120 results about "Training quality" patented technology

The invention relates to the technical field of training assistance, in particular to a training quality prediction method and system based on training damage analysis, and the method comprises the steps: multi-modal data collection and accumulative superposition, causal graph construction, attitude risk modeling, data enhancement, dynamic prediction and training plan optimization. According to the method, daily exercise data of a user is continuously collected, a chronic load accumulative calculation model is established, and a time sequence analysis method is adopted to perform long-term tracking and accumulative calculation on core indexes such as exercise amount, heart rate variability and joint activity, so that a complete personal exercise state database is formed; the chronic load accumulation mechanism breaks through the limitation of traditional single training evaluation, comprehensive monitoring and long-term trend analysis of the motion state of the user are achieved, a potential risk mode can be found earlier, a reliable data basis is provided for personalized risk evaluation and scientific training optimization, and the method is suitable for popularization and application. The problems that a traditional motion monitoring system is single in data and one-sided in evaluation are effectively solved.

The invention relates to the technical field of medical simulation training, in particular to an anesthesia puncture virtual simulation operation training and analysis system which comprises a force feedback calibration unit, a force feedback adjustment unit and a force feedback output unit. A theoretical force feedback value is calculated based on a human tissue mechanical model library, tissue levels and characteristics are accurately considered, in a deviation correction link, a force perception deviation value is periodically recalculated, data are processed by applying a sliding window averaging method, overall deviation and local deviation are distinguished and correspondingly adjusted, and the overall deviation is uniformly corrected; functional fine adjustment is locally set according to puncture depth sections, time-dependent force feedback of tissue viscoelasticity is considered, components are calculated through convolution integral and synthesized into final values with elasticity and inertia components, force feedback accuracy is improved comprehensively, individual differences and operation details of trainees are fitted, and anesthesia puncture training quality and effect are improved efficiently.

The invention relates to a simulation dialogue partner training system based on a large model. The simulation dialogue partner training system comprises a product knowledge base module, a question and answer library construction and management module, a pair training simulation module, a stage control module, a supernatural voice dialogue module, a verbal skill prompt module, a real-time evaluation module and a dialogue summary report module. The intelligent partner training system for customer communication training has high simulation dialogue ability, flexible configuration ability and a perfect evaluation feedback mechanism, can effectively replace a traditional scripted training or real person simulation partner training mode, and improves the communication actual combat ability of front-line personnel such as sales personnel and customer service personnel. According to the invention, low-efficiency links in a traditional training mode are replaced by an intelligent means, the training quality, the standardization degree and the reproducibility are improved, an enterprise is finally assisted to create a more professional and efficient customer front-line team, and the system can be widely applied to scenes such as enterprise training, new employee on-duty training and product popularization preparation.

The invention relates to the technical field of operation training evaluation, in particular to a training quality evaluation method and system based on pilot attention distribution. The method comprises the following steps: collecting data required by pilot attention distribution training quality evaluation according to a specific flight mission scene; based on the collected data, calculating a standard attention distribution model of the pilot in a specific flight mission scene, and generating attention distribution and actual attention distribution of the standard attention distribution model; and comparing the attention distribution of the standard attention distribution model with the actual attention distribution, evaluating the training quality of the attention distribution of the pilot in the specific flight mission scene, and forming and displaying an evaluation result. According to the method, the attention distribution mode of the pilot is quantified, the eye movement tracking technology and task-related subjective and objective data are combined, the performance of the pilot in simulator training can be objectively and accurately evaluated, and the scientificity, fairness and safety of flight training are improved.

The invention discloses a method and system for generating an EBT scene of a pilot based on a text and flight data, and the method comprises the steps: extracting threat error items in the operation of the pilot from a multi-source text through employing a scene perception word frequency-inverse document frequency method, and generating text analysis; a method of combining time feature attention, convolutional self-encoding and a long short-term memory network is utilized to comprehensively analyze flight data of daily routes and simulator training, dynamic features and potential risk factors in pilot operation are extracted, and flight data analysis is generated; in combination with text data analysis, flight data analysis and a scene element library, training scene elements are generated by adopting a hierarchical rule structure condition generative adversarial network method, and a teacher performs screening and combination to generate a personalized training scene. Through multi-source data fusion and data-driven analysis, a pilot personalized training scene is generated, the pertinence and effectiveness of training are improved, the use of training resources is optimized, and the overall flight safety and training quality are improved.

The invention discloses an anesthesia anatomy practical training system based on virtual simulation, which relates to the technical field of medical simulation training and comprises a virtual anatomy modeling module, a physiological simulation module, a dynamic response and tactile feedback module, a multi-dimensional data acquisition and performance evaluation module and an intelligent clinical decision support and dynamic virtual case module. According to the invention, high-precision three-dimensional reconstruction and dynamic physiological simulation technologies are adopted, and real-time monitoring, tactile feedback and closed-loop adaptive optimization are combined, so that precise, real-time and personalized training of virtual simulation anesthesia anatomy practical training is realized. The system can dynamically simulate physiological changes of a human body, provides remote collaborative teaching and risk early warning, effectively improves training quality and clinical decision-making level, and has remarkable safety, practicability and popularization prospects.

The invention relates to a federated learning method based on training quality evaluation and on-chain reward payment, and belongs to the technical field of federated learning. According to the method, a block chain technology is utilized, a central server and a client are regarded as nodes on a block chain, data transmission between devices is realized through a block chain network, and payment of training quality is realized through an intelligent contract. Through a zero-knowledge certification technology, the certification of the training quality by the central server is realized on the premise of protecting user data privacy.

The invention provides a whole-people cardio-pulmonary resuscitation training effectiveness monitoring method and system, and the method comprises the steps: building an online learning platform, and generating a cardio-pulmonary resuscitation training plan based on an American heart association guide, a practical experience case library and an Ebbinghaus forgetting curve principle; acquiring electroencephalogram signal data and an operation video when the trainee end completes training; according to the electroencephalogram signal data, the concentration degree of the student terminal on different learning plates in theoretical knowledge training is analyzed; performing operation key point analysis on the operation video through a target identification and target tracking algorithm; and screening unqualified items from the training result score table by combining the corresponding relationship between different learning plates and operation key points, the concentration analysis result and the operation key point analysis result score, remaking a consolidation training plan, and sending the consolidation training plan to the student end for consolidation training. And updating the training result score table according to the concentration analysis result of consolidation training and the operation key point analysis result until all scores are qualified. According to the method, the training quality and the training efficiency are improved.

In order to overcome the defects that in the prior art, driving simulation training duration statistics is extensive, training quality cannot be effectively evaluated, and system fault interference is likely to happen, the invention provides a driving simulation training effective class hour evaluation method and device, and the method comprises the following steps: S1, collecting operation parameters of a driving simulator and current training scene information; s2, dividing the collected data into independent time slices according to a preset time interval, and calculating an operation characteristic index in each time slice; s3, performing effective class hour and comprehensive quality evaluation by utilizing an intelligent evaluation module, wherein whether the operation characteristic indexes in each time slice are effective or not is preliminarily judged on the basis of the basic threshold parameters; in combination with current training scene information, querying a scene-operation rule base, dynamically adjusting a basic threshold parameter, and re-evaluating whether the operation characteristic index in each time slice is valid or not; and performing quality evaluation and effective class hour evaluation based on a multi-dimensional data fusion algorithm, and outputting an accumulated effective class hour and comprehensive quality evaluation report.

The invention provides an accounting financial training evaluation method and system based on a neural network model and a storage medium, and the method comprises the steps: obtaining the login information of a training object and the last training rating information, and requesting to configure a simulation original bill to be processed of a simulation customer corresponding to the simulation customer grade; acquiring an on-site training image and a simulated original bill image; obtaining a first recognition result and a second recognition result; obtaining voucher input information manually input by the training object, and performing difference detection on the second identification result and the voucher input information in real time; when it is detected that a second behavior pre-judged by the first recognition result is finished, comparing the first-time input data after the second behavior is finished with the last-time input data before the second behavior, and if the data are not the same, sending out a first instruction; calculating a training accuracy evaluation value of the training object; a training rating for the training subject is determined. By adopting the training evaluation method provided by the invention, the training scheme can be optimized and the training quality can be improved.

The invention discloses a method and a device for adjusting a cushion of a spinning and electronic equipment, and relates to the technical field of software and the field of sports science and technology. The method comprises the steps that under the condition that user authorization is obtained, user data of a user and riding exercise data when the user carries out riding training on the spinning bike according to a target course are obtained; a cushion of the spinning is adjusted to be in an initial state according to the user data; according to the course data of the target course and / or the riding motion data, in the process that the user uses the spinning bike to conduct riding training, the cushion in the initial state is adjusted. The technical problems that in the prior art, due to the fact that a unified cushion is generally provided for helping a user to conduct spinning riding training, the cushion cannot be adjusted in a personalized mode, the training quality and the training experience are affected, and even the training injury risk of the user is likely to be high are solved.

The invention discloses a quality-effect index and influence factor correlation analysis model construction method and system, and the method comprises the steps: carrying out the preprocessing of an original analysis data set, and then carrying out the standardization processing, so as to obtain a standard analysis data set which comprises standard quality-effect indexes and standard influence factor data; dimensionality reduction processing is carried out on the standard influence factors to extract key influence factors, the correlation degree between the key influence factors and the standard quality-effect indexes is quantified, and an initial correlation analysis model is constructed based on the correlation degree; and performing iterative training on historical training data according to a machine learning algorithm, and dynamically optimizing model parameters in the initial correlation analysis model to obtain a trained correlation analysis model. The method is used for solving the technical problems of inaccurate quality and efficiency evaluation, fuzzy influence factor relevance and the like in a training scene, systematic analysis and scientific prediction of the training quality and efficiency are realized, and quantitative decision support is provided for training scheme optimization and quality improvement.

The invention discloses an intelligent management system for sports basketball training risk data, which relates to the technical field of sports data analysis and comprises an acquisition module for generating three-dimensional tracks of athletes, an identification module for identifying risk actions, an analysis module for analyzing kinematic characteristics of the risk actions and a feedback module. According to the invention, data acquisition is carried out through multi-view video capture and a three-dimensional reconstruction technology, through real-time analysis of features such as postures and joint angles of athletes, the system can provide customized action suggestions for each athlete, the training quality is effectively improved, iterative updating of a deep learning model is carried out according to an evaluation result of a feedback module, and the training efficiency is improved. Along with the promotion of the training process, the recognition precision and risk judgment capability of the system are continuously improved, and more accurate risk action recognition is ensured.

AI / ML model quality monitoring and rapid recovery under model fault detection are disclosed. A UE may receive a training quality query message from a network device, wherein the training quality query message includes query information about one or more training quality metrics of one or more AI models used to train the UE; and send a training quality response message to the network device, wherein the training quality response message includes response information about the one or more training quality metrics of the one or more AI models used to train the UE.

The invention provides a large model data set quality evaluation method and system. The method comprises the following steps: S1, constructing a large model data set quality evaluation framework based on file quality, file description quality, file content quality, data labeling quality and model training quality; s2, constructing a large model data quality evaluation index based on the constructed large model data set quality evaluation framework; and S3, acquiring a large model data set, classifying the large model data set according to modal types and single evaluation indexes, and performing corresponding quality evaluation on the classified data set. According to the method, the data set quality of the large model can be comprehensively and systematically evaluated, and the high-quality data set construction of the large model can be effectively guided, so that the training efficiency of the large model is improved, errors and deviations in the training process are reduced, and the accuracy and generalization ability of the model are improved.

The invention discloses an offshore platform special operation interactive terminal virtual simulation training teaching method and system, and the system comprises a safety education module, an immersive teaching module, a teaching management module and an industrial-grade terminal, and all the modules cooperate through a multi-layer architecture. The method comprises the following steps: authenticating an identity through an interaction token, performing virtual platform roaming on a display screen of an industrial-grade interaction terminal, and learning regional safety specifications; selecting a homework type through an interactive screen, completing a practice task in a three-dimensional scene, and verifying operation and feeding back in real time by a system; an approval process is triggered through the interaction token, and the system generates a score and evaluation report according to the operation data; and the teaching management module analyzes the weak link, and pushes customized training content or updates a resource package. According to the invention, the training immersion is improved, and the continuity of marine environment training is guaranteed through a low-bandwidth hot update technology; the AI analysis realizes personalization, optimizes the training quality, and adapts to the harsh working environment.

The invention belongs to the technical field of intelligent data processing and personnel performance evaluation, and discloses a multi-terminal collaborative personnel training and performance measurement system based on an end-side cloud network architecture. The system comprises a terminal layer, an edge computing layer, a cloud and a network layer. The terminal layer collects multi-source data such as operation behaviors, physiological statuses and environments of personnel training; the edge calculation layer pre-processes the data in real time through a lightweight model and extracts key feature sub-information; the cloud fuses and analyzes the feature data, and constructs a performance evaluation model; and the network layer realizes communication of each layer. According to the invention, the problems of insufficient multi-terminal collaboration, limited data processing and single performance measurement in the prior art are solved, efficient collaborative management and accurate evaluation in the training process are realized, and the training quality and effect of personnel are improved.

The invention discloses an appointment management method for driving training of a driving school student, and relates to the technical field of appointment management, and the method comprises the steps: student registration and system information input are carried out, and student information is obtained; performing identity verification according to the student information; generating a personalized training plan according to the student information to obtain a training plan; performing reservation scheduling according to the training plan to obtain reservation information; performing real-time updating and notification according to the reservation information, and recording training data; performing data analysis and optimization according to the training data to obtain an optimization result; and training quality feedback is carried out according to an optimization result. According to the invention, the flexibility of training is improved, feedback can be carried out in real time, the training process is dynamically adjusted, the training efficiency and the training effect are improved, the learning experience of students is improved, and the individual requirements of different students are met.

The invention relates to the technical field of vehicles, in particular to a vehicle energy management strategy training method and device, equipment, a medium and a product, and the method comprises the steps: obtaining the operation data of a vehicle model of a target vehicle; training an intelligent agent based on reinforcement learning by using the operation data, the intelligent agent comprising a state space and an action space, the state space receiving the operation data, and the action space outputting an energy management strategy of the target vehicle; evaluating the energy management strategy by using a pre-constructed reward function, wherein the reward function comprises a multi-stage fuel consumption reward, an SOC stabilization reward and an extreme state constraint penalty reward; and optimizing the output of the action space based on the output value of the reward function, and stopping training until a preset condition is met to obtain a target energy management strategy. The problems that the training quality is poor and the practical deployment feasibility of the energy management strategy obtained through training is poor in the process of training the intelligent agent to output the energy management strategy in the related technology are solved.

The application provides a logistics warehouse picking training and motion optimization method and system based on virtual reality, and relates to the technical field of intelligent warehousing. The method constructs a virtual warehouse environment linked with a database in real time and generates a picking task guide; collects depth images, inertial measurement data and physiological signals, and fuses to generate whole body posture data of a trainee; identifies non-standard actions based on the posture data and calculates work efficiency; combines the carrying weight, physiological state and motion data to perform ergonomics scoring, fatigue accumulation analysis and injury risk prediction; dynamically adjusts the task difficulty and controls the training process according to the training state; and finally generates a training evaluation report through motion data comparison. The application can improve the quality of logistics picking training and reduce the risk of work injury.

The invention discloses a human body acupoint automatic positioning method, system and device based on deep learning and a storage medium. A body part area containing an acupoint is quickly positioned through a target detection model; utilizing a key point detection model to accurately detect anatomical key point coordinates in the region; innovatively, firstly, according to a preset traditional Chinese medicine acupoint positioning rule knowledge base, mathematical calculation is conducted on the key point coordinates, and initial acupoint coordinates are obtained; then a local image area with the initial coordinates as the center is intercepted, a lightweight self-adaptive fine tuning network is input, fine offset compensation is conducted on the initial coordinates according to local image features, and final high-precision acupoint coordinates are output. In addition, the invention further provides a double-model cooperative training process, weighted screening is carried out on training samples by utilizing a region detection model so as to improve the training quality of a key point detection model, and traditional Chinese medicine knowledge and a modern artificial intelligence technology are deeply fused so as to improve the training quality of the key point detection model. The method overcomes the defects of black box, high data dependence, poor generalization and the like of a pure data driven model, has the advantages of high positioning precision, high reliability, good interpretability and the like, and is suitable for multiple fields of traditional Chinese medicine clinic, teaching, health service and the like.

The application discloses a real-time screenshot splicing-based operation key step playback method in a practical training room, relates to the technical field of data processing, and balances integrity and storage economy by aligning desktop screenshots with multi-dimensional event timestamps and combining operation strength adaptive sampling, which not only completely captures operation details, but also avoids invalid screenshot waste; relying on screenshot splicing and incremental storage technology, a globally consistent operation context is constructed to solve the information loss problem under window switching and complex operation; through intelligent screening and atlas indexing of key steps, accurate positioning of operation steps is realized, and playback step-level time compression and event superposition presentation are matched to greatly improve the backtracking efficiency; the playback consistency verification and rollback correction mechanism guarantee the accuracy of reproduction, and finally, the operation review effect in practical training teaching is optimized, the students are helped to quickly master core skills, and the training quality is significantly improved.

The present invention discloses a sports training system based on sports sensation, comprising a storage unit, an electromyographic signal acquisition unit, a data analysis unit and a display unit, wherein: the storage unit has a plurality of preset limb movement schemes built in, and these schemes can be demonstrated by the display unit; the electromyographic signal acquisition unit is used to collect the electromyographic signals of the trainee when completing the movement according to the demonstrated movements, and send them to the data analysis unit; the data analysis unit is used to receive the electromyographic signals and analyze them; the storage unit can also be used to store the electromyographic signals and the analysis results thereof; the data analysis unit can generate a virtual limb movement trajectory according to the trainee's electromyographic signals, and display it through the display unit, and judge the training quality by comparing the preset movement scheme with the virtual limb movement trajectory generated by the electromyographic signals.

The invention discloses a military crane chassis fault reproduction and practical training system based on working condition simulation, and relates to the technical field of military equipment practical training, and the system comprises an entity chassis building unit which selects and uses entity parts of subsystems of a military automobile crane to be arranged and installed according to a real automobile, retains a key relation, presets an interface, defines a safety threshold value and the like; the dual-mode fault generation unit constructs an initial library, and an intelligent agent is embedded to generate a fault; the multi-dimensional data acquisition unit responds to the trigger signal to acquire multiple types of data; the fault diagnosis practical operation unit is used for trainees to operate; the training evaluation and fault iteration unit generates a report and feeds back optimization suggestions; according to the invention, a dual-mode fault generation unit is constructed, an initial fault library and an intelligent agent exploration capability are integrated, a screening algorithm is matched, and multiple fault scenes are provided; a complete practical training system is built, multi-dimensional data acquisition is achieved, practical operation and evaluation iteration are standardized, the practical training quality is improved through closed-loop design, and the military crane chassis fault practical training requirements are met.

The invention relates to the technical field of physiological signal recognition, in particular to a flight training quality analysis method and system based on brain magnetic resonance imaging. According to the method, fMRI data of students before and after flight training are collected, dACC and PoCGL of brain functional areas are defined, BOLD signal time sequences corresponding to the functional areas are accurately extracted, meanwhile, resting state functional connection analysis is carried out on the BOLD signal time sequences of two key brain areas before and after training by utilizing a Pearson's correlation coefficient, and a connection strength difference value with high credibility is obtained, so that the training accuracy of the students is improved. An individual training quality score is output through nerve-behavior joint modeling, a structured evaluation report is formed, training quality evaluation is converted from experience judgment to data driving and mechanism supporting, objectivity and scientificity of the system are enhanced, and compared with a traditional subjective scoring system, the system has the advantages that the training quality evaluation efficiency is improved. The index has the advantages of physiological interpretability and high repeatability, and can accurately analyze the flight training quality of trainees.

The invention discloses a driving training path generation and evaluation system and method based on garage location data modeling, belongs to the technical field of intelligent driving training, and is used for solving the problems of inconsistent driving training standards and insufficient subject path planning and evaluation accuracy. The system comprises a data acquisition module, a storage location modeling module, a spatial index module, a track generation module, a track evaluation module and a teaching guidance module. The method is implemented by adopting the system through the steps of information acquisition, storage location modeling, index construction, standard trajectory generation, actual trajectory deviation calculation and teaching guidance generation. According to the invention, through parking space accurate modeling and module cooperation, training standards are unified, the path evaluation precision and the teaching guidance pertinence are improved, and the driving training quality and efficiency are improved.

The present application relates to a kind of breathing training systems using six-word formula, including user end hardware and cloud server, using the VR head-mounted integrated machine of user end hardware and elastic fabric waistband, guide and detect the breathing training condition of user, realize the accurate classification of abdominal breathing, chest breathing, mixed breathing by means of EMG, displacement, triple fusion calculation mode of flow, utilize mouth shape identification auxiliary phoneme confidence correction, accurately identify different exhale mode of six-word formula, introduce mouth shape identification, phoneme model, physiological sensing fusion multi-modal scoring mechanism, compared with traditional single chest and abdominal displacement monitoring scheme or single audio identification scheme, accurately evaluate the training quality of user from many aspects and comprehensive score, it is convenient for user to understand the improvement direction and progress space of self breathing training.

The invention discloses a practical training room desktop operation key step playback method based on real-time screenshot splicing, relates to the technical field of data processing, and aims to completely capture operation details, avoid invalid screenshot waste and balance integrity and storage economy through alignment of desktop screenshots and multi-dimensional event timestamps and adaptive sampling in combination with operation intensity. On the basis of screenshot splicing and incremental storage technologies, a globally consistent operation context is constructed, and the problem of information missing under window switching and complex operation is solved; through intelligent screening of key steps and map indexing, accurate positioning of operation steps is realized, step-level time compression and event superposition presentation of a playback end are matched, and the backtracking efficiency is greatly improved; a playback consistency verification and rollback correction mechanism guarantees reproduction accuracy, and finally, operation reproduction and efficient backtracking experience are performed with low storage transmission cost and high integrity, an operation replay effect in practical training teaching is optimized, students are assisted to quickly master core skills, and training quality is remarkably improved.

The invention provides a method for constructing a data quality evaluation model, and belongs to the technical field of quality evaluation, and the method comprises the steps: collecting a to-be-evaluated data set, and obtaining a business demand and an application scene of the to-be-evaluated data set; determining an assessment index vector of the to-be-assessed data set based on the business demand and the application scene of the to-be-assessed data set; based on the to-be-evaluated data set and the evaluation index vector, determining a training quality feature matrix and a test quality feature matrix; and constructing a quality evaluation model based on the training set and the training quality feature matrix, and evaluating and optimizing quality evaluation performance based on the evaluation index vector, the test set and the test quality feature matrix. The method can enhance the capturing capability of the model for the data quality characteristics, achieves the high-precision evaluation of dynamic weighting, improves the intelligence and stability of the quality evaluation model, and improves the adaptability of the model in the quality management and analysis scenes of complex data.

The invention discloses an electric energy metering device field calibration skill training method, system, equipment and medium, and relates to the technical field of electric energy metering device calibration training, and the method comprises the steps: generating a fault training scheme and a training operation instruction according to a fault scheme template library based on a training demand; in response to the practical training operation instruction, carrying out practical training safety pre-test, and after the test is passed, starting multi-skill item operation according to a fault practical training scheme sequence; generating a training report based on the monitoring data of the multi-skill project operation process; according to the invention, through a whole training period from fault scheme adaptation, operation process guidance to result feedback, training quality improvement of skills of the trainee from operation to standardized and accurate operation is realized, and operation standardization and accuracy are improved while operation fluency and efficiency of the trainee are improved.