26results about How to "Improve evaluation efficiency" patented technology

The present application relates to the technical field of children nutrition assessment, and provides a kind of intelligent food material identification weighing and children nutrition assessment system, comprising: weighing module, for accurately weighing food material weight;Image recognition module, integrated multispectral camera and edge computing unit, through convolutional neural network model, multi-level feature extraction is carried out to food material image, and food material category and subdivision category are identified;Database module, built-in latest version Chinese food composition table, stores the nutrient component data of each kind of food material per 100 grams;Calculation module, according to the weight data output by weighing module and the food material category identified by image recognition module. Through the linkage of image recognition and weighing module, the synchronous acquisition of food material category and weight is realized, non-professional personnel can operate independently, the evaluation efficiency is improved by more than 70%, long-term data accumulation and trend analysis are supported, help parents to master children's nutrition status comprehensively, avoid phase nutrition imbalance.

This invention relates to the field of medical device technology and provides a method, system, and medical device for measuring peak cough flow rate. The method includes real-time acquisition of inspiratory and expiratory flow rate signals and airway pressure signals; monitoring changes in the expiratory flow rate signal to identify burst cough events and lock a cough analysis window; calculating the difference in inspiratory and expiratory flow rates within the cough analysis window to obtain a baseline cough flow rate sequence; calculating the airway pressure signal within the cough analysis window using a system leakage factor to obtain a leakage flow rate compensation sequence; determining coefficients based on the ratio of tubing and patient airway resistance parameters and multiplying the expiratory flow rate signals to obtain a tubing resistance compensation sequence; superimposing the above sequences to obtain a corrected flow rate sequence; and extracting extreme value features and evaluating the effectiveness of the corrected flow rate sequence generated after a preset number of iterations to determine the peak cough flow rate value. This invention solves the problems of inaccurate and inefficient measurement results in existing peak cough flow rate measurements.

The application discloses a geothermal caprock multi-factor coupling evaluation system, which aims to solve the problems of low standardization degree of existing evaluation manual operation process, lack of unified engineering architecture of multi-factor coupling and insufficient result visualization. The application automatically executes caprock comprehensive evaluation on a unified platform through a data acquisition module, a single-factor evaluation module, a coupling model construction module, a coupling score calculation module, a comprehensive evaluation module and a result output module. The system completes single-factor scoring based on basic data, constructs and calculates the scores of four coupling subsystems of lithology-diagenesis-physical property, structure-mechanics-integrity, thickness-continuity and fluid-pressure-temperature, quantifies the coupling relationship between the subsystems by using a cross influence matrix to obtain the final score, and outputs the comprehensive score and the visualized result after weighting. The application realizes the integration and automation of the evaluation process, supports the engineering landing of complex coupling models, and improves the result visualization and decision support capability.

This invention provides a system for evaluating the breakthrough pressure of temporarily plugged chemical bridge plugs, comprising: a high-temperature oven; a breakthrough pressure main device for holding the base fluid of the temporarily plugged chemical bridge plug, which can be arranged inside the high-temperature oven, the breakthrough pressure main device having an inlet pipeline and an outlet pipeline; a horizontal flow pump for injecting a displacement medium, the horizontal flow pump being connected to the inlet pipeline; a first pressure sensor and a second pressure sensor respectively installed on the inlet pipeline and the outlet pipeline; a pressure sensor workstation connected to the first pressure sensor and the second pressure sensor for recording the data measured by the first pressure sensor and the second pressure sensor; and a camera for capturing the breakthrough process of the temporarily plugged chemical bridge plug. This invention also provides a method for evaluating the breakthrough pressure of temporarily plugged chemical bridge plugs.

The application discloses an AI-based health risk assessment and intelligent grading method and system, and relates to the fields of artificial intelligence, health management and big data analysis.The system comprises a data acquisition and preprocessing module, an AI risk assessment model, a personalized suggestion generation module and a user interaction and interface module; the method collects multidimensional data such as physiological indexes, physical examination reports, lifestyles, genetic heredity, medical histories and wearable devices, inputs the data into an AI model after preprocessing, automatically calculates the weights of dynamic indexes and generates a quantitative score, maps the score into a three-level action orientation grade such as a suggestion for medical treatment, regular review and daily attention, outputs personalized guidance, department recommendations and disease early warning in combination with a user portrait, and supports third-party integration and model closed-loop optimization.The application realizes panoramic and accurate insight, dynamic tracking and personalized management of health risks, has high efficiency and can be scaled up, and provides scientific decision-making support for users, medical institutions and insurance companies.

The application discloses a kind of active implantable medical device in-vivo radio frequency response modeling method based on equivalent lumped element model, by constructing and matching the electromagnetic characteristics of the actual conductive path of AIMD and surrounding tissue, equivalent lumped element model (LEM), the key factors such as the multiscale electrical characteristics of the geometry size of implantable medical device and its in homogeneous, non-uniform even real anatomic tissue environment are parameterized characterization, so as to quickly and accurately reconstruct the radio frequency transfer function of implant.The method of the application effectively breaks through the bottleneck of the existing Tier 3 evaluation method, meets the technical requirements of the latest standard based on Tier 4 evaluation method for modeling the radio frequency transfer function of implant in the environment closely related to clinical tissue, and provides a new technical path and implementation means for efficient and accurate evaluation of the radio frequency heating risk of implantable medical device in the magnetic resonance environment.

The application discloses a capital construction subcontractor project input evaluation method based on large model retrieval enhanced generation, which constructs a personnel portrait library, a team portrait library and a capital construction subcontractor portrait library based on manager dimension data, construction personnel dimension data and capital construction subcontractor dimension data, evaluates the portrait data in each portrait library of the large model and the expert scoring rule to evaluate the manager input score and the construction personnel input score of the capital construction subcontractor, and obtains a project input comprehensive score based on the manager input score and the construction personnel input score. By fusing the expert scoring rule and the reasoning ability of the large model, the consistency of the evaluation standard is ensured, the evaluation result is more objective and accurate, and the evaluation efficiency is also significantly improved. Moreover, the evaluation large model is obtained by fusing the expert scoring rule into the initial large model based on the retrieval enhanced generation technology, the retrieval enhanced generation technology can provide detailed scoring reasons for each score, so that the evaluation result is more persuasive.

This invention relates to the fields of biomolecule synthesis technology and artificial intelligence technology, specifically disclosing a method and apparatus for assessing the synthesizability of biomolecules based on reinforcement learning. The method includes: acquiring a preset dataset; merging the preset dataset to generate a merged dataset; performing structural verification and repair operations on the merged dataset to generate a corrected dataset; extracting bioaccessibility features from the corrected dataset to generate a bioaccessibility database; scoring the synthesis paths of the molecules to be analyzed based on a multimodal fusion scoring model and the bioaccessibility database, and determining the optimal path; and performing similarity clustering and replacement on the unsynthesized molecules in the optimal path to optimize the synthesis path. Through systematic data processing, multimodal feature fusion, reinforcement learning path search, and similarity replacement, efficient and accurate synthesis path assessment is achieved.

This invention relates to the field of power system control technology and discloses a method for assessing the safety domain of a DC sending-end system under transient overvoltage constraints. The method establishes an equivalent model of the sending-end power grid under operating conditions; constructs a transient equivalent model of the sending-end power grid after blocking; derives an analytical expression for the peak value or upper limit of transient overvoltage after DC blocking of the converter bus based on node reactive power balance relationships, voltage sensitivity relationships, or equivalent impedance relationships; simplifies the complex multi-node power grid into a multi-region or single-port equivalent network suitable for analytical calculation; constructs a safety discrimination function based on the analytical expression and a preset voltage safety threshold, using AC system short-circuit capacity, DC active power, and renewable energy active power as coordinate axes, thereby obtaining the transient voltage safety domain boundary surface; and outputs the assessment results. The advantage of this invention is that it enables rapid assessment of the safety boundary of the sending-end power grid operation.

This invention discloses a method and apparatus for operational risk assessment based on multidimensional data. The method includes: acquiring operational information of a target device, including basic attribute information, real-time status information, and wear and tear maintenance information; determining whether the target device meets preset basic operational assessment conditions based on the operational information; and if so, determining the operational risk assessment result corresponding to the target device based on the operational information and the preset operational assessment conditions. Therefore, this invention can intelligently realize the function of equipment operational risk assessment, which is beneficial to improving the comprehensiveness and scientific nature of the equipment operational risk assessment method, thereby improving the accuracy and reliability of the determined operational risk assessment results, and also improving the efficiency and convenience of determining the operational risk assessment results.

This application discloses a method, system, and electronic device for evaluating large-scale models. The method includes: acquiring a target regulatory document and performing semantic parsing on the target regulatory document based on a structured mapping method between the target large-scale model and regulatory semantic fragments; generating a corresponding test evaluation scheme based on the parsing results; constructing test cases corresponding to the test evaluation scheme; and performing compliance evaluation tests on the large-scale model to be evaluated based on the test cases, generating evaluation results. The technical solution provided by this application achieves the unification of the test evaluation scheme and evaluation execution, effectively solving the problem of low efficiency in regulatory compliance assessment caused by large differences in regulations under cross-border and multi-regulatory environments, thus improving the efficiency of model compliance evaluation.

The application relates to the technical field of data processing, in particular to a code reordering processing method and system. A plurality of candidate codes are generated based on requirements; a plurality of indexes are set for each candidate code; each index is tested based on an execution channel to generate an execution result vector of each candidate code; each index is tested for deviation to set a deviation value of each index; an equivalent cluster of each candidate code is constructed; an execution score of each candidate code is calculated based on the deviation value and the execution result vector; each candidate code is tested based on an inference channel to output an inference score of each candidate code; a mixed score is calculated, and each candidate code is reordered based on the mixed score and the equivalent cluster. The application overcomes the inference illusion problem of a large language model when generating codes through a double-channel scoring system, and improves the quality of code generation.

The application provides a chip end face image definition evaluation method and system based on semantic information, comprising: obtaining a chip end face image to be evaluated; inputting the chip end face image to an image degradation feature extraction module, extracting the degradation features of the image and performing global average pooling processing, and obtaining a guide vector through MLP network mapping; constructing an adaptive prompt word pair, processing the image to be evaluated through an image encoder to obtain an image feature vector, and simultaneously processing the adaptive prompt word pair through a text encoder to obtain a prompt word feature vector; calculating the definition score of the image to be evaluated through a Softmax function and comparing it with a preset threshold to obtain a determination result. The application overcomes the problem that the picture definition evaluation scale is not the same under the condition that the texture quantity and density are different, and makes the evaluation score only depend on the overall definition of the picture, so as to avoid the problem that the definition of the defects at different focal depths of the chip end face image causes the score to be biased and leads to inaccuracy.

This invention discloses a data processing method, apparatus, computer-readable storage medium, and computer device. The method involves acquiring statistical data in at least two dimensions related to GDP information for each grid cell; generating at least two graph structures based on the positional relationships between grid cells and the statistical data; constructing a graph neural network model based on the at least two graph structures; determining the feature vector corresponding to each grid cell based on the graph neural network model; training a preset regression model based on the first feature vectors corresponding to a preset number of first grid cells and first GDP information; and calculating the target GDP corresponding to the target region based on the trained regression model. Thus, by employing machine learning methods, training a network model based on grid cells with partially known GDP, and then using the trained network model to predict the GDP of other grid cells, the efficiency of assessing the level of regional economic development can be improved.

The application discloses a model evaluation method and device and electronic equipment, and relates to the technical field of audio data processing. The method comprises the following steps: obtaining M first audio signals synthesized by using a first to-be-evaluated speech synthesis model, and obtaining N recorded second audio signals; performing voiceprint extraction on each of the M first audio signals to obtain M first voiceprint features; performing voiceprint extraction on each of the N second audio signals to obtain N second voiceprint features; clustering the M first voiceprint features to obtain K first center features; clustering the N second voiceprint features to obtain J second center features; counting the cosine distance between the K first center features and the J second center features to obtain a first distance; and evaluating the first to-be-evaluated speech synthesis model based on the first distance. According to the technology of the application, the evaluation efficiency of the first to-be-evaluated speech synthesis model can be improved.

This application discloses a method and apparatus for evaluating and processing retrieved presentation documents. The method includes: parsing the presentation document to obtain its text information, visual elements, and structural information, wherein the text information includes presentation text and / or presentation notes; performing multi-dimensional evaluation processing based on the text information, visual elements, and structural information to obtain at least two of the following: a text-image separation evaluation result, a context integrity evaluation result, a structured degree evaluation result, and an information density to noise ratio evaluation result; and weighting at least two of the following: a text-image separation evaluation result, a context integrity evaluation result, a structured degree evaluation result, and an information density to noise ratio evaluation result, to obtain a comprehensive evaluation result for the presentation document.

This invention discloses a method and system for identifying the state of transmission lines, applied in the field of transmission line technology. The method includes: acquiring multi-dimensional historical data of a target transmission line; analyzing the trend characteristics of each dimension of historical data and the correlation characteristics between the historical data of each dimension, processing the trend characteristics and correlation characteristics to obtain the risk result of the target transmission line, and determining high-risk points based on the risk result; acquiring multi-dimensional real-time electrical data of the high-risk points, performing correlation analysis on the multi-dimensional real-time electrical data to determine the initial fault state; determining the first state identification result of the high-risk points; inputting the acquired real-time multimodal image data of the target transmission line into a pre-constructed fault state identification model to obtain the second state identification result, thus obtaining the state identification result of the target transmission line. The method and system for identifying the state of transmission lines provided by this invention effectively improve the efficiency of state identification of transmission lines.

This invention relates to the field of testing and evaluation of autonomous driving systems, and more particularly to a method for evaluating the intelligence level of autonomous vehicles based on a large language model's subjective-objective mapping. This method addresses the shortcomings of traditional evaluation methods in terms of objectivity, efficiency, and nonlinear fitting capability. The method includes the following steps: converting autonomous driving interaction data into natural language descriptions; constructing a knowledge base for the autonomous driving domain and enhancing the large language model to improve its understanding of professional rules; using the enhanced large language model to quantitatively evaluate the interaction data across multiple dimensions (safety, comfort, efficiency, social interactivity, and impact on the traffic system); and employing a multilayer perceptron to construct a nonlinear mapping model from interaction data to intelligent scoring, achieving efficient and objective comprehensive evaluation. This invention effectively reduces reliance on human experts, improves the consistency and efficiency of evaluation, and is applicable to the comprehensive evaluation of the intelligence level of autonomous driving systems at different levels.

This invention discloses a real-time assessment method for hotspot stress response of floating platform structures based on wave and stress monitoring. The method includes: acquiring measured stress response spectra and wave monitoring parameters; determining optimal wave direction parameters based on the measured stress response spectra and a pre-established structural dynamic response database; matching the optimal wave direction parameters to obtain a first target stress response amplitude operator for a reference measuring point and a second target stress response amplitude operator for fatigue hotspots; performing wave spectrum inversion on the measured stress response spectra using the first target stress response amplitude operator; calculating statistical values ​​of the inverted wave spectrum; and eliminating inverted wave spectra with large errors based on the wave monitoring parameters of the target floating platform and the statistical values; and obtaining the target stress response spectrum of fatigue hotspots based on the second target stress response amplitude operator and the calibrated inverted wave spectrum. This invention can acquire the stress response spectrum of hotspots that are difficult to monitor directly in real time and can be used for the safety assessment of floating platform structures.

This invention provides a multi-dimensional dynamic monitoring and early warning method and system for smart device security. The method includes continuously monitoring all operations and state changes of the smart device in real time, digitizing its behavior to form a device behavior sequence, and identifying abnormal sequences that deviate from the normal behavior pattern of the smart device. A preset smart home scenario logic is transformed into a predictive path model for security analysis, and this model is compared with the abnormal sequences. The causal chain of the TTP knowledge graph is used to determine whether the abnormal sequences constitute a security risk. The comparison results and security risk status are presented intuitively in the form of a heatmap to show the risk distribution and intensity of devices or areas. It can also integrate the analysis of unprotected major disaster types generated by TTP prediction and the protection effect diagram based on the ATT&CK framework. This invention solves the problems of low efficiency, incomplete coverage, and limitation to "single-point alarms" in existing smart home security solutions.

This specification provides a method, apparatus, device, medium, and product for evaluating a model. The scheme may include: inputting a visualization page generation instruction and a test sample into a model to be evaluated, and obtaining the output result of the model to be evaluated; performing functional verification on the model to be evaluated based on the output result, and obtaining a first verification result; if the first verification result indicates that the model to be evaluated can generate page code that meets preset requirements, then rendering the generated page code to obtain the visualization page; performing visualization component quality verification on the rendered visualization page, and obtaining a second verification result; performing content quality verification on the rendered visualization page, and obtaining a third verification result; and evaluating the model to be evaluated based on the first verification result, the second verification result, and the third verification result.

The present application relates to the technical field of tunnel engineering, and particularly relates to a tunnel lining long-term safety evaluation method based on a PSO-SA hybrid algorithm, comprising: determining a surrounding rock creep constitutive model and obtaining initial surrounding rock parameters through an inversion algorithm; introducing the influence of a supporting structure on surrounding rock deformation to obtain corrected surrounding rock parameters, so as to improve authenticity; based on time-varying factors, iteratively updating surrounding rock parameters and lining parameters to realize dynamic evaluation of long-term safety; inputting the iteratively updated surrounding rock parameters and lining parameters into numerical analysis software to obtain stress and deformation characteristics of the lining structure through the numerical analysis software; and evaluating the long-term safety of the tunnel lining structure according to the stress and deformation characteristics and relevant specifications, wherein the application constructs a dynamic evaluation model that truly reflects the time-varying characteristics of the tunnel structure, brings about a qualitative leap in evaluation accuracy, reliability and foresight, and provides strong technical support for the long-term safety of operating tunnels.

This invention relates to a method and system for assessing the lifespan of steam turbine blades. The method includes the following steps: S1, acquiring vibration and rotational speed signals of the steam turbine blades; S2, obtaining the actual vibration value V1 of the steam turbine blades based on the vibration and rotational speed signals; S3, using the actual vibration value V1 as a fatigue reference for assessing the steam turbine blades to obtain the remaining lifespan y of the steam turbine blades. This invention effectively improves the reliability, stability, and accuracy of lifespan assessment for steam turbine blades, especially the last-stage blades of nuclear power steam turbines. It enables data collection and real-time lifespan assessment of steam turbine blades under any operating condition, while simplifying the process of assessing the lifespan of each turbine blade and improving assessment efficiency.

This invention proposes a method and system for assessing the quality of spatiotemporal information contained in crowdsourced sensing data, aiming to solve the problems of fragmented quality factors and the lack of a unified cross-modal assessment framework in existing technologies. The method includes: Step S1, constructing a common and individual cross-modal quality factor system. Common factors cover richness, accuracy, timeliness, and reliability, while individual factors adapt to six types of multimodal data features, including professional spaces and IoT sensing. Step S2, by integrating spatiotemporal statistical natural language processing, deep learning, and other technologies, designing differentiated algorithms to achieve automated extraction and calculation of quality factors. Step S3, based on the entropy weight method, completing factor normalization, objective weighting, and comprehensive scoring, dividing the data into four quality levels. This invention achieves a unified and accurate assessment of the quality of spatiotemporal information contained in multimodal data, supports cross-type quantitative comparison, and provides core support for high-quality data source selection and the construction and updating of spatiotemporal knowledge graphs.

The application discloses a fly ash backfill field groundwater pollution risk assessment method based on a double-module analytical model, and comprises the following steps: obtaining geological parameters, hydrological parameters and pollutant parameters of a backfill field area; constructing a vadose zone pollutant migration model based on the parameters, and calculating the concentration of the pollutant when the pollutant enters an aquifer; taking the output as the input, constructing an aquifer pollutant migration model, and predicting the pollutant concentration at a target sensitive point; comparing the predicted concentration with a groundwater quality standard value, and judging whether the groundwater pollution risk is controllable; determining a risk sensitive area based on the simulation result, and identifying key control parameters affecting the pollutant migration. The application adopts a double-model series analytical calculation method, simplifies the operation process, improves the accuracy and consistency of the risk assessment, and is suitable for groundwater pollution risk prediction and control of a fly ash backfill field.