22results about How to "Ensure reasonableness" patented technology

This invention relates to the field of artificial intelligence visual inspection technology, and discloses an artificial intelligence visual inspection method, system, and storage medium. The method includes: establishing a spatiotemporal field composed of sequential image frames; constructing dynamic behavioral trajectories of pixels within the spatiotemporal field, analyzing their fluctuation and propagation patterns to form evolutionary features; calculating a correlation matrix based on the evolutionary features, identifying pixel clusters, and performing multi-level feature decoupling to separate stable and transient feature layers; performing topological weaving on the stable feature layers to form a feature topology network and extracting structural invariants; using topological rules defined by the structural invariants to constrain the generative network and construct an enhanced feature expression layer; and fusing and projecting the enhanced features with the original image after removing the transient layer to generate a visual inspection image for surface state discrimination. This invention can separate the essential attributes of objects from environmental interference, and improves the accuracy and robustness of detection through feature enhancement guided by topological rules.

This application provides a map generation method and apparatus based on high-resolution remote sensing imagery. Its purpose is to achieve accurate matching and fusion of small patches and semantically compatible large patches through comprehensive similarity calculation of spectral, texture, and shape three-dimensional features, ensuring the accuracy of the generated map of the target area. Specifically, the map generation method based on high-resolution remote sensing imagery includes: acquiring a plot raster map based on remote sensing imagery of the target area; converting the plot raster map into an initial vector polygon map to obtain vector patches; calculating the comprehensive similarity between small patches and any large patch based on spectral, texture, and shape features in the feature data of the vector patches, wherein the large patch is a patch whose minimum distance to the small patch is within a preset distance threshold; fusing the large patch corresponding to the maximum comprehensive similarity with the small patch to obtain a plot vector file of the target area, and using the plot vector file to generate a map of the target area.

This invention provides a sample entry / exit method and system. Upon receiving sample entry / exit instructions, it automatically determines the task sequence and generates a task scheduling strategy based on the current number of idle robots. This achieves a fully automated process from task reception to execution, significantly reducing manual intervention and improving work efficiency. It also ensures the rationality and timeliness of task allocation, demonstrating a high level of intelligence. By comprehensively considering the task sequence and the number of idle robots, task allocation can be dynamically adjusted to ensure optimal resource allocation, thereby improving overall entry / exit efficiency. Furthermore, based on warehouse layout, shelf location, sample type and specifications, and task allocation results, precise movement paths can be planned for each target robot. This not only shortens robot travel time and reduces energy consumption but also avoids collisions and path conflicts between robots, ensuring the safety and smoothness of entry / exit operations.

The application discloses a multi-agent material calculation consistency calibration method, belonging to the cross field of material science, artificial intelligence and computational physics. The method adopts a master-slave structure multi-agent system, containing one master agent and at least three slave agents. The master agent is responsible for overall coordination, embedding physical mechanism constraints, consistency calibration and output results. The method steps are: constructing a calculation system, introducing physical mechanism constraints and embedding slave agent calculation models, collecting calculation data, performing bias analysis, adjusting parameters or correcting results through iterative calibration, and finally verifying and outputting the final results. The application introduces physical mechanism constraints, combines bias analysis and iterative calibration, and solves the problems of poor consistency of existing multi-agent material calculation results and easy violation of physical laws. Experiments show that the method reduces the deviation of the calculation results and the experimental measured values to below 3%, improves the calibration efficiency by more than 40%, and improves the calculation accuracy by more than 35% compared with the prior art, thereby improving the accuracy and engineering practicability of high-throughput calculation of material performance.

The present invention discloses a method and system for simulating and analyzing the impact on the marine resource environment. The method of the present invention includes constructing a two-dimensional plane numerical model for simulating the marine hydrodynamical environment; processing the grid of the two-dimensional plane numerical model to obtain a grid processing result; constructing a large sea area model based on the grid processing result; determining the water boundary input, time step, bed roughness rate and horizontal eddy viscosity coefficient of the large sea area model to obtain a simulation and analysis result. Through fine grid processing, the details of the marine hydrodynamical environment can be better captured, thereby improving the prediction accuracy of the model.

This invention discloses a method for predicting the maneuvering motions of hydrogen fuel cell-powered ships based on multi-source data fusion, relating to the field of intelligent ship navigation. The method collects geodetic coordinate system position and heading data from the BeiDou Navigation Satellite System and ship hull coordinate system acceleration data from the Inertial Measurement Unit (IMU). After differential and integral preprocessing, a neural network model is built. A fusion-type loss function is constructed based on the transformation relationship between the ship hull coordinate system and the geodetic coordinate system. The model is trained using a backpropagation algorithm and can also be extended to fuse data from multiple sensors such as GPS. This invention fully leverages the complementary advantages of multiple sensor sources, effectively compensating for the inherent deficiencies of single-sensor data, significantly improving the accuracy and robustness of ship maneuvering motion prediction, and providing reliable technical support for intelligent navigation decision-making and safety assurance of hydrogen fuel cell-powered ships.

The application relates to an application method, equipment and medium of power distribution network harmonic tracing in responsibility division, wherein the method comprises the following steps: S1, collecting harmonic data at a public coupling point, system side equivalent impedance and user side average fundamental active power, and performing pretreatment; S2, performing harmonic responsibility qualitative judgment through waveform feature analysis based on the harmonic data and the system side equivalent impedance, and generating a responsibility preliminary judgment conclusion; S3, performing responsibility quantitative calculation by using a comprehensive evaluation method based on the harmonic data, the system side equivalent impedance and the user side average fundamental active power, and obtaining responsibility quantitative parameters; S4, generating a responsibility division result based on the responsibility preliminary judgment conclusion and the responsibility quantitative parameters; the equipment and the medium are used for realizing the method. Compared with the prior art, the application significantly improves the accuracy and environmental adaptability of harmonic tracing and responsibility division.

This application discloses a method, apparatus, storage medium, and electronic device for positioning testing of freight trains. The method includes: acquiring satellite positioning information, driver-input departure information, identification and message information of the first group of physical transponders, and track installation position information of the first group of physical transponders; verifying the validity of each piece of information to obtain the validity status corresponding to each piece of information; combining the validity statuses of each piece of information to form a validity status combination result; generating a test scenario set based on the validity status combination result, scenario dimension layering rules, operating condition probability weighting strategy, and anomaly coupling rules; adjusting the triggering timing and triggering intensity of the target test operating condition based on the test scenario set and the real-time operating status parameters of the freight train; collecting the operating response data of the onboard system and the interaction status data between the onboard system and the radio block center during the simulation of the target test operating condition; verifying the operating response data and the interaction status data; and generating test results.

The application relates to a page generation method and device, equipment and a medium, and the method comprises the following steps: in response to a page generation event, determining table structure metadata of a target data table corresponding to the event, wherein the table structure metadata comprises field types, index information and field annotation information; determining target query fields according to the index information, determining front-end component types corresponding to each target query field based on the field types of the target query fields and preset component mapping rules; generating query configuration and display configuration according to the front-end component types and the field annotation information, wherein the query configuration is used for defining a query component containing the target query fields, and the display configuration is used for defining a data table component with the field annotation information as a table header; and rendering and generating a target page according to the query configuration and the display configuration. The application automatically reads database table structure metadata and generates a target page in a configuration-driven manner, thereby realizing automatic construction from a data table to a functional page.

This application discloses a method and equipment for recommending fracturing construction parameters for horizontal wells in transitional marine-continental shale gas reservoirs. The method includes: establishing a comprehensive geoscientific model of the transitional marine-continental shale gas reservoir based on geological parameters; determining a target fracture network model based on microseismic parameters and current fracturing parameters, and determining a target production simulation model based on current production parameters; determining single-stage mechanism models for each type of shale reservoir based on the target fracture network model, the target production simulation model, and the comprehensive geoscientific model; determining multiple sets of simulated fracturing construction parameters corresponding to the current fracturing construction parameters for each type of shale reservoir; determining multiple sets of simulated production parameters through the single-stage mechanism models for each type of shale reservoir; determining multiple net present values ​​(NPVs) based on the multiple sets of simulated production parameters, and determining the simulated fracturing construction parameter with the largest NPV as the target fracturing construction parameter. The technical solution provided in this application can improve the rationality of fracturing construction parameters for horizontal wells in transitional marine-continental shale gas reservoirs.

The application provides a kind of goods grabbing and placing strategy generation method and system, method includes the sampling processing to original video data, obtains continuous video frame sequence;Video frame sequence is encoded, and the discrete visual vocabulary sequence is generated;The time sequence dependence modeling of visual vocabulary sequence is carried out to learn the continuous change rule of object action in the video content represented by visual vocabulary sequence;Based on the visual vocabulary corresponding to the current state of the goods to be operated and the visual vocabulary corresponding to the expected target state, and using the continuous change rule of object action, the latent action vector representing the action execution sequence required for the transition from the current state to the target state is generated;The real-time physical state information of the robot obtained is mapped with the latent action vector, to generate the control instruction for driving the robotic arm to perform goods grabbing or placing operation, effectively reduces the dependence on a large amount of manually labeled data, and improves the self-adaptation and generalization ability of the model to unseen scenarios.

The application discloses a photovoltaic unit outer package line generation method based on cluster group intelligent division and dynamic bridging, and belongs to the photovoltaic system design field, and comprises the following steps: S1, identifying a photovoltaic panel set in a CAD drawing and obtaining a boundary coordinate set Pxl, calculating the number of photovoltaic panels Cx and the size parameters of each photovoltaic panel; S2, determining the minimum value of the cluster group distance threshold based on the size parameters of the photovoltaic panels, automatically calculating the optimal cluster group distance threshold in combination with statistical analysis based on the distance between all photovoltaic panels, cluster analysis based on distance distribution and density analysis, performing cluster analysis on the photovoltaic panels according to the threshold, and completing photovoltaic panel cluster group division; S3, generating an equidistant outer package line for each photovoltaic panel cluster group; S4, connecting all the offset cluster group outer package lines into a single closed photovoltaic unit line through a dynamic bridging algorithm based on the minimum distance path. The adaptive intelligent division of the photovoltaic panel cluster group is realized, and the high-precision, boundary-fitting and smoothly connected photovoltaic unit outer package line is generated.

This application relates to the field of elderberry extraction technology, specifically to an elderberry extract, a low-temperature production process, and equipment. The process includes: obtaining elderberry raw materials; during continuous countercurrent microwave extraction, collecting the heating power of each microwave generator in each cycle and the corresponding temperature; selecting adjustable generators from all microwave generators; quantifying the temperature change caused by a unit heating power per unit time; calculating the power correction amount for each adjustable generator in the current cycle based on the temperature difference between the current cycle and its standard cycle; and correcting the heating power of each adjustable generator after continuous countercurrent microwave extraction; obtaining the extract after extraction; preparing a glycosylated solution; passing the glycosylated solution through a macroporous resin column; eluting and filtering to obtain the elderberry extract. This improves the stability and accuracy of the low-temperature extraction process of elderberry extract.

The present application relates to the technical field of intelligent control of water plants, and discloses a sewage treatment carbon source intelligent dosing method, which comprises the following steps: constructing a sewage treatment biochemical simulation model, and performing static initialization and dynamic optimization based on historical data; in the first control stage, the model is used to perform dosing control, measured data and calculated data are accumulated and screened as a training data set, and an AI model is constructed; in the second control stage, i.e. mechanism and AI fusion, after model self-checking, intermediate state parameters representing microstate are generated; the intermediate state parameters are input into the AI model to obtain instructions, drive the carbon source dosing unit to perform dosing, and perform stepwise feedback regulation according to the effluent water quality. The present application uses an AI model to replace the cyclic iteration trial calculation of a mechanism model, shortens the calculation time, ensures that AI prediction conforms to the biochemical reaction rule through the microstate parameters provided by the mechanism model, and combines a feedback regulation mechanism to realize precise, rapid and stable dosing of the carbon source.

This invention provides a market-based method for distributed resource negotiation and spatiotemporal conflict resolution. The method includes: a management node constructs a spatiotemporal demand Bloom filter based on task spatiotemporal constraints and broadcasts task announcements; simultaneously, it maintains a reputation model containing historical scheduling deviations and conflict contributions of nodes; contractor nodes match the filter and submit bids containing resource scheduling schemes and associated confidence levels; the management node calibrates the scheduling schemes based on reputation information and confidence levels to obtain a resource scheduling probability distribution, and calculates the global load entropy reduction accordingly; when conflicts exist, a loss function is constructed based on task migration, resource idleness, and opportunity cost to calculate the preemption compensation cost; an evaluation value is obtained by comprehensively considering the bidding benefits, entropy reduction, and compensation cost; the best contract is awarded; after the contract is executed, the contractor node's reputation record is updated based on the actual execution and conflict results, thereby achieving distributed resource negotiation and conflict optimization resolution.

This invention discloses a swarm cooperative intelligent localization method and system with enhanced physical information, relating to the field of swarm control technology. The method includes: obtaining the posterior state estimate and its corresponding covariance matrix of each agent based on inertial measurement data using an extended Kalman filter algorithm; constructing a dynamic spatiotemporal graph based on effective relative position observation information among the agents; obtaining the input feature vector for each agent based on its posterior state estimate and corresponding covariance matrix; inputting the input feature vector and the dynamic spatiotemporal graph into a decoupled dual-head graph neural network model to obtain the global state correction for the entire agent swarm and the local relative state correction for each agent; and calculating the final state estimate for each agent based on its posterior state estimate, local relative state correction, and global state correction. This invention can significantly improve the accuracy and robustness of cooperative localization.

This invention discloses an automatic code generation method based on agent-assisted and natural language understanding. The method is implemented using a three-layer architecture system with agent scheduling. The system includes an agent, a requirement understanding layer, a logic planning layer, and an intelligent completion layer. The method comprises the following steps: receiving natural language code requirements input by a user; the agent calling the requirement understanding layer to process the natural language code requirements; the agent calling the logic planning layer to decompose and generate a corresponding business logic framework based on preset business scenario classification rules; and the agent calling the intelligent completion layer to perform syntax verification and logical consistency verification on the target code. This invention solves the technical problems of traditional low-code platforms requiring manual configuration of complex business logic, and the inconsistent user experience and poor controllability of pure natural language code generation tools by constructing a three-layer collaborative system of "requirement understanding-logic planning-intelligent completion".

This invention belongs to the field of gas-sensitive material development technology, and discloses a machine learning-based reverse design method, system, and device for gas-sensitive materials. The reverse design method for gas-sensitive materials includes the following steps: S1, constructing a target dataset; S2, based on the target dataset, constructing and training a physical information neural network model coupled with multi-physics partial differential equations; the multi-physics partial differential equations include at least one of the following: multi-component competitive Langmuir adsorption kinetics equation, Fick diffusion equation, Poisson charge equation, and Drift-Diffusion carrier model; S3, using the trained neural network model, with the target sensing performance as input, to obtain the corresponding target material configuration. The design method provided by this invention can significantly improve the screening accuracy and speed of gas-sensitive materials and is suitable for engineering applications.

The utility model provides a kind of wiring device of electrical equipment installation, including wire slot, the upper position of two parallel sides of wire slot is equipped with multiple even arrangement partition strip, there is gap for inserting electric wire between adjacent two partition strips, the top cover is inserted in the one end of partition strip away from wire slot, bottom plate is inserted in the side away from top cover in wire slot, the upper side of bottom plate is equipped with multiple layer and the layered strip of parallel arrangement of bottom plate, two perforations are set in the upper surface of layered strip, guiding rod is inserted in the perforation, the one end of guiding rod is connected with bottom plate, the upper side of perforation is equipped with the support sleeve of concentric arrangement with perforation, the one end of support sleeve is connected and fixed with layered strip, rubber sleeve is pasted in support sleeve by glue, the utility model has the beneficial effects as follows: multiple electric wires are arranged in wire slot in layered manner, reduce the resistance of damaged line extracted from wire slot in later period.

The application relates to a fast atmospheric temperature and humidity inversion method and system based on a neural network substitute model, which comprises the following steps: generating a training data set; constructing a deep neural network, training the deep neural network based on the training data set, and obtaining a trained neural network; replacing a forward radiation transmission model in a physical model-based iterative inversion method with the trained neural network to obtain an improved iterative inversion method; and inverting atmospheric temperature and humidity by using the improved iterative inversion method to obtain an atmospheric temperature and humidity profile. Without changing a physical inversion mathematical framework, the application uses a neural network technology to construct a high-precision and high-efficiency forward radiation transmission substitute model, embeds the substitute model in a traditional iterative inversion process, realizes order-of-magnitude improvement of inversion speed, and ensures physical rationality and precision of an inversion result.

This invention relates to the field of spatial intelligence and real-time graphics rendering, providing a spatial intelligent panoramic Gaussian block-based streaming rendering method and system. On one hand, by structurally dividing the spatial scene into blocks and explicitly expressing it using Gaussian parameters, each rendering unit possesses clear spatial location, orientation information, and energy distribution attributes, improving the interpretability and traceability of the rendering process. On the other hand, through cross-block energy conservation constraints and geometric continuity correction mechanisms, it effectively eliminates problems such as inter-block brightness drift, boundary discontinuities, and topological discontinuities that are prone to occur in traditional parallel rendering. Simultaneously, this invention integrates rendering, stitching, and performance feedback mechanisms into a dynamic closed-loop system. During each frame rendering process, it collects the performance status of the execution entity and rendering quality indicators in real time, and adaptively adjusts parameters such as block granularity, sampling density, and illumination weight, thereby achieving millisecond-level streaming output and stable, continuous panoramic rendering effects.

This application discloses a data prediction and early warning method, apparatus, equipment, and medium applicable to long-distance transportation in deep-sea mining, relating to the field of computer technology. The method includes: performing feature engineering processing on physical entity data and prior engineering data; fusing multi-fidelity data based on dimensionless numbers and target coupling indices; training a target model using the fused data; transferring the knowledge of the trained teacher model to a preset student model to obtain a target student model; optimizing the target student model to obtain an initial prediction model; if real-time operational data drift is detected, performing feature distribution alignment and small-step fine-tuning on the initial prediction model; performing meta-training on the processed prediction model to obtain a target prediction model; inputting a target vector constructed based on dimensionless numbers into the target prediction model to obtain prediction data and confidence intervals; and issuing an early warning based on the conditional value of risk and confidence intervals of the prediction data. This achieves high-precision prediction and early warning.