo state network, and reserve pool state vector is output by reserve pool structure mapping, and reserve pool state vector is defined as characteristic base function vector, Bellman error is calculated based on error variable, and reinforcement learning evaluation network is constructed using characteristic base function vector, weight estimation value and disturbance estimation parameter are calculated, aggregate uncertainty function is obtained, output control moment is calculated based on aggregate uncertainty function, and actual output moment of actuator is calculated by output control moment, to complete the control of manipulator.

The present application relates to the technical field of intelligent power distribution equipment and power distribution automation, and particularly relates to an automatic topology identification method of a modular power distribution box; the process comprises: collecting connection behaviors of module interface insertion, mechanical locking and main circuit conduction state to form a connection behavior sequence; generating a structure-derived connection behavior sequence based on the power supply path of the module in the box and the correlation module relationship; checking the time sequence correspondence relationship and state closure relationship between the interface level and the structure-derived level sequence through cross-level consistency rules to form a topology relationship determination result; performing local topology update according to the determination result to update the topology structure mapping of the modular power distribution box; the present application overcomes the recognition dead zone and electromagnetic coupling interference caused by low impedance and high collinear branch, can accurately determine the real physical connection relationship between the modules, supports plug-and-play of the modules and dynamic adjustment of the local topology, and improves the system topology identification precision and operation and maintenance management efficiency.

This invention discloses an AI-powered intelligent recognition and automated form filling system for the manufacturing industry, integrating OCR and NLP technologies, and its implementation method, belonging to the field of manufacturing digitalization technology. The core of this technology lies in achieving rapid recognition of business scenarios with multiple input types, including voice, text, and documents, through the integration of OCR and NLP technologies. It utilizes a JSON template with a table structure to complete standardized data parsing and automatically links and opens the corresponding business modules to automate form filling. Specifically, it quickly matches input information with business scenarios by constructing a scenario feature library and a JSON mapping system with the table structure; it uses enhanced OCR to extract image / document data and NLP technology to parse voice / text semantics, generating JSON format data conforming to the table structure; finally, it automatically calls and opens the target business module to complete data filling and process triggering. This invention solves the technical pain points of slow scenario recognition, non-standard data parsing, and the need for manual switching of business modules in traditional manufacturing form processing, significantly improving form processing efficiency and business continuity. It can be widely applied to various manufacturing scenarios such as equipment inspection and invoice recognition, and has strong practicality and scalability.

The present application relates to a kind of sports pants tension band structure mapping model construction method and performance evaluation method and system, belong to sports clothing performance analysis technical field, solve the problem that evaluation means lacks unified objective standard in prior art, cannot be reused.The method includes: quantitative analysis is carried out to each sample sports pants, obtains the parameter vector value of hip tension band structure;Through video posture recognition, respectively extract each sample sports pants before and after wearing hip joint angular velocity variation;With the parameter vector value of hip tension band structure of each sample sports pants and hip joint angular velocity variation before and after wearing as sample label value, sample data is constructed;Multiple sample data is used to train multiple linear regression model, and mapping model predicted by the parameter vector value of hip tension band structure hip joint angular velocity variation is constructed.The present application can quantitatively evaluate the performance of sports pants tension band structure, realizes efficient, reusable performance evaluation.

The present application belongs to the technical field of computer system testing, and particularly relates to a deep learning library defect detection method based on a weighted directed cyclic graph, and the specific process is as follows: a weighted directed cyclic graph WDCG topology structure for expressing a complex timing control flow is constructed, and is serialized into a standardized configuration file; priority guided topology structure variation and operator variation are implemented for a high-risk transmission path in the WDCG topology structure physical graph; the generated WDCG topology structure is mapped into an executable physical model under different deep learning libraries; multi-dimensional test prediction is concurrently executed on the executable physical model, and output tensors and parameter gradients are captured through given input data; the output tensors and the parameter gradients are compared, when there is a defect, the execution data collected in the test process is structurally analyzed, a high-risk transmission path is identified and is fed back to the WDCG topology structure variation; files required for reproducing the defect are saved and are fed back.

The application discloses a kind of thin reservoir top interface accurate structure mapping method and device, belong to oil and gas field development technical field, the method is directed to thin reservoir and innovates top interface seismic horizon correction method, using amplitude variation characteristics eliminates the time horizon deviation error caused by thin layer effect, the amplitude value of formation top interface reflection phase axis and the time deviation of amplitude maximum value change with formation thickness variation, by establishing its function relationship, the relationship between the amplitude value of formation top interface reflection phase axis and the time deviation of amplitude maximum value is directly obtained, to carry out correction.The application avoids the influence of interwell thickness variation on correction effect in the correction process, improves the interpretation horizon precision, and finally improves the precision of thin reservoir top interface structure mapping, and has an important role in finding remaining oil and gas enrichment area in the later development stage.

The application provides an artificial intelligence-based automatic control method for a hydropower station gate, and relates to the technical field of automatic control technology for hydropower stations, and the method comprises the following steps: constructing an initial response characteristic space of a gate control variable according to a target water level inversion; performing dynamic flow field compression modeling based on the initial response characteristic space to construct a compression state variable; establishing a state input-action feedback learning model according to the initial response characteristic space and the compression state vector; generating a target-oriented regulating amount based on the compression state prediction value and the feedback model; and performing structure mapping correction according to the regulating amount and the motion characteristics of the gate mechanical structure. The application adopting the above scheme can significantly enhance the adaptability and self-learning ability of the hydropower station gate control system to a nonlinear dynamic environment.

The application discloses an API behavior perception modeling method and system based on semantic structure mapping and continuous learning, a device and a medium, and belongs to the technical field of API modeling. The method comprises the following steps: generating an interface semantic graph and a representation matrix through semantic analysis, combining user behavior modeling to extract behavior feature embedding and context association graph, fusing semantics and behavior features to form a joint representation, performing security risk analysis to identify abnormal behavior and assess risk levels, updating model parameters according to new data and feedback, monitoring model drift and adjusting behavior baseline through a continuous learning mechanism, and generating an interpretable report based on abnormal results, risk scores and multi-modal weights. Through the introduction of the API semantic structure mapping mechanism and behavior context modeling, the application realizes accurate perception and identification of interface call intentions and complex attack chains. Through the continuous learning mechanism, the application has the environment self-adaptation and long-term evolution ability, and effectively avoids model aging.

The application provides a data model structure mapping method, system and terminal, which synchronizes and supplements metadata of a to-be-mapped data model structure, generates a corresponding original operation data storage model through the supplemented metadata of the to-be-mapped data model structure, performs a mapping operation on the to-be-mapped data model structure based on a pre-constructed table field mapping large language model, maps the to-be-mapped data model structure to a preset standard data model structure, generates a corresponding data model mapping relationship and a data model mapping script, thereby replacing an artificial mapping mode, reducing mapping time consumption, reducing mapping cost, improving mapping efficiency and accuracy, and solving the technical problems of large artificial workload, high cost, low efficiency, dependence on artificial experience, poor accuracy, reliability and traceability in the prior art of mapping each data model structure by using an artificial mapping mode.

The application provides a method and device for converting a time domain seismic profile into a depth domain seismic profile, which comprises the following steps: reading time domain seismic profile data, interpreting a geological horizon of the time domain seismic profile, and dividing strata in the time domain into a plurality of strata segments; obtaining a seismic-logging time-depth relationship calibration list according to geological layering data of a logging curve and geological horizon interpretation data, calculating average velocities of each stratum and average velocity errors of stratum velocities at each well; updating a time domain stratum velocity field matrix according to the average velocity errors of the strata and the average velocity field, and drawing a depth domain seismic profile. The application more directly interprets seismic data in the depth domain, realizes a programmed processing mode of the average velocity field of the strata and correction, greatly reduces the workload of time-depth relationship correction and depth domain structure mapping, is convenient for directly mapping, and also provides support for carrying out other related geological researches.

The application relates to the technical field of data retrieval, in particular to a power distribution network data intelligent retrieval method based on a double-helix question and answer system. The method comprises the following steps: acquiring a to-be-retrieved question input by a business personnel; acquiring historical power data of a power distribution network to construct a distribution network corpus, and cutting the distribution network corpus into multiple information segments; evaluating semantic correlation between the information segments and the to-be-retrieved question to filter out all relevant segments from the information segments; constructing a pre-retrieval knowledge graph; constructing a weighted undirected graph; performing maximum spanning tree extraction on the weighted undirected graph, mapping the topological structure reserved by the spanning tree back to the pre-retrieval knowledge graph to extract a knowledge sub-graph; performing intent recognition on the to-be-retrieved question, mapping the recognized intent to a corresponding relationship in the knowledge sub-graph to perform semantic reconstruction on the to-be-retrieved question, and performing question and answer retrieval by using the reconstructed question. The application improves the intelligent retrieval efficiency and precision of power distribution network data.

This invention discloses an intelligent disaster relief command method based on graph neural networks, comprising the following steps: Step 1: acquiring disaster relief elements at the disaster site; Step 2: establishing relationships between rescue objects through spatial topological mapping; Step 3: generating a disaster relief relationship graph through graph structure mapping; Step 4: performing hierarchical neighborhood propagation and situational modeling on the disaster relief relationship graph using an improved GraphSAGE network; Step 5: performing optimal matching solutions using an improved Hungarian matching algorithm to generate a set of matching results between rescue resources and disaster-affected targets; Step 6: generating a set of rescue command strategies and distributing them to target rescue units for collaborative disaster relief command; Step 7: continuously acquiring disaster relief elements for dynamic updates. This invention improves the accuracy and real-time performance of disaster relief command by using an improved GraphSAGE network and an improved Hungarian matching algorithm.

This invention relates to the field of software engineering design technology, specifically to an interaction protocol for automatically decomposing sub-agents in a multi-agent scenario. The protocol includes a tag structure construction module, a sequence behavior derivation module, an action statement definition module, a protocol content arrangement module, and an instruction resource archiving module. In this invention, by decomposing and mapping the state identifiers in the main agent's task flow into fields, constructing a state transition sequence based on time sequence, and determining the coherence of attribute change paths, a logically constrained behavior chain can be formed. Through classification and labeling, the semantic expression of task control instructions and the precise definition of the state mapping structure are achieved. Furthermore, the order of action elements and feedback fields are optimized and the structure is filtered to ensure that instruction statements have unified logic and response adaptability, and that the protocol content has efficient execution and consistent functional support. This also enhances the protocol's adaptability and semantic structure stability during multi-task progression.

The application relates to the technical field of medical care information science, and discloses an AI-based old-age care system and method, which comprises the following steps: a signal acquisition module acquires physiological signals of an audience; a feature segmentation module extracts physiological feature vectors by using a physiological feature vector library; a topological modeling module constructs a physiological state directed topological structure; a search matching module maps the physiological topological structure into a binary hash search code by using a local sensitive hash function cluster, and matches a reference topological feature in a physiological normal state library to determine a Hamming distance; and a care instruction generation module determines a physiological abnormal state according to the Hamming distance and generates a care decision data packet. In the application, waveform evolution is converted into a topological atlas, and a high-dimensional search mechanism is introduced, so that the false alarm problem caused by physiological parameter dynamic drift is effectively overcome, and the reliability of the identification of hidden recession is improved.

The specification discloses a navigation structure generation method and device, a storage medium and an electronic device, wherein the method comprises: obtaining three-dimensional modeling data corresponding to each building in a target geographical area, and a regional image corresponding to the target geographical area; determining a building road network of at least one floor in each building based on the three-dimensional modeling data; generating a road network structure of the target geographical area based on an outdoor road network in the regional image and the building road network; the outdoor road network is other road network in the regional image except the building road network; mapping the road network structure into a planar graph data structure; obtaining a structure parameter corresponding to the graph data structure; and using the specification, the three-dimensional data of the target geographical area is converted into planar data, and the structure parameter of the graph data structure corresponding to the target geographical area is calculated according to the planar data, so as to improve the accuracy and efficiency of the navigation path.

This invention discloses a method for aligning nodes in large-scale complex networks based on a large language model. First, structural embeddings are learned for both the source and target networks, and node-level structural similarity is calculated to select a candidate set for each source node. Then, the local topological features, embedding vectors, and structural prior scores of the source and candidate nodes are compressed into pseudo-text prompts. A JSON similarity score is output by calling the large language model using a "source node aggregating candidates, single-time multi-candidate comparison" approach. If parsing fails, structural similarity backoff is used to construct an LLM similarity matrix. Finally, the GNN embedding channel, PALE structural mapping channel, community prior channel, and LLM channel are incorporated into a learnable multi-channel joint decision framework. Under anchor constraints and ranking loss training, a comprehensive similarity matrix is ​​obtained, outputting the alignment relationship from the source node to the target node. This invention significantly reduces the coverage and average number of calls to the large model while improving alignment accuracy.