9 results about "Model quality" patented technology

A gas temperature field reconstruction method using thermocouple measurement correction is disclosed. First, an Inventor 3D model and an ANSYS temperature field model are established for the gas temperature field. Then, a mapping relationship is established between the control parameters of the gas temperature field and the boundary conditions of the ANSYS temperature field model. Based on the principle of maximizing the influence of fuzzy boundary conditions on the temperature field reconstruction results, experiments are designed for precise boundary conditions and experimental data are obtained. Next, given the boundary conditions of the ANSYS temperature field model, the model is run to obtain the temperature field reconstruction results. A model quality assessment algorithm is run to calculate the fitting degree between the measured curve and the simulation curve, obtaining the algorithm fitting parameters. The algorithm fitting parameters are selected to form the loss function of the gradient descent algorithm. The learning rate, termination condition, and initial iteration parameters are determined. The gradient descent algorithm is run until convergence. Finally, the final iteration parameters are taken as the correction result of the fuzzy boundary conditions of the ANSYS temperature field model. This invention improves the spatiotemporal resolution of the temperature field reconstruction results.

This invention provides an intelligent modeling method and system for steel performance prediction based on LLM (Liquidity Management Model). The system includes: receiving and parsing user instructions through a natural language understanding module to generate a standardized task description; automatically generating or matching an automated model building process based on the task description through a planning and execution module; providing decision support based on a knowledge base through a knowledge recommendation module during task planning or execution; and automatically scheduling functional modules such as data access, feature engineering, and model building to complete the modeling task and output the results, based on the recommended information, through the planning and execution module. The system accordingly includes various functional modules implementing the above method. This application achieves end-to-end automated modeling through natural language interaction, automated task planning, and intelligent knowledge recommendation, significantly improving modeling efficiency, lowering the technical threshold, and enhancing model quality and versatility.

This invention relates to the fields of blockchain and privacy computing technology, and provides a blockchain-based federated learning method, an industrial product quality prediction method, and a system. The federated method includes: deploying an initialized global model on the blockchain; clients retrieving the model from the chain, training it locally, and submitting model updates; committee nodes, dynamically elected, scoring the updates based on a verification dataset, and generating a consensus score by combining reputation weights and a two-sided pruning mechanism; qualified updates being aggregated by a smart contract to generate a new global model and writing it back to the blockchain; the smart contract distributing rewards and updating the reputation of the client and committee members based on the client's model quality and the consistency of committee member votes; and the system entering the next training iteration. This invention effectively solves the problems of centralized dependence, low-quality update interference, and unfair incentives in traditional federated learning by introducing an incentive mechanism and a dynamic reputation evolution mechanism.

The present disclosure provides a business model creation method and device, the method comprising: in response to a triggering operation on a modeling control in a visual modeling page, displaying a modeling element area; in response to a configuration operation triggered on each modeling element in the modeling element area in sequence, configuring modeling parameters corresponding to each modeling element based on a target business requirement; in response to the modeling parameters of each modeling element being configured, generating a target modeling process matched with the modeling parameters based on the modeling parameters configured for each modeling element; and running the target modeling process to execute a model construction operation through multiple modeling process nodes to generate a target business model. Thus, the present disclosure reduces the threshold for non-technical users to use machine learning modeling tools, reduces the dependence on feature engineering professional knowledge, and avoids the model failure problem caused by node misconfiguration or process loss in traditional visual modeling, while ensuring model quality and significantly improving modeling efficiency.

The application relates to the technical field of three-dimensional modeling, and discloses a large model driven industrial product design process optimization system and method, the large model driven industrial product design process optimization system comprising the following steps: analyzing input text; generating a differential parameter candidate set; constructing a surface boundary entity model and constructing a surface boundary topology graph; calculating a comprehensive impedance value; generating a target geometric parameter vector; generating a final instruction sequence and a final entity model; and outputting the final instruction sequence, the final entity model, the final comprehensive impedance value, the final model quality, the final modal frequency and the impedance improvement rate. The application realizes directional optimization of parameters through a one-time finite difference candidate set, avoids randomness of a large model, and generates a model which can simultaneously meet multidimensional constraints of heat, mechanics, manufacturing and assembly, so that a large amount of manual correction is not needed, the design iteration cycle of an industrial product is shortened, and the engineering practicability and landability of a design result are improved.

This invention provides an automatic identification and detection method and system for sealing grooves in aircraft structural fuel tank areas, comprising the following steps: S1, dividing the sealing groove into a groove bottom surface, groove sides, and auxiliary surfaces, and classifying the shape of the groove bottom surface; S2, constructing a set of concave diagrams of the sealing groove; S3, identifying the groove sides; S4, identifying the groove bottom surface; S5, verifying the groove features to ensure they are not empty sets and that their aspect ratios meet requirements; S6, performing automated standardization detection on key geometric parameters based on the groove features identified in the preceding steps. This invention can automatically identify sealing groove features in the 3D CAD model of the aircraft structural fuel tank area and perform comprehensive automated checks on its key geometric parameters. This method can improve model quality from the design stage, effectively avoiding manufacturing defects and sealing failure risks caused by modeling errors.

The present application relates to a kind of three heart circle hat brim bevelled type portal parameterized modeling method and system.Hand modeling of three heart circle hat brim bevelled type portal exists low efficiency, precision is not high, modification difficulty and other problems.This method obtains the basic parameters of bevel segment lining and hat brim of three heart circle hat brim bevelled type portal;Using the basic parameters of bevel segment lining and hat brim establishes the space curve control equation of four contour lines;According to four contour lines lofting generation space surface, suture obtains hat brim three-dimensional entity model;According to the basic parameters of bevel segment lining, generate bevel segment tunnel three-dimensional entity model;The three-dimensional entity model of hat brim and bevel segment tunnel three-dimensional entity model are combined, and three heart circle hat brim bevelled type portal three-dimensional entity model is obtained.Compared with traditional from two-dimensional design drawing, this method is faster, precision is improved and easy to modify, and the modeling efficiency and model quality are improved.

This application discloses a method, apparatus, device, and storage medium for generating a three-dimensional model. The method includes: acquiring a two-dimensional view of a three-dimensional object and extracting features from the two-dimensional view to obtain object feature vectors of the three-dimensional object; acquiring K feature vectors containing Gaussian features and, through an attention mechanism, performing feature enhancement processing on the object feature vectors of the three-dimensional object using each reference feature vector to obtain K enhanced feature vectors; constructing a Gaussian three-plane of the three-dimensional object using the Gaussian features of each enhanced feature vector, thereby performing three-dimensional reconstruction of the three-dimensional object based on the Gaussian three-plane to obtain a three-dimensional model of the three-dimensional object, thereby improving the object representation capability of the three-dimensional model and thus improving the model quality of the three-dimensional model.

This invention relates to model quality assessment technology, specifically a method for evaluating the quality of a 3D Gaussian splash model based on dual-graph representation similarity. The method includes the following steps: acquiring the distorted 3D Gaussian model to be evaluated and its corresponding distortion-free reference model; rendering the model to obtain distorted and distortion-free sequences; constructing a recurrent graph network to capture the non-uniform structural distortion of the 3D Gaussian model using the irregular graph association modeling capability of graph convolutional networks; fusing multi-frequency motion information through a recurrent neural network to establish a coarse-to-fine perceptual description of viewpoint switching; and extracting multi-scale graph features, including graph vertex pyramids and graph edge pyramids; designing a dual-graph representation similarity assessment module to perform Gaussian distribution similarity assessment and vertex structure similarity assessment on the multi-scale graph features; and concatenating the two similarities and inputting the results into a multilayer perceptron for fusion regression to obtain the final quality score. This invention achieves accurate perception of the non-uniform structural distortion and viewpoint switching coherence of the model.