81 results about "Assessment evaluation" patented technology

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.

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.

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 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.

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 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 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.

Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

The invention discloses an intelligent networked automobile safety situation assessment method based on multi-source information fusion. The method comprises the following steps: 1) acquiring training parameters of a speed prediction model; 2) training a neural network by using the speed prediction model training parameters, and constructing a speed prediction model; 3) predicting the speed of the vehicle at the next moment by using the speed prediction model; 4) acquiring driving safety information, and processing the safety information to obtain a safety situation assessment parameter; and 5) processing the safety situation assessment parameter to obtain a current safety situation assessment value so as to determine the driving safety state of the vehicle. According to the method, the self-vehicle speed prediction model and the driving safety situation evaluation model are constructed, and the importance of the safety situation value on the driving safety of the intelligent networked vehicle is clarified by taking the prediction of the self-vehicle speed as a link, so that theoretical and technical support is provided for realizing the safe driving technology of the intelligent networked vehicle.

The application belongs to the technical field of large model security, and specifically discloses a large model threat sample library construction method, which comprises the following steps: step S1, embedding malicious instructions or malicious data into prompt words to construct threat samples; step S2, inputting the threat samples into a target large model as prompt words; step S3, using an evaluation large model to evaluate the output results of the target large model; and step S4, if the evaluation result is harmful content, adding the threat sample into a threat sample library, otherwise, discarding the threat sample. The application solves the problem of the lack of a threat sample library for security testing of an existing large model, and automatically tests and evaluates the threat samples during the construction of the sample library, so that the threat samples can be stored in the library only after the evaluation, thereby effectively improving the construction efficiency of the threat sample library. Meanwhile, the constructed threat sample library can support the security testing of the target large model, and can be used to improve the security of the target large model.

The application provides a crane health assessment method and system, the method comprising collecting data of a working state of the crane; performing health assessment based on the collected data and a health assessment model; obtaining quantitative data based on a result of the assessment and performing maintenance guidance based on the quantitative data. The application can monitor the use of the crane in real time, analyze and assess the state of main structural parts and key components of the crane, assess the health of the crane, provide quantitative data guidance for equipment maintenance, and realize early prediction of the state of the equipment by the production and maintenance departments, so as to arrange maintenance or component plans in a targeted manner.

The embodiment of the invention provides a reliability evaluation method based on mechanical equipment component-level mechanism analysis. The method comprises the following steps: analyzing an equipment failure mode; key components are decomposed; evaluating the failure rate of the component; determining a multiplier factor; and summarizing equipment failure rates. According to the embodiment of the invention, dependence on equipment experiment data is eliminated, the influence of environmental conditions on the parts is determined by issuing the operation environment faced by the equipment to the part level, the reliability of the mechanical equipment is evaluated under the condition that the experiment data is incomplete and insufficient, the evaluation precision is improved, the early failure is early warned, the maintenance cost is reduced, and the reliability of the mechanical equipment is improved. By establishing a'material-component-system 'multi-scale model, the modeling barrier between a micromechanism and macroscopic performance of a traditional method is broken through, the component failure rate is expressed in a multiplier factor mode, and quantitative calculation of the component failure rate is achieved.

The invention belongs to the technical field of air pollution assessment, and relates to an urban air pollutant change amplitude assessment and ranking method and system, and the method comprises the steps: 1) obtaining the concentrations of a plurality of air pollutants of a plurality of cities in different time dimensions, and carrying out the standardization processing of the concentrations; 2) performing multi-dimensional time sequence analysis on the air pollutant concentration to obtain a multi-dimensional time sequence analysis result; 3) calculating a comprehensive score of each city according to the air pollutant concentration and the multi-dimensional time sequence analysis result; 4) calculating a dynamic evaluation score of each city and dynamically ranking the plurality of cities according to the dynamic evaluation scores; and 5) evaluating the change amplitude of the pollutant concentration of each city, and evaluating the plurality of cities according to the multi-dimensional time sequence analysis result and the change amplitude to obtain the risk level of each city. Evaluation is carried out based on the multi-dimensional time sequence analysis result and the dynamic weight, and the evaluation result is comprehensive and accurate.

The invention relates to an underground mine mining work evaluation method, device and system and a medium, and belongs to the technical field of mine field management.The method comprises the steps that positive indexes and negative indexes of a carry-scraper driver are obtained; wherein the positive indexes comprise the total underground working time length of a driver, the mineral mining quantity in each working stope and the moving distance of driving a carry-scraper; the negative indexes comprise work violation times; determining the positive influence degree on the mining work according to the positive index, and determining the negative influence degree on the mining work according to the negative index; and generating a mining work evaluation result of the carry-scraper driver according to the positive influence degree and the negative influence degree. The mining work of the driver is evaluated from multiple dimensions, the evaluation mode is more reasonable, and the evaluation result can more accurately reflect the mining work completion condition of the driver.

The invention relates to the technical field of rehabilitation systems, in particular to a game type rehabilitation platform for children, which comprises a user registration and login module for a user to perform account registration and login operation; the rehabilitation evaluation module is used for comprehensively testing rehabilitation conditions of children, including data comparison before and after rehabilitation, and providing user data and reference standards for the training module; the rehabilitation training module is used for establishing a virtual environment and providing rehabilitation training for children in combination with virtual equipment; and the data visualization module is used for displaying the training data and the evaluation result in the forms of charts and reports. According to the whole technical scheme, through a personalized rehabilitation scheme, the beneficial effects of improving user motivation and participation degree, real-time feedback and guidance, data-driven rehabilitation monitoring and optimization, user feedback and technical improvement and the like are achieved, the rehabilitation effect and experience of children can be improved, and more comprehensive and personalized rehabilitation services are provided.

One embodiment proposes a brainwave-based cognitive function evaluation method. The brainwave-based cognitive function evaluation method includes deriving a predicted response intended by an evaluation subject based on evaluation data including brainwaves of the evaluation subject for a specific task, generating a response accuracy including voice clarity, whether an answer matches, and answer meaning accuracy based on the predicted response and a preset correct answer for the specific task, and evaluating a cognitive function of the evaluation subject based on the response accuracy.

This disclosure provides a data processing method, apparatus, electronic device, and storage medium. The method includes: inputting a first row of data into a positive evaluation model to determine a first evaluation score for positively evaluating the recommendation effect; inputting a second row of data into a negative evaluation model to determine a second evaluation score for negatively evaluating the recommendation effect; and determining a final evaluation score based on the first and second evaluation scores. This disclosure combines the first evaluation score from the positive evaluation and the second evaluation score from the negative evaluation to assess the recommendation effect, resulting in a more comprehensive evaluation and better overall evaluation performance.

An information processing method is an information processing method for weighting an evaluation item for evaluating an evaluation target, and includes: obtaining, as text information, information expressed by one or more persons in an organization to which the one or more persons belong; obtaining one or more topics related to the text information by analyzing the text information; and weighting the evaluation item based on one or more similarity degrees between the evaluation item and the one or more topics.

The invention relates to the technical field of self-media marketing, and provides a self-media marketing content intelligent generation and distribution system based on artificial intelligence, and the system comprises a content collection module; an intelligent analysis module; constructing a knowledge graph enhancement module; a content generation module; a personalized customization module; the system comprises a content distribution module, a distribution strategy module and an effect evaluation module, a real-time monitoring and multi-dimensional evaluation index system is adopted to comprehensively evaluate the content distribution effect, the evaluation index system comprises but is not limited to exposure, click rate, conversion rate, user retention rate and the like, and an evaluation result is fed back to other modules in time so as to realize continuous optimization of the system. Through cooperative work of all the modules, intelligent generation and accurate distribution of the we-media marketing content are realized. According to the method, content collection comprehensiveness, intelligent analysis depth and accuracy, content generation high quality and diversity, personalized customization accuracy, distribution strategy high efficiency and effect evaluation comprehensiveness are achieved.

An information processing method of the present disclosure includes acquiring an evaluation perspective in evaluating a motion of an evaluation target. The information processing method includes determining a configuration evaluating the motion of the evaluation target based on the evaluation perspective. The information processing method includes acquiring at least one of video information related to a motion and audio information. The information processing method includes generating content including a configuration and at least one of video information and audio information.

This invention relates to the fields of neuroscience and brain cognitive function assessment, specifically to a method and system for assessing motor and cognitive synergistic function based on electroencephalogram (EEG) signals. The method includes: collecting EEG signal data from subjects performing motor imagery and cognitive tasks; extracting motor imagery features, cognitive task features, and brainwave propagation features from the EEG signal data; inputting these features into an assessment model to evaluate the subject's motor function, cognitive function, and synergistic function; and outputting a motor function score, a cognitive function score, a brainwave propagation score, and a comprehensive assessment index from the assessment model. This invention enables synergistic assessment of motor and cognitive functions, improving the objectivity and accuracy of assessment results, and is applicable to rehabilitation assessments for stroke and neurodegenerative diseases.

The present invention makes it possible to evaluate buckling of a panel component before assembly to another component through simple molding analysis. Provided is a method for evaluating buckling in which buckling prior to assembly of a panel component obtained by press molding a plate material into a three-dimensional form is evaluated through molding analysis using a computer. This method for evaluating buckling comprises: a press molding analysis step (20A) for performing press-molding analysis in which the plate material is formed into the panel component, and acquiring the panel shape after mold release as a reference panel shape (10); a self-weight analysis step (20B) for performing self-weight analysis with respect to the reference panel shape (10) in a condition in which the panel component is placed on a flat surface, and acquiring the panel shape after deformation resulting from the weight of the panel component as an evaluation panel shape (11); and a buckling evaluation step (20C) for evaluating buckling of the panel component having the evaluation panel shape (11).

The invention relates to the technical field of optics, and discloses a Newton ring interference fringe quality real-time quantitative evaluation system, which comprises an image acquisition module configured to acquire a Newton ring image; the primary evaluation module is configured to perform primary evaluation on the stripe quality of the Newton ring image according to the integrity of the dark ring; the evaluation adjustment module is configured to adjust the primary evaluation value according to the contrast ratio; and an evaluation decision module configured to calculate the distance from each sampling point of each dark ring to the central point of the Newton ring image, calculate the difference between the distances of each dark ring, screen out the maximum distance difference, and obtain the dark ring roundness of the Newton ring image according to the maximum distance difference of each dark ring. And adjusting the evaluation adjustment value according to the dark ring roundness to obtain an evaluation final value. The evaluation comprehensiveness is improved.

The invention discloses a process-assisted rapid compilation method based on a grouping technology and an MBD model, and the method comprises the steps: obtaining the MBD model, and converting the MBD model into a data format which can be recognized and analyzed; a feature information acquisition stage: analyzing the MBD data model which comprises structured annotation information and unstructured annotation information, and mapping process feature information contained in the part according to the analyzed information; a process feature comparison stage: performing empowerment distance measurement comparison according to the process feature information of the part and a process knowledge base with a process feature information identifier to obtain an initial process instruction file with high similarity; in the evaluation optimization and revision stage, manufacturing feasibility evaluation is carried out, key parameters are verified after evaluation is passed, and then other non-key description information is optimized; and if the evaluation is not passed, feeding back a matching environment, and performing secondary matching after excluding the selected answers. The method is easy to implement and has higher trueness and technical feasibility.

The invention relates to the technical field of data management, and discloses an enterprise finance and taxation data management method and system based on big data, and the method comprises the steps: building an enterprise finance and taxation data middle platform, obtaining data, carrying out the preprocessing of the obtained data, and numbering the data to form a finance data set, a taxation data set, a business data set, and a market data set. Calculating a financial health predicted value Cjk, a tax compliance predicted value Shg and a business stability predicted value Ywd by combining an algorithm calculation formula, constructing a risk scoring rule, and performing risk assessment and enterprise risk level assessment according to the financial health predicted value Cjk, the tax compliance predicted value Shg and the business stability predicted value Ywd. According to the method and the system, the risk assessment and enterprise risk level assessment results are output, comprehensive and targeted assessment is carried out on the enterprise risk from different dimensions, the assessment efficiency is high, the assessment effect is accurate, and accurate monitoring and dynamic early warning of enterprise finance and tax data are realized.

The invention discloses an intelligent monitoring method and system for the safety state of an efflux pump, and relates to the technical field of industrial equipment safety, the system collects working condition data of the efflux pump in real time through a sensor group installed on the efflux pump, and pre-processes the working condition data to construct a fluid state data set and a load evolution data set; medium disturbance evaluation is carried out by calculating a medium disturbance leading edge index VPI and a medium disturbance response threshold TH, when shear disturbance is evaluated to be formed, a load evolution analysis instruction is executed, a load lag evolution index LEI is calculated based on structure response data, and then a joint instability risk index UDR is calculated in combination, so that the shear disturbance is evaluated to be formed. And performing comprehensive instability response evaluation with a set first joint instability boundary threshold UA and a set second joint instability boundary threshold UB, and executing a grading safety adjustment strategy according to a comprehensive instability response evaluation result. According to the system, early recognition, dynamic evaluation and closed-loop response of the abnormal state of the outer conveying pump can be achieved, and the safety and stability of operation of the conveying system are improved.

The invention discloses a house health intelligent physical examination method based on a large model, and the method comprises the following specific steps: (1) carrying out the fusion analysis of multi-source monitoring data, and extracting the features of the safety hidden troubles of a house; (2) formulating house health examination standards; (3) constructing a house health intelligent physical examination large model, and establishing an intelligent evaluation algorithm; (4) developing a mobile terminal APP; according to the method, fusion analysis is carried out on monitoring data, space features of potential safety hazards of the houses are extracted, mass house feature data collected by non-professionals in an area are subjected to batch, efficient, low-cost and intelligent analysis through a house health AI intelligent evaluation algorithm, and the house health state is judged; according to the invention, the health conditions of massive houses in the area can be evaluated, a unified house evaluation standard is provided during evaluation, and the convenience and efficiency of monitoring are improved.

To evaluate consistency between testing criteria described in natural language and a testing procedure or testing command described in natural language.SOLUTION: A testing evaluation system comprises: a first extraction AI model that extracts descriptions related to predefined evaluation criteria from descriptions of testing criteria input to a first input part; a second extraction AI model that extracts descriptions related to the evaluation criteria from descriptions of a testing procedure or a testing command input to a second input unit; an evaluation item integration part that integrates the descriptions of the testing criteria extracted by the first extraction AI model and the descriptions of the testing procedure and the like extracted by the second extraction AI model to obtain evaluation items in the evaluation criteria; and an evaluation AI model that evaluates consistency between the descriptions of the testing criteria and the descriptions of the testing procedure and the like for the evaluation items in the evaluation criteria integrated by the evaluation item integration part.SELECTED DRAWING: Figure 2