106 results about "Training course" patented technology

The invention discloses a multi-agent cooperation system construction method, a medium and equipment, and the method comprises the steps: carrying out the task modeling of a target business scene, and constructing a task dependence graph; initial cooperation strength weights are set for the atomic tasks with the cooperation relationship, and multi-stage cooperation training courses from easy to difficult are generated based on the cooperation complexity of the atomic tasks; the intelligent agent is controlled to execute a task in a training course, interaction behavior data is collected, the overall task completion efficiency is calculated, the cooperation weight is dynamically updated, and interaction data and the updated weight are input into a reinforcement learning model to iteratively optimize a cooperation strategy; and finally, solidifying the converged cooperation strategy into the constructed multi-agent cooperation system. According to the invention, through the combination of course learning and reinforcement learning, the cooperation efficiency and robustness of the system in a complex business scene can be significantly improved.

The invention provides a safety training model, method and system based on a capability evaluation dynamic weight optimization model, and a computer medium, and the method specifically comprises the steps: building a capability-knowledge-course three-dimensional map model, building a three-dimensional mapping relation, and determining an initial weight; fusing, optimizing, adjusting and triggering subjective and objective weights dynamically based on student behavior data, generating a personalized curriculum recommendation sequence through a reinforcement learning algorithm, forming a state space by an ability evaluation vector and a knowledge mastery degree vector, and taking a curriculum resource set as an action space; the short-term learning efficiency and the long-term post assessment passing rate are used as reward functions to construct a recommendation strategy, meanwhile, the invention further provides a computer medium achieved based on the scheme, and the method can provide safety capability assessment means and training courses which are high in pertinence and good in accuracy for chemical enterprise employees.

The invention discloses a reinforcement learning model training method and device based on dynamic data selection and electronic equipment, and the method comprises the steps: carrying out the screening from an original mathematical problem data pool according to preset data quality, diversity and difficulty evaluation indexes, and obtaining a candidate training set; calculating a data validity score of each training sample in the candidate training set; difficulty filtering is carried out on the candidate training set, and an adaptive training course is constructed; further filtering the candidate training set according to the solution reasoning process and the reward score of the candidate training set; dynamically selecting a data subset for the current training period by setting a temperature parameter attenuated along with the training process and a probability threshold based on the further filtered candidate training set and the data validity score; the selected data subsets are put into a reinforcement learning model for training, and the reinforcement learning model is trained in an optimized mode according to the correctness reward and the format reward. The model training period can be remarkably shortened, and the performance equivalent to or even better than that of full data training is achieved.

Systems, methods, and computer-readable storage media for indexing a catalog of training content, and more specifically to indexing the catalog of training content using Artificial Intelligence (AI) to improve responses to queries. A system can execute a search of training course content stored in a database, identifying at least one of new training course content or updated training course content. Based on the media type of the each piece of content, the system can execute one or more data extraction algorithms, resulting in extracted data for each piece of new or updated content. The system can then add the extracted data to a semantic search index.

The invention relates to the technical field of enterprise training, and discloses an enterprise training course generation method based on AI personalized customization, and the method comprises the steps: S1, data collection, S2, AI model construction and training, S3, course content generation, S4, course optimization and evaluation, and S5, course release and update. Through comprehensive collection of employee information, deep analysis of post requirements and accurate evaluation of employee performance, skill weakness and learning requirements of employees can be accurately positioned, personalized curriculum generation is carried out by using an AI technology, high matching of training contents and individual requirements of the employees is ensured, and training efficiency is improved. For example, courses customized for technology research and development personnel focus on the latest technology trend and research and development method, and courses of marketing personnel focus on market dynamics and marketing strategies, so that the learning enthusiasm and participation degree of employees are effectively improved, and training resources are more reasonably utilized.

Systems, methods, and computer-readable storage media for using distinct Artificial Intelligence algorithms to review incident reports and identify, within a corpus of training courses, which courses would be best for mitigating or preventing future incidents. A system can receive an incident record involving an individual human being involved in an incident, then analyze that incident record by executing a first Artificial Intelligence (AI) algorithm, resulting in a natural language incident summary. The system can then generate, by executing a second AI algorithm using the natural language incident summary, corrective training recommendations for the individual human being, the corrective training recommendations predicted to perform at least one of mitigating or preventing the incident from occurring again, and provide those corrective training recommendations to an authority over the individual human being.

The invention discloses a teacher teaching ability improvement training method and system, and the method comprises the steps: determining a plurality of evaluation dimensions for teacher teaching ability, obtaining a quantitative evaluation index of each evaluation dimension, and obtaining a plurality of high-quality training course resources according to the quantitative evaluation indexes; historical teaching state parameters input by each teacher are obtained, and teaching ability evaluation is carried out on each teacher; analyzing a teaching short board index and short board state description of each teacher according to an evaluation result, and determining capability improvement demand parameters; and screening out a target training course resource from the plurality of high-quality training course resources according to the ability improvement demand parameters, making a training plan based on the learning ability information of each teacher, and carrying out teaching ability improvement training on each teacher according to the training plan. According to the invention, accurate short board related ability training can be accurately carried out for teachers with different teaching levels, the training efficiency and stability are improved, the adaptability of training resources is ensured, and the practicability is improved.

The invention provides an online car-hailing driver qualification dynamic verification system and method based on multi-source information fusion. Comprising a multi-source information acquisition module used for receiving related data submitted by a driver end and performing consistency verification by using a person-certificate consistency detection algorithm to generate a first verification result; the data consistency comparison module is used for carrying out cross-certificate comparison and generating a second verification result; the automatic auditing and decision-making module is used for outputting a driver qualification auditing conclusion and a conclusion identifier according to a preset city auditing rule base and the second verification result; the training task management module is used for matching and distributing a training course task for the target driver account according to the conclusion identifier, and receiving a training completion state; and the vehicle authority control module is used for opening or keeping limitation on the order receiving authority of the target driver account according to the conclusion identifier and the training completion state, and dynamically adjusting the order receiving authority. According to the invention, rapid auditing, automatic training distribution, data linkage and real-time dynamic compliance management and control can be realized.

The invention discloses a child gait anomaly recognition feedback method and system based on plantar pressure data, and relates to the technical field of gait anomaly recognition, and the method comprises the steps: collecting the plantar pressure data of a target wearer through a sensor array, and carrying out the feature extraction of multi-dimensional gait feature parameters; comparing and analyzing the model with a child gait development standard model, and recognizing a gait abnormal mode; carrying out risk assessment on the target shoe wearer and dividing risk levels; performing gait analysis on the target wearer to generate an individualized gait analysis report; and performing gait correction analysis on the target wearer according to the individualized gait analysis report, and matching to generate a correction training course scheme. The technical problems that in the prior art, child gait evaluation lacks quantitative standards, detection intervention is disjointed, and personalized analysis based on a dynamic development model is lacked are solved, and the technical effects of achieving objective, accurate and intelligent recognition of child gait abnormity and improving the child gait health management level are achieved.

The invention relates to the technical field of rail traffic safety operation and maintenance, in particular to a rail traffic training method and system based on an AR intelligent head-mounted terminal, and the method comprises the steps: classifying rail traffic equipment into high-risk equipment and common equipment based on a preset fault library; generating a virtual training scene aligned with the physical space coordinates; based on a preset student skill portrait, a preset fault library and a preset operation instruction library, configuring a modular training course in the virtual training scene; acquiring operation data when a student executes the modular training course through an AR head-mounted terminal, wherein the operation data comprises spatio-temporal trajectory data, decision delay and an interaction log; based on the spatio-temporal trajectory data and the decision delay, a compliance score is generated through fusion; and generating a skill short board positioning report. The method has the advantages that effectiveness and safety of operation training of the rail transit equipment are improved, and high-precision positioning and targeted strengthening of short skill of trainees are achieved.

The invention discloses an online training course personalized recommendation method and system, and relates to the technical field of online education. The method comprises the following steps: acquiring multi-modal learning interaction data of a user, and constructing a course knowledge graph comprising courses, knowledge components and relationships between the courses and the knowledge components; processing the course knowledge graph by adopting a heterogeneous graph attention network so as to track the dynamic knowledge state of the user; estimating the cognitive load level of the user through a pre-trained cognitive load classification model based on the multi-modal learning interaction data; and based on the dynamic knowledge state and the cognitive load level, generating a personalized learning path in a deep reinforcement learning framework by maximizing a cumulative reward function combining knowledge gain reward and cognitive load balance reward.

The invention provides a marking task-oriented training course generation method and device, a medium and a product. The method comprises the steps of obtaining label sets corresponding to a plurality of service platforms respectively, wherein each label set comprises a label field and a corresponding label rule; based on entities pointed by the semantic information of the annotation fields in each annotation set, constructing an annotation knowledge graph; the annotation knowledge graph comprises a first node for representing an entity and a second node for representing an annotation field, a connection relationship for indicating semantic association is established between the first node and the second node, and each second node is associated with a corresponding annotation rule; if the annotation rules corresponding to different second nodes connected with the same first node in the annotation knowledge graph have differences, generating a cross-platform contrast training course based on the differences; and if the labeling rules corresponding to different second nodes connected with the same first node in the labeling knowledge graph are the same, generating a cross-platform unified training course.

The invention provides a supplier life cycle management method based on a dynamic portrait and AI enabling, and the method comprises the steps: taking a Kafka message queue as a unified data bus, accessing supplier multi-source data through an API interface, log collection and other modes, employing Flink to clean and convert high-speed data streams in real time, and carrying out the batch processing of large-scale historical data through an MRS; based on GuasDWS, constructing an evaluation model containing dimensions of quality control, delivery ability and the like, calculating supplier ability scores and generating ability short board labels; analyzing demands for the purchasers, screening and sorting to recommend suppliers, and pushing customized training courses matched with a short board for the suppliers; decision feedback and training effect data are collected through portal interaction, and a driving model and algorithm increment optimization are transmitted back. The problems of static lag and extensive matching of traditional management can be solved, and the supply chain management efficiency and toughness are improved.

The invention provides an image analysis processing method and system for a law enforcement recorder, and belongs to the technical field of maintenance management, and the method specifically comprises the steps: carrying out the correlation of the deviation condition of a training course affecting a person in a law enforcement video of an untrained person, and the data of the law enforcement video as a basis; and determining an analysis processing scheme of the law enforcement video associated with the influencing personnel, determining an identification result of the illegal behavior associated with the influencing personnel by using the analysis processing scheme, and determining the law enforcement video associated with the influencing personnel by using the matching condition of the identification result and the law enforcement personnel having the training course of the law enforcement video of the untrained personnel. According to the method, the analysis processing sequence of the law enforcement videos of the untrained personnel is determined, and whether the residual law enforcement videos of the untrained personnel need to be continuously analyzed or not is determined based on the matching condition of the real-time analysis processing result and the law enforcement videos of the untrained personnel which are not subjected to analysis processing, so that the image analysis processing efficiency is improved.

The invention discloses an agricultural training path planning method based on data fusion, and relates to the crossing field of intelligent agriculture and online education technology. The method comprises the following steps: firstly, acquiring agricultural training course data represented by an agricultural knowledge graph, and collecting student personalized data of a target user and containing historical learned record information oriented to agricultural training courses and historical planting record information oriented to crops; then combining the two data to generate a skill mastering vector of the target user, after receiving a target crop planned to be planted by the target user, extracting a skill demand vector of the crop from an agricultural knowledge base, and then comparing and analyzing the two vectors to determine a skill difference vector of the target user; and finally, an agricultural training path is planned according to the skill difference vector and agricultural training course data, and an agricultural training course is pushed according to the path for the target user to learn, so that a highly personalized agricultural training path with target guidance can be generated for trainees.

The invention discloses a motor train unit driver state identification method and system. The method comprises the following steps: collecting multi-modal data; receiving the synchronized multi-modal data to recalculate the running scene of the vehicle; the illegal behavior of the driver is automatically identified through an improved identification model of the space-time attention network; the identified illegal behaviors are classified; automatically matching a corresponding reinforcement training course according to the type of the identified illegal behavior and associated scene information, and pushing the reinforcement training course to the simulated driving equipment to break a data barrier between a real vehicle and a simulator, so as to realize accurate training based on a real vehicle driving problem; multi-modal data fusion and a space-time attention network are applied, so that the accuracy and efficiency of violation recognition are improved; performing dynamic course matching based on violation classification and historical data; an evaluation report is automatically generated, manual intervention is reduced, and the management efficiency is improved; the system supports simulation driving of various motor vehicle models, and has good expandability.

The invention discloses an AI-based schizophrenia clinical thinking training simulation system, which relates to the technical field of artificial intelligence, and is characterized by comprising the steps of constructing a dynamic knowledge base, receiving and preprocessing multi-modal input, performing standardized mapping by extracting keywords, and then performing judgment of a rule layer and a semantic layer. A student question method and a standard answer method in the dynamic knowledge base are sent into a model for response generation, then four-dimensional quantitative scoring and clinical operation multi-dimensional scoring are carried out, error codes and positioning sentences thereof are output, and finally personalized training courses are recommended to students; and hot-updating the dynamic knowledge base continuous optimization model. According to the method, four dimensions of the ICD-10 diagnostic standard are converted into a quantitative scoring algorithm capable of being automatically executed, quantitative assessment of clinical operation specifications is integrated, a diagnosis and operation double-track evaluation system is constructed, the problems that a traditional method is lack of evaluation standards and high in subjectivity are solved, and the evaluation efficiency is improved. Therefore, the evaluation of the clinical thinking ability of the medical students becomes objective, comprehensive and evidence-based.

This invention relates to the field of computer software technology, specifically to a deep learning-based employee performance analysis and training course matching system and method. The system uses a multi-source data acquisition module to uniformly collect and standardize internal and external data to construct a complete employee dataset. An employee competency profile construction module extracts and fuses multimodal features from the data to generate dynamically updated multidimensional competency profiles. A performance weakness analysis engine analyzes the relationship between competency and performance, identifying weaknesses and strengths. A dynamic learning path planning module adjusts subsequent courses based on learning outcomes for continuous optimization. A training effectiveness evaluation and feedback module quantifies the training improvement effect and provides feedback to the system. A high-potential talent discovery and experience graph module constructs a reusable experience knowledge graph. An adaptive performance-competency causal evolution modeling module analyzes the causal relationship between competency and performance, dynamically adjusting competency weights and recommendation strategies.

The application discloses a kind of teacher teaching ability promotion training method and system, its method includes: determining multiple evaluation dimensions of teacher teaching ability, obtaining the quantitative evaluation index of each evaluation dimension, obtain multiple high-quality training course resources according to quantitative evaluation index;The historical teaching state parameter of each teacher is input and the teaching ability of each teacher is evaluated;According to the evaluation result, the teaching short board index and short board state description of each teacher are analyzed and the ability promotion demand parameter is determined;According to the ability promotion demand parameter, the target training course resource is filtered from multiple high-quality training course resources, and the training plan is formulated based on the learning ability information of each teacher, and the teaching ability promotion training is carried out according to the training plan for each teacher.It can accurately aim at different teaching level teachers for accurate short board related ability training, which improves the efficiency and stability of training, and also guarantees the adaptability of training resources, improves the practicability.

This invention relates to the field of intelligent education technology and discloses a tiered training method for editing skills based on deep learning. The method includes: constructing a training course library containing course units; using the course unit as the smallest learning unit, and based on the pre-dependencies of the course units, collecting real-time interactive operation data of learners to construct multi-dimensional feature vectors for learners; inputting the multi-dimensional feature vectors into a trained deep neural network model to output the learner's current assessed comprehensive course ability index; using a clustering method to divide all learners into three levels: basic, intermediate, and advanced; associating each level with a subset of course units, obtaining the matching degree between each learner's current assessed comprehensive course ability index and the difficulty coefficient, and generating a personalized course learning path recommendation for each learner. This invention achieves tiered training for learners' editing skills.

The invention discloses a student score category prediction method, system and device based on a knowledge graph, a medium and a product, and relates to the field of knowledge graphs, and the method comprises the steps: constructing a dynamic knowledge graph based on a training course; acquiring behavior time sequence data of the trainee at the current time; querying in a dynamic knowledge graph based on the behavior time sequence data to generate an adjacent matrix; the adjacent matrix is a matrix with a timestamp; constructing an input matrix based on the behavior time sequence data; inputting the adjacent matrix and the input matrix into a student score category prediction model to obtain a predicted score category; the student score category prediction model comprises a long and short term memory optimization network and a classification head; according to the long-short-term memory optimization network, a graph convolutional neural network is added on the basis of a long-short-term memory network. The real-time performance and accuracy of student score category prediction can be improved.

The application provides a multi-source information fusion-based dynamic verification system and method for the qualification of a network car driver. The system includes a multi-source information collection module for receiving relevant data submitted by the driver end and performing consistency verification using a person-certificate consistency detection algorithm to generate a first verification result; a data consistency comparison module for cross-certificate comparison to generate a second verification result; an automated audit decision module for outputting a driver qualification audit conclusion and conclusion identifier based on a pre-set city audit rule library and the second verification result; a training task management module for matching and assigning training course tasks to the target driver account based on the conclusion identifier, and receiving the training completion status; and a vehicle permission control module for opening or maintaining restrictions on the order receiving permission of the target driver account based on the conclusion identifier and the training completion status, and dynamically adjusting the order receiving permission. The application can achieve fast audit, automatic training distribution, data linkage, and real-time dynamic compliance control.

Provide a system. 【Solution means】 Means for evaluating the ability level of each employee by collecting the past work performance data and learning history of the employees, Means for automatically generating a training course suitable for the employee based on the generated evaluation result, Means for providing a training course implemented for the employee in a virtual reality environment, Means for monitoring the implementation result in the virtual reality environment in real time and providing an immediate response to the employee, Means for analyzing the implementation result of the employee after the implementation in the virtual reality environment and reporting the result, Means for generating an individual training program for improving the skills of the operation of industrial equipment and making it executable in a virtual environment, Means for providing a function for the operator to safely practice the operation of industrial equipment in a virtual reality environment, A system including.

Method for analyzing training-related data from training sessions on bicycles and training bikes with the following steps: - Recording (S1) training-related data of at least one training session on a stationary training bike; - Recording (S2) training-related data of at least one training session on a bicycle; - Processing (S3) the recorded training-related data of the training session on the bicycle and the training session on the training bike to generate a summary of the training session on the bicycle and a summary of the training session on the training bike; - Displaying (S4) summaries of training units in an overview panel of a display device.

The invention discloses an AI-based enterprise training interaction system algorithm, and relates to the technical field of enterprise training, the AI-based enterprise training interaction system algorithm comprises an enterprise management platform, a user terminal and an AI dynamic adaptation module, the enterprise management platform is electrically connected with the user terminal, and the output end of the enterprise management platform is electrically connected with a knowledge graph construction module; the output end of the knowledge graph construction module is electrically connected with a training course generation module, the output end of the training course generation module is electrically connected with an AI dynamic adaptation module, and the AI dynamic adaptation module comprises a training course matching module, a user training learning module, a training result detection module, a dynamic adjustment module and an adjustment feedback module. According to the AI-based enterprise training interaction system algorithm, a training course generation module is used for generating training courses of different posts, different skills and different difficulties by AI on the basis of an enterprise knowledge graph, and an AI dynamic adaptation module can perform course matching based on AI analysis.

The present invention relates to a control method for a single vehicle lane change and merging into a convoy based on curriculum reinforcement learning. The method comprises setting reinforcement learning training courses from simple to complex according to the difficulty of the task; determining the state space and action space of the reinforcement learning based on the surrounding vehicle information and the control object obtained by the on-board sensor; and setting a reward function in a multi-dimensional and hierarchical manner according to the vehicle state and the target task to guide the vehicle to complete the pursuit and lane change and enter the convoy; building an Actor network and a Critic network, and building an environment exploration module based on the proximal policy optimization algorithm, and updating the network using the Adam optimizer; selecting a corresponding reward function for training, performing a random number seed experiment on the network after each course training, and performing a scenario test on the policy neural network finally trained by the course learning to verify the completion of the target task of the model. The present invention solves the problem of slow and difficult training convergence caused by sparse rewards in the process of single vehicles merging into a convoy under complex traffic flow scenarios.

The application belongs to the technical field of artificial intelligence driven system design optimization, and discloses a training course planning service method and system. A quantum principal component analysis module is used to extract a correlation feature matrix of scene fluctuation parameters and resource demand, a quantum Fourier transform is used to analyze system health degree attenuation signals, and dynamic scene features are generated. A parameter tuning instruction set is constructed based on a quantum annealing algorithm to drive a genetic algorithm to optimize the topology. A quantum superposition state mapping is used to distribute micro-optimization units to a digital twin platform, and a variation quantum algorithm is used by a collaborative verification module to solve resource multiplexing strategies to form a data closed-loop feedback link. The application solves the problem of static data and dynamic demand mismatch, and improves real-time responsiveness and resource optimization efficiency in complex scenarios.

To provide an automobile training system capable of appropriately evaluating the driving of a driver.SOLUTION: An automobile training system includes an automobile capable of traveling on a training course, and a control device for acquiring driving information when a driver drives the automobile on the training course, and for extracting any inappropriate operation in the driving of the driver based on the acquired driving information and model information to be a model when driving the automobile on the training course.SELECTED DRAWING: Figure 2

1. The name of the design product: airplane horizontal stabilizer control intelligent teaching equipment. 2. The use of the design product: for the control principle teaching of airplane horizontal stabilizer in airplane maintenance training course. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: perspective view. 5. The bottom of the design product is the part that is not easy to see or cannot be seen during use, so the top view is omitted.

The invention discloses a VR training course difficulty dynamic adjustment method and system based on multi-modal behavior perception, and relates to the technical field of virtual reality teaching. The method comprises the steps of obtaining a face and body interaction data sequence when a user operates VR equipment, and obtaining interaction confidence by analyzing spatial deviation of sight and an operation part; calculating an interaction qualification degree according to a matching degree between the body action and the standard template, and obtaining an interaction concentration degree based on facial feature analysis; optimizing parameters are adaptively configured by using interaction confidence, a fitness function fusing security and quality targets is constructed by combining interaction qualification and interaction concentration, and optimal course difficulty is solved through iterative optimization; and finally, implementing personalized teaching according to the difficulty. According to the method, accurate perception and quantitative evaluation of the user operation state and the cognitive load are realized, the course difficulty can be dynamically adjusted, and the training efficiency and the teaching quality are effectively improved on the premise of guaranteeing the practical training safety.