47 results about "Design evaluation" patented technology

The invention relates to the technical field of power systems and automation thereof, in particular to a distribution network auxiliary decision-making method and system considering source load fluctuation relevance and a medium. The method comprises the following steps: firstly, collecting related information of a distribution network area, quantifying a synchronization and hysteresis association rule of multi-source heterogeneous data fluctuation, and constructing a composite feature vector and a standardized risk perception data set; defining a state space and an action space of a reinforcement learning algorithm based on the composite feature vector, and realizing auxiliary decision-making optimization of the distribution network; constructing a scene feature library, calculating the fluctuation relevance similarity between a new scene and a historical scene, and multiplexing a deep reinforcement learning model architecture and carrying out transfer learning; building a power grid digital twinborn simulation platform, designing evaluation indexes, generating candidate schemes, deducing the candidate schemes, selecting recommendation strategies and storing the recommendation strategies in a strategy knowledge base.

The invention relates to the technical field of computer aided design and visual computing, and provides a visual communication design evaluation system and method based on data analysis. The method comprises the following steps: acquiring original design data, and extracting a spatial layout feature matrix, a color distribution feature vector and a semantic content feature set; calling a design specification knowledge base based on the design purpose information; performing simulated attention distribution analysis and design compliance analysis to generate corresponding features; constructing a transmission efficiency prediction model to generate a comprehensive transmission efficiency score and an initial design evaluation report; performing interference effect joint analysis to obtain a comprehensive interference effect quantitative evaluation result; and performing efficiency optimization correction on the initial design evaluation report based on the result, and outputting a final design evaluation report integrating spatial layout and visual attribute optimization suggestions. According to the method, the interference effect is accurately quantified through conjoint analysis of spatial layout and semantic attributes, and the accuracy and reliability of design conveying efficiency evaluation are improved.

The invention discloses a sheet metal part manufacturability reasoning method based on space-semantic map alignment, and relates to the field of manufacturing-oriented design evaluation and industrial knowledge reasoning, and the method comprises the following steps: carrying out geometric analysis on a CAD geometric model of a sheet metal part to be evaluated; abstracting the geometric features and the topological / metric spatial relationship thereof into a computable spatial semantic graph; performing semantic analysis on the process specification described by a natural language, converting the process rule into formalized logic check expression by using a large language model through context learning, and generating an executable domain-specific language check script; executing the script on a spatial semantic graph, realizing deterministic reasoning through graph matching and attribute verification, and completing accurate mapping and violation detection of text rules and geometric features; and outputting an interpretable diagnosis result containing violation feature positioning, triggering rules and numerical evidence. In order to solve the problems that a process rule'natural language-geometric model 'has a semantic gap, a traditional rule system is poor in adaptability, and an end-to-end learning method is high in data dependence and cannot be explained, a new rule can be quickly adapted under the condition that a large amount of data does not need to be labeled and a model does not need to be retrained; the method can accurately identify the violation of the micro-size and spatial relationship, and has reasoning preciseness, interpretability and engineering availability.

The invention discloses a cooperative training data generation method for an adjustment and optimization problem and electronic equipment, and the method comprises the following steps: carrying out the filtering processing of an input code description text, and obtaining input data; injecting the problem data into the input data to generate first adversarial sample data containing the problem data; gradient information and disturbance amplitude are calculated, and second adversarial sample data are obtained through adjustment and optimization; designing a shared encoder based on the second adversarial sample data to obtain problem data and normal code data features; carrying out separation processing on the two in a feature space; according to the separated features, the shared encoder is promoted to learn through feature comparison, and finally a model generated by code training data is obtained; and designing an evaluation index for judging whether a generation result of the model in the problem data injection scene is correct and stable, thereby completing model training of code training data generation. According to the method, generalization and robustness of the large language model in the process of processing actual problems are improved.

The application discloses a product design intelligent evaluation system based on big data, and particularly relates to the technical field of product design evaluation, and the system comprises an anchor point account establishing module, a product evaluation module, a scheme rating module and a result output module; the anchor point account establishing module forms a design anchor point table according to a demand preliminary evaluation sheet and initial scheme information; the product evaluation module acquires a scheme change sheet and calls scheme verification data, and performs product undertaking verification; the scheme rating module combines the undertaking verification result and an auxiliary verification result to output a scheme evaluation state; and the result output module outputs product design intelligent evaluation results in a summarized manner. The application can continuously verify whether customer demand is undertaken by design parameters, versions, materials, processes, samples, costs and market feedback after scheme change, and can locate abnormalities to specific change fields, change components, anchoring relationships and data sources, thereby improving the traceability and review efficiency of evaluation results.

The invention provides an optimization design evaluation method for a labyrinth welding drum based on a parameterized model, and belongs to the technical field of aero-engines, and the method comprises the steps: building a drum parameterized mathematical model, and determining a drum stress expression; determining a dangerous part of the drum at the maximum working rotating speed, and determining the section average stress of the dangerous part based on the stress expression; aiming at the welding part, determining the residual strength reserve coefficient of the drum based on the initial defect, and determining the stress reserve coefficient of the welding part; for the maximum stress part, the ratio of the minimum self-sustaining radius of the two wheel discs connected with the drum to the pitch diameter of the drum is obtained; when the ratio does not meet the preset condition, the stress reserve coefficient of the maximum stress part is determined; and carrying out optimization design on the structural parameters of the drum by taking the lightest weight of the drum as an objective function and taking the condition that the residual strength reserve coefficient and the stress reserve coefficient do not exceed the material performance as a constraint condition. A complete evaluation system is established, the design period is shortened, and the evaluation accuracy is improved.

A big data-driven automatic evaluation method for automotive exterior styling design is proposed. First, a large-scale multi-view automotive image dataset is created for vehicle angle recognition and grade recognition, and deep neural network methods are used to train the corresponding vehicle angle recognition and grade recognition machines. Next, an automotive styling evaluation dataset is created for exterior styling scoring. This dataset includes multi-view automotive images and corresponding brand, model, and other labeled information, with styling score annotations and semantic evaluation annotations for end users and styling experts respectively. The automotive styling evaluation dataset is then split into corresponding subsets according to vehicle grade and evaluator attributes, and trained using deep learning regression and classification methods to obtain automatic scoring machines and automatic semantic evaluation machines at different levels for automotive exterior styling users and experts. The significant features affecting styling scores and semantic evaluations are visualized, providing stylists with real-time and objective styling design evaluations during the development process.

The invention provides a free surface range prediction method and device for a hole site design evaluation system, and relates to the technical field of tunnel intelligent blasting. The method comprises the steps that a coordinate system is established, blasting design is conducted, and coordinates of the two ends of all blast holes are obtained; determining a detonating time sequence, grouping the blast holes and coordinates thereof according to the detonating time sequence, and determining a grouping number; the slotting holes serve as a first group of blast holes, the range of a slotting area is defined by a triangle, and a slotting area enveloping surface is formed; triangles belonging to an orifice working surface and a hole bottom working surface are screened out and removed, and the remaining triangles form a first group of new free surfaces; and determining the range of the blasting cavities formed after blasting of the subsequent groups, updating the enveloping surfaces of the blasting cavities of the subsequent groups, and updating the new free surfaces corresponding to the groups until the last group. According to the method, the free surface range formed after blasting of each group of blast holes can be obtained, and a foundation is laid for calculating the blast hole resistance line.

The invention relates to a stochastic simulation method considering dimensional deviation and concrete material variability, and belongs to the field of concrete structure analysis. According to the method, accurate simulation of the mechanical properties of the concrete structure under the influence of construction errors and material randomness is realized by determining random factors, establishing a random field matrix, carrying out sample transformation, establishing random models in batches, solving in batches and carrying out post-processing. A random simulation result is used as an output parameter, a random sample is used as an input parameter, and a PRRM-EPR algorithm is adopted to establish a machine learning prediction model. Compared with a traditional method, the method has the advantages that the generation quality of the random sample is improved, the calculation cost is reduced, the randomness in actual engineering can be better reflected, and the established prediction model can directly predict the mechanical response (displacement, load and the like) of the component through actually measured random parameters. The method is suitable for design, evaluation and optimization of a concrete structure, and particularly has a remarkable effect on improvement of structural safety.

The invention provides a dynamic multi-level evaluation system, which comprises an evaluation specification management module used for storing an evaluation plug-in integration specification, an evaluation data description specification, an evaluation plug-in development specification and an evaluation model description specification; the evaluation data management module is used for creating an evaluation data model required by the task based on the evaluation data description specification; the evaluation model management module is used for completing the design of a comprehensive calculation model on the basis of an evaluation model which is developed by the evaluation model description specification; the evaluation plug-in management module is used for managing an evaluation plug-in, and the evaluation plug-in is packaged according to an evaluation plug-in integration specification and is called by the evaluation model management module; the evaluation system management module is used for designing and managing a multi-level index system required by an evaluation task; and the evaluation scheme management module selects a multi-level index system based on the evaluation task to create an evaluation scheme, and executes the evaluation scheme to generate an evaluation result. The method is clear in logic and simple to operate, and the evaluation work efficiency is greatly improved.

This invention discloses a method for constructing an AI-assisted assessment system for physical education teaching scenarios, belonging to the field of education. The method includes the following steps: First, a standard movement sample database is constructed based on physical education teaching standards, containing movement samples and feature annotations from multiple angles and difficulty levels; second, an AI assessment model is designed, using computer vision technology to extract key points of human posture, and combining temporal analysis algorithms to achieve automatic recognition and quantitative scoring of movements; then, a recording module, a feedback module, and a report generation module are integrated to provide video acquisition, real-time analysis, and personalized guidance functions; finally, the system is continuously improved through an iterative optimization path of data acquisition, model training, system integration, and experimental verification. This invention realizes the transformation of physical education teaching assessment from a subjective experience-driven model to a data-driven model, supports multi-dimensional movement scoring and deviation localization, provides objective and unified evaluation results, and offers immediate and accurate feedback, effectively improving teaching guidance efficiency and students' movement skill levels.

The invention belongs to the technical field of combination of a green building design evaluation technology and a multi-objective optimization algorithm, and provides a green building design scheme evaluation system based on a multi-objective optimization algorithm, and the system comprises the steps: screening quantifiable and optimizable green building design targets, and recognizing the strong conflicts between the targets; if the strong conflict exists, the anti-interference capability of a to-be-selected optimal solution set obtained through multi-objective optimization on weight fluctuation is checked through a judgment module; if the anti-interference performance of the solution set is poor, a weight sensitive target is positioned through sensitivity analysis; a reliable reference weight is generated by combining subjective weighting, objective weighting and sensitive target characteristics; and finally, giving consideration to the comprehensive performance and stability of the scheme through priority calculation, and outputting the priority of the to-be-selected scheme, thereby solving the problems of subjective weight setting and poor anti-interference performance of the scheme in the existing green building design evaluation, remarkably improving the scientificity and reliability of the evaluation result, and providing precise support for decision making of the green building design scheme.

The invention discloses an automobile instrument software design evaluation policy information extraction method and system, a medium and equipment. The method comprises the following steps: constructing design evaluation policy annotation data containing noise; screening a clean set and a noise set from the design evaluation policy annotation data based on a k-fold cross validation method; combining the clean set and the noise set based on a weighted weak supervision loss function to perform weighted training on an information extraction model to obtain a trained information extraction model; and performing information extraction on the to-be-identified automobile instrument software design evaluation policy document by utilizing the trained information extraction model. According to the method, through a two-stage adaptive noise processing framework, high-confidence-coefficient cleaning samples are screened based on loss values, and then noise sample training is fused through a weighted weak supervision loss function. According to the method, the extraction precision in a noise environment is remarkably improved, the dependence on expert labeling is reduced, and efficient compliance development of automobile software is facilitated.

The invention provides a core accomplishment-oriented Chinese teaching design evaluation method and device, and relates to the technical field of data processing, and the method comprises the steps: obtaining Chinese teaching design text data; inputting the Chinese teaching design text data into a pre-trained Chinese teaching design evaluation model to obtain scoring results of the Chinese teaching design text data in multiple dimensions; wherein the Chinese teaching design evaluation model is obtained by training a large language model based on a historical Chinese teaching design text data set through a pre-established Chinese teaching design evaluation system oriented to subject core accomplishment; the Chinese teaching design evaluation system oriented to the subject core accomplishment comprises a plurality of evaluation indexes of multiple dimensions. Through the method provided by the invention, automatic evaluation of Chinese teaching design is realized, and teachers are assisted in improving teaching design quality and teaching level.

This design evaluation system comprises: a feature quantification unit that, on the basis of a first trained model obtained by learning a first correspondence relationship between a material image indicating the design of a material and a feature amount obtained by quantifying an appearance feature of the design, quantifies the appearance feature of the design of a material indicated by a material image inputted as an evaluation target and generates feature amount information indicating the feature amount of the evaluation target; and a sensibility quantification unit that, on the basis of a second trained model obtained by learning a second correspondence relationship between the feature amount and a sensibility amount obtained by quantifying a sensibility word representing the appearance of the design, quantifies the sensibility word corresponding to the feature amount of the evaluation target indicated by the inputted feature amount information and generates sensibility amount information indicating the sensibility amount of the evaluation target.

The extrapolation degree of the candidate design of the target substance is evaluated. A design evaluation device includes: a reference design determination unit configured to determine a reference design indicating a recipe of a target substance manufactured using two or more material substances; a candidate design determination unit configured to determine a candidate design indicating a recipe different from the reference design; a level determination unit configured to determine a level indicating an extrapolation degree of the candidate design on the basis of a classification indicating a difference between the formula of the candidate design and the formula of the reference design; and a result output unit configured to associate and output the candidate design with the rank.

The invention discloses an EEG-based old-age institution visual environment cognitive performance evaluation method, relates to the technical field of environment monitoring, and aims to solve the problem that the cognitive performance of a scheme cannot be effectively pre-judged and optimized in the prior art. Objective quantitative evaluation of the cognitive performance of the visual environment of the pension institution is achieved, the problem that a traditional design evaluation method is low in evaluation accuracy is solved, and then effective pre-judgment and optimization of the cognitive performance of the scheme are achieved.

This invention discloses an intelligent control optimization method for cryogenic liquid evaporators. The method includes modeling a multi-valve control unit for the cryogenic liquid evaporator, designing an adaptive evaporator loss function, designing a centralized execution evaluation architecture for the multi-valve control unit, prioritizing experience replay training, and optimizing evaporator control. This invention belongs to the field of intelligent control, specifically referring to an intelligent control optimization method for cryogenic liquid evaporators. This scheme constructs precision control reward terms, energy consumption penalty terms, and safety penalty terms to balance control precision and system synergy. Based on the adaptive evaporator loss function design, conflict penalties are used to avoid contradictions in action logic, thereby improving the stability of control optimization. The degree of action conflict is incorporated into the experience priority calculation, prioritizing the learning of conflict scenarios. Importance weights and collaborative penalty designs are added to evaluate network loss, significantly reducing the probability of action conflict. Importance sampling is used to correct distribution offsets, thereby improving the reliability of control optimization.

The invention discloses a system interface design evaluation method and device, a storage medium and electronic equipment, and the method comprises the steps: collecting system interface data and a design rule, and setting a static evaluation index and a dynamic evaluation index according to the design rule; evaluating the system interface data based on the static evaluation index and the dynamic evaluation index to obtain a static evaluation value and a dynamic evaluation value; obtaining a human error evaluation value of the system interface based on the cognitive possibility model; and constructing a comprehensive score model according to the static evaluation value, the dynamic evaluation value and the human error evaluation value, and obtaining a design evaluation result according to the comprehensive score model.

The invention relates to the technical field of green building design, and discloses a digital intelligent green building design evaluation method. The method comprises the steps of collecting a multi-dimensional design parameter data set of a target building, wherein the multi-dimensional design parameter data set comprises spatial layout, material attributes, energy consumption and environment interference event parameters; energy consumption characteristic parameters, structural characteristic parameters and interference characteristic parameters corresponding to environment interference events are separated from the data set; establishing dynamic correlation characteristics of energy consumption and structural characteristic parameters, and extracting cooperative adjustment characteristics of environmental interference events on the two parameters; generating a comprehensive evaluation feature set representing the sustainability difference of the building based on the features, and calculating environmental performance score distribution; and according to the distribution optimization multi-dimensional design parameter data set, an optimization energy consumption and structural characteristic curve is separated. According to the method, through multi-dimensional parameter analysis and dynamic association mining, the comprehensiveness and accuracy of evaluation are improved, and a direction is indicated for design optimization.

The present invention discloses an automated evaluation system for cotton cloth design, comprising a data acquisition module, a preprocessing module, a database module, an import module, a data processing module, and a data output module; the preprocessing module is used to denoise and enhance real-time image data; the import module is used to match index thresholds of cotton cloth; and the data processing module is used to generate an evaluation report and an opinion report; the present invention collects parameter information of newly designed cotton cloth in different states, processes and analyzes different parameter information to quantitatively deduce the cotton cloth design, judges the rationality and practicality of different parameter designs, and automatically evaluates them, thereby effectively improving the efficiency of cotton cloth design evaluation; at the same time, the whole process unifies the measurement standard, thereby ensuring the consistency and accuracy of the evaluation and avoiding errors caused by human subjective judgment.

The present application relates to a target detection network evaluation method based on quantitative evaluation and explainability method. The present application combines quantitative evaluation and explainability method, which can more comprehensively and accurately evaluate the performance and decision basis of the target detection network. The present application uses multiple quantitative evaluation indicators (accuracy, recall rate, average precision, FPS) to comprehensively evaluate the target detection network. An explainability method based on perturbation and class activation mapping is proposed, which can help users understand the decision-making process of the target detection network. A visualization method based on gradient descent method and regularization technique is proposed, which can help users understand the semantics contained in the target detection network. The explainability method proposed in the present application can intuitively show the internal operation process and knowledge of the target detection network, thereby enhancing the explainability of the model and improving the credibility of the model results. Experimental results show that the present application can effectively evaluate the performance of the target detection network, improve the explainability of the model, and can be used for the design, evaluation and improvement of the target detection network.

The application discloses a kind of based on big language model's chart alternative text quality automation evaluation method and system, it is related to big language model field and chart alternative text field, including: by demand investigation, obtain chart alternative text quality evaluation scheme;Artificially construct chart alternative text evaluation standard data set carries out data preprocessing, based on GLM4-9B model carries out Finetune training and performance tuning.The chart alternative text quality automation evaluation method proposed in the application is based on chart accessibility reading criteria to design evaluation scheme, and the prediction score of the transfer model obtained by training is highly correlated with the artificial evaluation score, which can provide high-reliability automated chart alternative text quality evaluation results and can be applied to text quality evaluation in the field of chart alternative text.

The present application belongs to the technical field of green building design evaluation technology and multi-objective optimization algorithm combination technology, and provides a green building design scheme evaluation system based on a multi-objective optimization algorithm, which comprises: screening quantifiable and optimizable green building design targets and identifying strong conflicts between the targets; if there is a strong conflict, a judgment module is used to test the anti-interference ability of the selected optimal solution set obtained by multi-objective optimization to weight fluctuation; if the solution set has poor anti-interference ability, a sensitivity analysis is used to locate the weight sensitive target; then, in combination with subjective weighting, objective weighting and sensitive target characteristics, reliable benchmark weights are generated; finally, the priority of the selected scheme is output by considering the comprehensive performance and stability of the scheme through priority calculation, thereby solving the problems of subjective weight setting and poor scheme anti-interference in the existing green building design evaluation, significantly improving the scientificity and reliability of the evaluation results, and providing precise support for the decision of the green building design scheme.

This invention relates to a method, apparatus, and equipment for evaluating the single-event immunity of aerospace chips. By dividing the evaluation process into three stages—preliminary design evaluation, preliminary assessment, and chip compliance evaluation—the single-event immunity capability of aerospace chips is quantitatively measured. Simultaneously, the early evaluation in the preliminary design stage, the secondary verification in the preliminary assessment stage, and the comprehensive comparison in the chip compliance evaluation stage clearly and in a closed-loop manner assess whether the chip's single-event immunity performance meets the orbital insertion standards, greatly enhancing the risk control of aerospace chips. This evaluation technology is characterized by high universality and strong operability, improving the reliability of aerospace chips while avoiding design risks, and can be widely applied in the aerospace field.

The invention provides a hoisting evaluation method for a large-scale radar dome cover, and belongs to the field of radar erection, and the method comprises the steps: employing a finite element modeling method to construct a hoisting model, and the hoisting model comprises a radar dome cover model, a sling model, a crane sling model, a hoisting tool model, and a connection relation model; establishing a fluid calculation model of the radar dome cover at a set hoisting height, calculating pressure values of the inner surface and the outer surface of the radar dome cover, importing the pressure values into the hoisting model, and obtaining wind load input of the radar dome cover; calculating a key calculation index of the hoisting model in the hoisting action process by adopting a nonlinear display dynamics analysis method, and evaluating whether the hoisting model design is reasonable or not by comparing the key calculation index with a set value; the invention further provides a hoisting evaluation system. And carrying out full-size modeling and connection relation modeling on a crane lifting rope, a lifting tool, lifting belts and a radar dome cover, and carrying out comprehensive evaluation on the self stress damage possibility of the dome cover, the type selection and number identification of the lifting belts and the effectiveness of the lifting tool.

The invention relates to the technical field of waveguide device design simulation, in particular to a pattern duty ratio design method and system. Comprising the steps that a class of constraint conditions of a to-be-simulated object are obtained, at least one first waveguide pattern is arranged in the to-be-simulated object, and the class of constraint conditions comprise the pattern duty ratio of the first waveguide pattern; selecting a second-class constraint condition according to the type of the to-be-simulated object, wherein the second-class constraint condition comprises an auxiliary parameter used for describing the specification of the to-be-simulated object; constructing a simulation constraint model according to the first-class constraint condition and the second-class constraint condition; at least one round of simulation is conducted on the simulation constraint model through an electromagnetic simulation method, so that a design evaluation result of the simulation constraint model is obtained, and the design evaluation result comprises at least one simulation solution used for defining the optical performance of the to-be-simulated object. According to the method, the pattern duty ratio is optimally designed, so that the process implementation difficulty of the waveguide device in the nanoimprint process is reduced.

The application provides a situation comprehensive multi-satellite task planning design evaluation system and method, belongs to the satellite system overall technical field, and aims to solve the problems of difficult evaluation of multi-satellite task planning efficiency and difficult verification of algorithm. The system comprises a task planning control plug-in, a perception data generation plug-in, a comprehensive situation processing plug-in, a system efficiency evaluation plug-in, and a comprehensive simulation deduction platform integrated with the foregoing plug-ins. The system builds a closed-loop verification environment for task planning-situation processing. The corresponding method comprises scene building, service configuration, running simulation and evaluation analysis. The application can simulate multi-algorithm concurrent execution, and quantitatively evaluate based on a multi-dimensional index system at the levels of coverage planning, task and situation, thereby providing reliable data support for task planning design.

The application discloses a highway route design evaluation system based on data analysis, relates to the technical field of route design, converts natural language into a target vector, outputs current evaluation data based on historical design parameter data and operation effect data, inputs the target vector into a mapping relationship model to generate a design parameter candidate set, and verifies the design parameter candidate set through a sample guiding mechanism, iteratively corrects the design through error feedback and dynamic weight adjustment, samples in a parameter space to construct a path control point sequence and configures structure parameters, and the application realizes automatic generation of design parameters from the target vector through a bidirectional coupling mechanism of forward modeling and reverse modeling, realizes multi-round optimization iteration through error feedback, and improves the adaptability of the design result to the user target. Compared with a traditional passive evaluation process, the application has the advantages of target driving, closed-loop optimization and adaptive adjustment, significantly improves the intelligent degree and multi-target consistency of route design, and has strong practicality and technical progressiveness.

The present invention discloses a method for reliability design evaluation of a bridge support column structure, which relates to the technical field of bridge design evaluation, and includes: obtaining a first modeling data set based on the design drawing of the bridge support column structure, and establishing a three-dimensional model to be evaluated and a finite element model; generating a first simulated traffic flow, obtaining standard state stress data through simulation by applying loads and screening to obtain key stress surfaces; calculating the creep force of the statically determinate structure of the key stress surface, and calculating the evaluated damage life based on the creep force of the statically determinate structure; generating a second simulated traffic flow and performing simulation to obtain the offset state stress data of the key stress surface, and calculating the anti-offset reliability based on the offset non-linear regression equation; establishing an anti-impact reliability function, generating a simulated impact combination through the Monte Carlo algorithm and determining the simulated value of the anti-impact reliability; calculating the fusion robustness value based on the anti-offset reliability and the anti-impact reliability, and performing threshold judgment to obtain the evaluation result.