10 results about "Iterative methodology" patented technology

The invention discloses a sample automatic collection and model iteration method for electrical equipment defect identification, belongs to the technical field of electrical equipment defect identification, and aims to solve the problems that a difficult sample discovery and collection mechanism is missing, model short plates are difficult to supplement and a model performance evaluation and feedback mechanism is imperfect. The method comprises the following steps: collecting multi-source power equipment inspection data, carrying out standardization processing, automatically discovering and collecting difficult samples, identifying the difficult samples from preprocessed samples based on a preset rule, establishing a difficult sample library, carrying out model iteration training, constructing a training set based on the difficult sample library and a basic sample library, and carrying out model training by adopting a weighted sampling strategy. Generating an iterative model; according to the method, key samples for model optimization are accurately screened through a difficult sample automatic discovery mechanism, storage and computing resources are prevented from being occupied by invalid samples without defects, with simple backgrounds and the like, and limited sample resources serve for model performance improvement in a centralized manner.

The invention discloses a multi-source data adaptive fitting method for a liquid hydrogen storage tank bench test, which comprises the following steps: synchronously acquiring multi-source sensor data in the liquid hydrogen storage tank bench test in real time, and preprocessing the data to obtain preprocessed real-time data; establishing a physical priori constraint equation based on a low-temperature thermodynamic law and a heat transfer mechanism, embedding the physical priori constraint equation into a data fitting objective function, performing physical constraint, and determining energy conservation, phase equilibrium and heat transfer boundary conditions required to be met by a fitting result; extracting data features of the preprocessed real-time data, matching the data features with a preset working condition feature library, and performing working condition identification to obtain a current test working condition identifier; adjusting regularization parameters by adopting an iteration method according to the current test working condition identifier, the data fitting residual error and the noise level; and carrying out data fitting by combining physical constraints, current test working condition identifiers and the adjusted regularization parameters, and inverting the state parameters in the storage tank. The algorithm can provide a reliable basis for design optimization and safety evaluation of the liquid hydrogen storage tank.

This invention provides a semi-automatic method for constructing and iterating an ontology in the financial and tax domain, comprising the following steps: S1, system initialization and configuration; S2, data acquisition and preprocessing; S3, based on a few-shot learning model and an expert rule base, automatically extracting core concepts from structured financial and tax data and inferring relationships between concepts, performing hierarchical modeling according to financial and tax business logic, and generating a draft ontology model; S4, multi-dimensional automatic verification and manual optimization of the draft; S5, ontology output and version management; S6, dynamic iterative update of the ontology; S7, iterative automatic verification of the ontology in multiple dimensions. This invention achieves four core advantages: improved efficiency, quality assurance, scenario adaptation, and dynamic updates, solving key technical challenges in the construction and application of ontology in the financial and tax domain, providing core support for the efficient operation of financial and tax intelligent agents, and possessing broad application prospects and commercial value.

The present invention relates to computer implemented adaptive and iterative methods to improve and accelerate a quality control decision or a performance test in a specific technical field while reducing the overall cost of the quality control or performance test process, respectively; the method comprising: constructing a sequential test; iterating the following steps using the sequential test until a decision is made, obtaining a set of samples, checking the decision of the criteria for the set of samples, determining in an adaptive way the optimal number of additional data samples required for the subsequent iterative step if no decision has been made in the current iteration.

The invention provides a karst tunnel excavation support pressure reliability design method based on threshold gradient. According to the method, aiming at three random variables in an HB constitutive model, firstly, center composite sampling is carried out in a standard normal space to obtain seven test points, coordinates of the test points are converted into an original parameter space, a failure threshold value of each test point is obtained through calculation by establishing a numerical model, then a secondary response surface agent model without cross terms is established, and the failure threshold value of each test point is calculated. And establishing a tunnel face support force dominant threshold function by solving a linear equation set and determining seven coefficients of the proxy model, on this basis, proposing a standard normal space target reliability isoline checking point iteration method, performing checking point iteration on a sphere with the radius being the target reliability, and updating checking points in a gradient manner by adopting the threshold function. And calculating the collapse load of the design point during iterative convergence, so that the collapse load meets the requirement of a target reliable index. According to the method, the design complexity is reduced, and the design efficiency is improved.

The application discloses a kind of space target pointing iterative calculation method and system of strapdown, belong to communication and measurement control technical field.The application is installed on the azimuth rotating platform of horizontal tracking frame by heading angle output angle as azimuth feedback information by heading angle output angle as azimuth feedback information, combined with the geographical pointing angle of space target, the theoretical heading angle when horizontal tracking frame points to space target is calculated using iterative method, and the corresponding heading angle correction method is provided.The application is installed on the azimuth rotating platform of horizontal tracking frame by the method that heading angle output angle as azimuth feedback information is output as feedback information, avoids the azimuth axis angle initialization process, effectively reduces the start-up time of horizontal tracking frame, with the advantages of no need to increase additional hardware, simple implementation, wide application range.

This application discloses a risk model iteration method, apparatus, device, and product, relating to the field of model iteration technology. The method includes: collecting operational data of an initial risk model in a production environment; detecting the operational data using detection indicators; when the operational data reaches the iteration trigger condition, creating a model iteration task and loading a pre-configured business dataset; collaboratively optimizing the hyperparameters of the initial risk model using the business dataset to obtain a globally optimal feature subset and an optimal hyperparameter combination; and iterating the initial risk model using the globally optimal feature subset and the optimal hyperparameter combination to obtain a final risk model. This solves the problems of lacking automated closed-loop iteration, delayed response, and the need for professional personnel to operate the risk model, thus failing to quickly adapt to dynamic business changes and improving the efficiency of risk model iteration.

This invention provides an efficient simulation method for multi-axis laser processing of complex surfaces based on keypoint interpolation. It addresses the technical problem that existing pulse-by-pulse laser processing simulation methods for complex surfaces, while improving simulation efficiency through parallel computing, suffer from limited efficiency gains due to the dependence of the number of parallel operations on the efficiency gain. The proposed method decomposes the processing trajectory of the complex surface into stable and unstable segments. Discretely sampled keypoint pulses are selected for iterative calculation within the stable segment, and interpolation is performed on non-keypoint pulses between two adjacent keypoint pulses. The interpolated morphology is almost identical to that calculated using the iterative method. By replacing iterative calculations with interpolation while maintaining simulation accuracy, the computational load is effectively reduced, significantly improving computational efficiency.

The invention discloses an aero-engine air system hardware-in-the-loop test method, which belongs to the technical field of aero-engine compressed air system tests and comprises an aero-engine compressed air system hardware test system and a main runner software model. The aero-engine compressed air system hardware-in-the-loop test method is a test method in which a main flow channel compressed air system adopts a software model for simulation and other compressed air systems adopt software and hardware real-time interaction of a hardware test bed. When an initial working condition is established, a software and hardware boundary coupling iteration method is provided by utilizing the characteristic of natural conservation in a hardware test bed. When a transient process test is carried out, a transient process iteration method is provided. According to the aero-engine air system hardware-in-the-loop test method provided by the invention, a compressed air system test under a transient process of an approximately real engine is realized, the test time is shortened, and the test difficulty and cost are reduced.

The invention relates to a power demand prediction-oriented data engine construction iteration method and system, and belongs to the technical field of power data security and artificial intelligence. Comprising the following steps: carrying out multi-granularity characterization on original power consumption time sequence data of a data private party, constructing a user-level and aggregated data sequence, and generating a multi-dimensional condition vector according to the user-level and aggregated data sequence; constructing a security data engine by using a conditional diffusion model trained in combination with a differential privacy stochastic gradient descent algorithm; a research and development party obtains high-simulation and privacy-risk-free synthetic power utilization time sequence data from the engine through structured query to train a demand prediction model; and after the model is deployed and verified by a data private party, carrying out collaborative iterative optimization on the prediction model and the security data engine according to performance feedback and business change. According to the method, on the premise of strictly protecting the privacy of the original data of the user, the effectiveness of the prediction model training data is ensured, and safe power consumption demand prediction collaborative research and development are realized.