197 results about "Assessment evaluation" patented technology

A method for evaluating textual output of one or more machine-learned language models is presented. The method includes receiving, from a user of a client device, a first prompt for input to one or more machine-learned language models, providing the first prompt to the one or more models for execution, and receiving a set of generated responses to the first prompt from the one or more models. The method further includes generating a user interface (UI) on the client device displaying the first prompt and generated responses as a table user interface element. The method applies a selected evaluation function to the generated response to evaluate the response with respect to an evaluation objective and identifies words that influence the evaluation. The method generates one or more UI elements on the UI to display the results of the evaluation for the generated responses.

The invention discloses a fall risk real-time assessment system and method based on big data, and relates to the field of risk assessment, and the system comprises a data collection and preprocessing module, a big data processing and integration module, a feature extraction and selection module, a fall risk assessment module and a real-time monitoring and early warning module which are sequentially connected and cooperatively work. Wherein the data acquisition and preprocessing module is responsible for acquiring data from a plurality of sources and converting the data into digital signals; the big data processing and integration module is responsible for secure transmission, convergence and preprocessing of data; the feature extraction and selection module is responsible for extracting features related to the falling risk from the preprocessed data; the tumble risk assessment module is responsible for real-time assessment of tumble risks based on the extracted features; and the real-time monitoring and early warning module is responsible for triggering an early warning signal according to the falling risk assessment result. According to the invention, accurate and real-time evaluation of the falling risk, accurate and timely output of the evaluation result and rapid response of the early warning signal are realized.

The invention discloses a power market user load prediction method, system and device and a medium, and relates to the technical field of power market user load prediction, and the method comprises the steps: collecting and preprocessing power market user load data, and dividing the preprocessed data into a training set and an evaluation set; and constructing a user load prediction model based on LSTM and dual Q network optimization, and inputting the training set to carry out single-step prediction. And evaluating the power market user load prediction model based on the evaluation set, and after the evaluation is passed, inputting future prediction data to the user load prediction model to obtain a predicted power market user load. According to the method, the external variables influencing the power load can be more comprehensively captured, so that the accuracy and the reliability of the prediction model are improved. And an LSTM network is combined with a double Q network model, so that the recognition capability of the model on the long-term trend is enhanced, and the accuracy of a prediction result and the generalization capability of the model are improved.

The invention relates to the technical field of computer data processing, in particular to a multi-model collaborative distillation and dynamic fine tuning model training method and system. The method comprises the steps that data collection is conducted, unlabeled data are input into a model to be made into labeled data, the labeled data and labeled data are integrated into a data set, and then the data set is divided into a training set, a verification set and a test set; inputting the training set into the model, guiding the model to generate extended data by cue words, and training a student model by using an extended training set; the student model is evaluated on the verification set, if the evaluation result shows that the evaluation index of the student model does not reach the expected value, error information is input into the model for analysis and data generation, and then the student model is adjusted until the evaluation index of the student model reaches the expected value; the method has the advantages that multiple large language models are used for collaborative distillation, training data are richer and more diversified, student models are more accurate, and the student models are circularly and dynamically fine-tuned, so that the models are higher in precision and adaptability.

Systems and methods for measuring, grading, evaluating, and comparing AI models via a graphical user interface are disclosed. The technology obtains a set of application domains of the AI model in which an AI model will be used. The application domains are mapped to one or more guidelines to determine a set of guidelines that define operational boundaries of the AI model. The guidelines are used to generate assessment domains, each associated with specific benchmarks that include indicators of a degree of satisfaction with the guidelines. For each assessment domain, assessments are constructed to evaluate the AI model's degree of satisfaction with the corresponding guidelines. The AI model is then evaluated against the assessments. Based on these comparisons, grades are assigned to the AI model for each assessment domain. The application-domain-specific grades are generated and displayed at a GUI, reflecting the AI model's degree of satisfaction with the guidelines.

Embodiments of the disclosed technologies are capable of evaluating content recommendations. The embodiments describe creating a prompt using a search query and a content recommendation output by a machine learning model in response to the search query. The embodiments further describe causing a LLM to generate an evaluation of the content recommendation and the search query using the prompt. The evaluation includes a relevance score of the content recommendation and the search query. The embodiments further describe training the machine learning model to generate an updated content recommendation in response to the search query. The training includes using the relevance score of the content recommendation and the search query.

The invention relates to the technical field of training simulation, and discloses a VR-based gas safety emergency training system, which comprises a three-dimensional scene construction module, an interactive data acquisition module, an interactive data processing module, an examination data analysis module and an examination evaluation module, entity drilling is replaced, the same scene can be repeatedly trained for infinite times, and the training cost is remarkably reduced; the VR technology provides multi-sensory stimulation, the intuitive cognition of students on danger is enhanced, the safety awareness and the emergency response capability are effectively improved, and no danger exists; by collecting operation data of students, the system automatically calculates key coefficients such as equipment operation precision, process compliance, disposal timeliness and path planning rationality, and scientific quantification and accurate scoring of training effects are achieved; and automatic grading evaluation is carried out according to a grading result, and a customized remedy module is triggered for students with insufficient abilities, so that a'training-assessment-intervention 'closed loop is formed, and the overall training efficiency is improved.

The invention provides a multi-modal large model question and answer evaluation system based on a unified platform and benchmark. The system comprises a visual question and answer evaluation platform, a question and answer benchmark based on a unified capability framework and an evaluation strategy based on a large language model. The visual question and answer evaluation platform is a unified platform which is based on concurrency control and supports multi-modal data; the systematic evaluation of the model performance is realized through a standardized data structure and task design according to the homemade question and answer benchmark; the evaluation strategy scores the answers based on multiple independent scores and a semantic comparison mechanism. According to the method, efficient task scheduling and stable performance expression are realized, and the requirements of a high-load evaluation scene can be met; systematic evaluation of different model performances is realized, and all core capabilities required by questions and answers of owners are covered. And the answers are scored based on multiple independent scoring and a semantic comparison mechanism, so that the scoring accuracy and consistency are improved, and the limitation of a traditional evaluation method in processing complex answers is overcome.

Methods and apparatus are provided for automated analysis and verification of plumbing code compliance in architectural design plans using artificial intelligence (AI). The system analyzes design plans, such as floor plans or architectural drawings, to identify, classify, and evaluate the placement, type, and number of plumbing fixtures, including water closets, sinks, and showers. The AI engine assesses these fixtures against applicable building and plumbing codes, evaluating spatial relationships, clearances, and pipe configurations. Where non-compliance is detected, the system offers automated suggestions for design revisions and optimizations, providing code adherence and functional efficiency before construction begins. The apparatus includes interactive tools for real-time simulation and collaboration, enabling designers, architects, and code compliance officers to make informed adjustments to the design.

The present invention relates to a workflow for chart review and audit of natural language medical text. More specifically, the present invention uses Knowledge Graph to find the ICD-10-CM Codes and MEAT (Monitor, Evaluate, Assess and Treat) evidence for a given diagnosis. The present workflow also provided for feedback collection and consolidation. The present system, instead of processing OCR for all pages, pre-processes to identify the pages that need OCR (i.e., which are the pages containing non-machine readable text—either in full page or partial page—are determined) and passed to the OCR engine. This approach reduces the time, cost and errors associated with the OCR process.

The invention discloses an employee ability growth navigation and resource recommendation system and method, and relates to the technical field of employee growth navigation and resource recommendation. Comprising a learning map construction module, a multi-modal ability evaluation module, a dynamic navigation engine, a resource recommendation module, a digital twinborn training module and a user interaction module. A learning map construction module; the multi-modal fusion realizes' voice-text-image-equipment 'four-dimensional evaluation, the evaluation dimension is expanded from traditional 3 items to 8 items, and the evaluation accuracy of the cross-department cooperation capability and the fault decision-making capability is improved; the assessment weight is dynamically adjusted through reinforcement learning, the technical trend matching degree is improved, the assessment period is shortened to the hour level from the quarterly level, and the talent inventory efficiency is improved; a composite fault scene is dynamically generated, practical training pertinence is improved, and the processing success rate of employees in a multi-equipment linkage failure scene is improved.

Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess, evaluating one or more target attributes of each object, assessing usability of each object using its target attributes' evaluations and each room using its objects' assessment and other room information with respect to an indicated purpose, and combining the assessments of multiple rooms in a building and other building information to assess usability of the building with respect to its indicated purpose.

The invention provides a digital beauty teaching system based on artificial intelligence, and the system comprises a learning condition collection and analysis module which is used for collecting learning condition data, constructing a student file, and carrying out the calculation to obtain a learning condition comprehensive index; the course planning and recommendation module is used for performing course recommendation, learning planning, course dynamic adjustment and cross-domain course recommendation; the intelligent tutoring and question answering module is used for constructing an error type database and an operation diagnosis model and carrying out diagnosis analysis and intelligent question answering on real-time operation; the learning condition evaluation module is used for constructing an AI scoring model and carrying out evaluation on real-time homework; and the visualization and adjustment module visually displays the learning condition evaluation result and dynamically adjusts the homework improvement suggestions and the recommended courses. The system can quantify the overall learning participation degree and expression level of students, accurately analyze the learning condition, accurately recommend courses, intelligently diagnose common errors, generate improvement suggestions, and score works, so that the scoring result is more accurate, and efficient proceeding of beauty teaching is promoted.

The invention discloses a method and device for improving the fine tuning effect of a large model based on an iterative data enhancement strategy. The method comprises the following steps: manually generating a batch of seed data with different distributions according to requirements; enhancing artificially generated seed data based on a rule or a large model; checking the quality of the enhanced data; finely adjusting the model by using the checked data, and reasoning training data by using the trained model; performing comprehensive evaluation on the reasoning result in various aspects; whether the evaluated indexes meet requirements or not is judged; if the error sample does not meet the requirement, enhancing the error sample again, and iterating repeatedly; and if the evaluation result meets the requirement, ending the whole process. According to the method, the threshold of fine adjustment of the large model under the small data set is remarkably reduced, and the model is excellent in performance in a data scarce scene by generating the targeted synthetic data.

The invention provides a reserve land development potential grading evaluation method and system based on pattern spot data, and relates to the technical field of reserve land development management, and the method comprises the steps: carrying out the pattern spot data mining of reserve land, and obtaining an original pattern spot data set with pattern spot attribute information; performing multi-level classification and layering according to a spatial planning hierarchical relationship, and extracting a potential constructable base range; performing pattern spot spatial topology processing, extracting pattern spot geometric feature parameters, and performing pattern spot scale division based on a preset area threshold value; establishing a pattern spot potential evaluation index system, and performing pattern spot development potential category division; and executing the refined extraction of the available space to form a visual board for the reserve land. The technical problems that in the prior art, the development potential of the reserve land is evaluated by depending on manual judgment and a rule-based simplified evaluation model, the evaluation precision is insufficient, the development potential of the land cannot be comprehensively reflected, and the scientificity and rationality of a development decision are further influenced are solved.

Regarding MS information, information about each of a plurality of MS's includes meta information of the relevant MS. Regarding model information, information about each of one or a plurality of models includes meta information of the relevant model. A system evaluates appropriateness of an evaluation destination MS / model for an evaluation source MS / model as a replacement MS / model for the evaluation source MS / model on the basis of the meta information of the evaluation destination MS / model and the meta information of the evaluation source MS / model. The system recommends one or more evaluation destination MS's / models, as a candidate for a replacement MS / model of a designated MS / model, to a user on the basis of evaluation of each of one or two or more evaluation destination MS's / models regarding which the MS / model designated by the user in an application configured from one or two or more MS's / models is the evaluation source MS / model.

The invention discloses a massage effect evaluation method and system, and the method comprises the following steps: S1, data collection: obtaining a plurality of physiological parameters; s2, data preprocessing: carrying out filtering, normalization and feature extraction processing on the physiological parameters; s3, effect evaluation: inputting the data after feature extraction into an effect evaluation model, and adaptively outputting an evaluation result by the effect evaluation model according to the massage manipulation; and S4, optimization iteration: optimizing the effect evaluation model by adopting a gradient descent method so as to improve the evaluation effect. The massage effect is evaluated by fusing the EMG feature, the skin temperature feature, the pressure distribution feature, the HRV feature and other parameter data, and the evaluation effect is more accurate.

According to the child brain development assessment and training system, method and device and the storage medium, parents or guardians can conveniently perform preliminary assessment on the brain development of children at home in an intelligent interaction mode. The evaluation report not only can provide scores of the children in various development fields, but also can give targeted education training suggestions, so that an online consultation platform is provided for families with further questions, and parents or guardians are helped to better guide and support the development of the children; in addition, the system has the advantages of being easy to operate, low in cost, wide in application range and the like. Parents or guardians do not need professional background knowledge and only need to complete evaluation according to system prompts, and a professional brain development evaluation preliminary result can be obtained. Meanwhile, the system is also suitable for various family environments, and parents or guardians can carry out testing at home in good time without reserving professional institutions or waiting for visits of professionals.

The invention discloses a method for constructing an effect evaluation model based on meteorological early warning service quality, and relates to the technical field of meteorological early warning service quality evaluation, and the main scheme is as follows: calculating a structural dimension index of a precipitation field by analyzing forecast precipitation intensity data and observation precipitation intensity data; performing grade evaluation on the structural dimension index through a grade division model, and analyzing forecast occurrence time data and actual occurrence time data to obtain a timeliness score; a public influence degree score is obtained through the early warning level data, the actual occurrence position data and the received data of the mobile phone users in the urban area and the remote area, the structural dimension comprehensive score, the timeliness comprehensive score and the public influence degree score are comprehensively analyzed, and a comprehensive quality score is obtained; and summarizing the assessed contents into a comprehensive assessment report, thereby solving the problems of single assessment mode, lack of comprehensive assessment and poor assessment authenticity in the prior art.

The invention particularly relates to an evaluation task formulating method based on multiple levels. According to the evaluation task formulation method based on the multiple levels, a data index management module collects data and customizes data indexes for an assessment and evaluation system; the assessment index model management module pre-configures assessment indexes and data indexes contained in the assessment indexes for the assessment evaluation system, configures a group of data indexes for an assessment index model according to business requirements, and configures names and descriptions of the assessment index model; an evaluation task is newly added, evaluation task information is set, then a pre-configured assessment index model is imported, and assessment index information is configured in the newly added evaluation task; and storing and issuing the configured evaluation task, and starting an evaluation process. According to the evaluation task formulating method based on the multiple levels, the efficiency and accuracy of evaluation task formulating are improved through a standardized and systematized configuration process, and the evaluation task formulating method has wide application prospects and remarkable actual benefits.

The invention belongs to the technical field of pilot ability assessment, and particularly discloses a pilot ability assessment method based on dynamic time warping and hierarchical clustering, which comprises the following steps of: acquiring eye movement data of a tested pilot in a flight simulation task process, preprocessing the eye movement data, extracting behavior indexes of each stage of a flight task, and calculating a pilot ability assessment result; generating a fixation area number sequence according to the fixation point position; in the selection target evaluation stage, a dynamic time warping algorithm is used for carrying out nonlinear alignment on the gaze sequences of all the pilots, and an eye movement difference degree matrix between the pilots is generated; based on the difference degree matrix, adopting a hierarchical clustering algorithm to group the pilots; and outputting an ability evaluation result of the pilot according to the distribution of the pilot in the difference degree matrix and the deviation information of the pilot and the teacher watching sequence. According to the method, structured comparison and capability grade evaluation of complex cognitive behaviors can be realized, and an evaluation result has relatively high objectivity and interpretability.

The invention provides a crane health assessment method and system. The method comprises the following steps: acquiring data of a crane in a working state; performing health assessment based on the collected data and a health assessment model; and obtaining quantized data based on an evaluation result, and performing maintenance guidance based on the quantized data. According to the system, the use condition of the crane can be monitored in real time, the states of main structural parts and key parts of the crane can be analyzed and evaluated, the health condition of the crane can be evaluated, quantitative data guidance is provided for equipment maintenance, and production and maintenance departments can predict the equipment condition in advance, so that maintenance or part plans can be arranged in a targeted manner.

A refractive index distribution evaluation method, evaluation device, and information processing program, comprising: a data acquisition step or a data acquisition unit for acquiring refractive index distribution data for an object of observation; a selection step or a selection unit for selecting whether a target included in the refractive index distribution data is an evaluation target; and an evaluation step or an evaluation unit for evaluating the refractive index distribution of the evaluation target.

The invention relates to the technical field of sailor information processing, and particularly discloses a sailor performance assessment evaluation method, device and equipment based on multivariate information, and the method comprises the steps: S1, selecting a performance assessment tool according to the work responsibilities and requirements of sailors, and determining an applicable assessment index design principle; s2, collecting multivariate information related to the assessment indexes, and comprehensively considering information of sailors in all aspects to establish an evaluation index system; s3, allocating a corresponding weight to each index, and evaluating and scoring each assessment index according to the collected information and weight allocation; according to the invention, comprehensive consideration is carried out by utilizing multivariate information related to the performance of the sailors, evaluation suggestions of direct supervisor, colleague, subordinate and clients of the sailors are comprehensively considered, and the performance of the sailors is evaluated in combination with the formulated performance evaluation index system and standard, so that the performance and ability of the sailors are comprehensively evaluated, and the evaluation efficiency is improved. Meanwhile, the excellent performance of sailors can be better accepted and complemented, and the sailors are stimulated to continue to work.

To provide an evaluation method which can evaluate personal characteristics of an evaluation object person such as resistance to a thermal load and a load by the work, and evaluate an environmental load due to a working environment in a place where the evaluation object person is working, and evaluates a physical condition risk of the evaluation object person from the personal characteristics of the evaluation object person and the environmental load, and an evaluation system which evaluates the physical condition risk of the evaluation object person.SOLUTION: A first personal characteristics evaluation method disclosed in the present invention is the personal characteristics evaluation method for evaluating the personal characteristics of an evaluation object person by a computer that operates with a computer program, and performs the characteristics evaluation for any of the physical strength characteristics, life rhythm and recovery degree of the evaluation object person on the basis of heart rate data and acceleration data of the evaluation object person acquired by a measurement device 11.SELECTED DRAWING: Figure 1

The invention provides an employee work assessment recommendation method and system based on a collaborative filtering algorithm, and relates to the technical field of employee work assessment, and the method comprises the steps: extracting a task dependency relationship and time consumption data from a project management system, and constructing an employee task dependency graph; secondly, collecting and analyzing work interaction information containing document operation and task marking features, and identifying task switching critical points to generate quantitative indexes; constructing a similar employee group and extracting an efficient working mode by means of a collaborative filtering algorithm after establishing an evaluation data set through space-time alignment of the two; by taking the task dependency graph as an environment state and the efficient mode as a reference, generating a task sequence optimization scheme by using a reinforcement learning model; according to the scheme, the staff group composition is adjusted according to the scheme execution effect, the optimization model is fed back, finally, a comprehensive evaluation result is generated based on the scheme and actual task sequence matching degree and the quantitative index stability, the task sequence optimization and physiological state adjustment ability can be accurately evaluated, and the work assessment scientificity and the task execution efficiency are improved.

The present invention relates to a dynamic evaluation model and implementation method for the value of data elements, which belongs to the field of data assets, including quality evaluation: evaluating the quality of data elements; value evaluation: evaluating the value generated by data elements in the market in actual applications; risk evaluation: evaluating the risks that may be generated by data during use; comprehensive evaluation: combining the evaluation results of the data element quality evaluation module, the data element market application evaluation module and the data element value risk evaluation module, performing a correlation analysis of the quality, market application and risk of the data elements through a neural network, assigning corresponding weights to them, and using a weighted average formula to obtain a comprehensive evaluation result. The present invention can comprehensively and dynamically reflect the value status of data elements, ensuring the comprehensiveness and accuracy of the evaluation results.

The invention discloses a newborn congenital heart disease screening method based on tandem mass spectrometry, and the method comprises the following steps: 1, collecting heel blood tandem mass spectrometry data of newborns subjected to echocardiography examination after birth, and preprocessing the data; 2, performing feature extraction on the data collected and preprocessed in the step 1, and dividing the data into a training set and a test set according to the extracted features; and 3, constructing a model by using a sklearn packet in Python, training the model on the training set divided in the step 2, evaluating the model on the test set, inputting data to be screened into the model, and screening data of the congenital heart through the model, wherein the evaluation index is the area under the ROC curve. According to the newborn congenital heart disease screening method based on tandem mass spectrometry, ventricular septal defect with the maximum proportion in congenital heart disease is focused on, and good economic cost benefits are achieved.

The invention discloses an assessment method and system combining a language model and a virtual technology, and the method comprises the following steps: drilling a police and people dialogue process, analyzing the drilling language output of a subject through a first language model, and obtaining a drilling analysis result; obtaining a drill score of the subject based on the drill analysis result; when the drill score of the subject meets a preset score requirement, obtaining an assessment permission; based on the examination permission, combining a virtual technology to construct police and people dialogue scene questions; the subject is assessed based on the police and people dialogue scene questions, and assessment language output is obtained; and analyzing the assessment language output by adopting a second language model to obtain an assessment evaluation report of the subject. According to the method and the system, the language model is combined with the virtual technology, so that the more advanced and efficient assessment method and system are constructed, and the assessment quality and effect are improved.

Provided is an evaluation device that includes an acquisition unit that acquires position data pertaining to a plurality of measurement target sites established in an evaluation target segment of a body, a calculation unit that fits a circle to the plurality of measurement target sites and calculates a value of a diameter of the fitted circle, an evaluation unit that evaluates flexibility of the evaluation target segment according to the calculated value of the diameter of the circle, and an output unit that outputs an evaluation result relating to the flexibility of the evaluation target segment.