65 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 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 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 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.

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.

The invention relates to a database-based data processing method and system, electronic equipment and a storage medium. The method comprises the following steps: creating a skill library, a course library, a personnel library and a post library; constructing a personnel skill relation table, a post skill relation table and a curriculum skill relation table based on the skill library, the curriculum library, the personnel library and the post library; an employee post matching relation is determined according to the personnel skill relation table and the post skill relation table, and the employee post matching relation is sent to the intelligent scheduling platform; and when post gap information of the intelligent scheduling platform is received, determining gap skills according to the post gap information and the post skill relation table, determining personnel needing skill training and training courses according to the gap skill and personnel skill relation table and the course skill relation table, and sending the training courses to the personnel needing skill training. And the personnel needing skill training are notified to execute course training. By adopting the method, manual dominant staff skill management is not needed, and automatic staff skill management is realized.

The invention relates to a training course pushing method and device, electronic equipment and a storage medium. The method comprises the steps of collecting multi-dimensional information data of employees; constructing a correlation model, outputting a fusion feature set, and identifying key influence factors based on the fusion feature set; inputting the fused feature set into a trained intelligent decision model, and outputting training decision data information; wherein the intelligent decision-making model is configured with a composite reward function adjusted based on a key influence factor; and generating a training course push instruction according to the training decision data information, and optimizing the intelligent decision model. By collecting multi-dimensional information data of employees and capturing space-time correlation between an employee ability growth curve and a post demand evolution trajectory, a recommendation strategy can respond to ability updating, post iteration and strategic adjustment in real time, and the hysteresis problem of static planning is thoroughly solved. And meanwhile, based on dynamic adjustment and optimization of a composite reward function in the intelligent decision model, deep binding of training management and organization strategy is realized.

The invention relates to the technical field of sailor assessment management, and particularly discloses an online management method and system based on sailor assessment, and the method comprises the steps: collecting an original voice signal during sailor assessment, and a propeller rotating speed, a sea condition grade and a ship navigational speed at a corresponding moment; the original voice signals and the physical parameters are input into a physical constraint noise reduction network to serve as a regularization item embedding loss function, ocean background noise is separated, and pure sailor voice signals are output; inputting the pure sailor voice signals into a navigation term recognition network, calculating the similarity between voice features and IMO standard term prototype vectors, and outputting term accuracy scores and term confusion point information; based on the pure crew voice signal, the term accuracy score and the sea condition level, a voice signal-to-noise ratio, term accuracy and a sea condition influence factor are fused to calculate a communication capability index; generating a personalized performance evaluation report and pushing training courses; according to the invention, the problems of difficult voice noise reduction and disjunction between evaluation and training in a complex marine environment are solved.

This invention provides a power trading training system, belonging to the technical field of training systems. The system includes: a login module: upon detecting a user's login, it verifies the user's legitimacy based on the power trading training platform, grants the user login privileges, and stores the corresponding login information in a database; a course assistance module: after successful login, based on user privileges and a decision support mechanism, it performs a time-limited key verification and matching to decrypt the encrypted user-specific training courses; a learning module: based on the user's learning hours for decrypted courses during the training period, it obtains a first learning pass status and a second learning pass status based on the final exam results for all decrypted courses, and obtains a learning pass score for each decrypted course; a ranking module: based on an indicator evaluation model, it obtains the weight of each decrypted course for the user and, combined with the learning pass score, generates a corresponding ranking. This provides a convenient training method and improves training efficiency.

1. The name of the design product: bank insurance intelligent training graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the intelligent training of new bank insurance personnel. 6. The human-computer interaction mode of the graphical user interface: the front view is the homepage of the intelligent training interface, the user clicks the "go to complete" button on the right side of the "new person area" in the front view, enters the interface change state diagram 1; the interface change state diagram 1 displays the interface of the new person area online learning course card, the user clicks the "onboarding training" button in the interface, enters the interface change state diagram 2; the interface change state diagram 2 displays the interface of the new person area onboarding training course card, the user clicks the "linkage training" button in the interface, enters the interface change state diagram 3; the interface change state diagram 3 displays the interface of the new person area linkage training course card, the user clicks the blank part of any course card in the interface, enters the interface change state diagram 4; the interface change state diagram 4 displays the course details interface. 7. Other circumstances that need to be explained: "XXX" in the interface represents replaceable text content, and the solid color block in the interface is a replaceable image.

The application discloses a fusion enterprise training course intelligent diagnosis recommendation system of deep learning, including: including: course data multidimensional acquisition module, student behavior characteristic extraction module, training demand intelligent diagnosis module, deep learning course matching module, recommended result dynamic optimization module, system running state monitoring module; through multidimensional acquisition of internal and external courses and student behavior data, deep pattern and preference are mined through feature extraction, knowledge short board and potential demand are determined through hierarchical analysis of the training demand intelligent diagnosis module, a multidimensional correlation model is constructed through the deep learning course matching module to realize accurate matching, the recommended result dynamic optimization module is combined to iteratively adjust the scheme according to real-time feedback, and the system running state monitoring module guarantees stable and efficient operation of each link. The system effectively improves recommendation accuracy and dynamic adaptability, improves training resource utilization, and meets the personalized and efficient demand of enterprise talent training.

The invention relates to the technical field of official business ship crew training, and provides an official business ship crew post capability grading training method and system, and the method comprises the steps: constructing a crew post capability matrix, and generating a plurality of pieces of quantitative capability information according to a plurality of pieces of professional direction information; according to a preset law enforcement scene and the quantitative capability information, generating a differentiated post capability standard; establishing a stepped training course library, and dividing courses in the stepped training course library into basic qualification courses, advanced promotion courses and actual combat strengthening courses; historical training data, real ship operation performance and post demand data of the sailors are acquired to generate a personalized learning scheme; a knowledge graph technology is utilized to diagnose weak ability links of the sailors, and complementary training contents are automatically matched; and according to the simulators and the real ship resources corresponding to the preset maritime affair colleges and the practical training bases, constructing practical operation tasks including different law enforcement scenes, and generating subsequent training courses and learning schemes.

FIELD: restorative medicine.SUBSTANCE: used to teach people with tetraplegia how to put on and take off socks independently. In a patient with tetraplegia, the range of motion of the upper body is determined within 5–15°, the presence of a hook grip with one finger of the hand. To perform the exercises, socks are used, on the sides of which two loops or two rings are attached to the top of each sock, or two holes are made for hooking with the fingers. Moreover, if the disabled person has the ability to perform movements of the upper body within 5°, then they are used to put on and take off socks with loops or rings. If a disabled person is unable to insert fingers into soft loops, metal rings with a diameter of 3 cm, made of an iron-nickel alloy, coated on the inside with polymorphus thermoplastic, are used. If the disabled person has the ability to perform bends from a sitting position within 6–15° and returning to the starting position without using the hands or with one hand, then holes with a diameter of 3 cm are made on the sides of the toe. Next, a course of 15 individual training sessions is carried out by an occupational therapist for 40 minutes daily in the morning in the presence of a caregiver, with 3-minute breaks every 10 minutes for the disabled person to rest. In the first 6 sessions, the disabled person learns to put on a sock on one foot, alternating feet every day. From the 7th session, the lesson includes training in putting on and taking off socks for 20 minutes on each foot. From the first day of classes, the disabled person and the caregiver practice putting on and taking off socks from each foot once in the evening. On weekends, put on and take off a sock from each foot twice a day, morning and evening. During independent exercises, the disabled person sits, and the caregiver places the shin of the leg on which the sock will be placed across the thigh of the other leg. The disabled person bends his body within 5–15° and throws the sock over the toes. Then, straightening up and leaning the torso back, the disabled person pulls the sock onto the forefoot. In this case, the disabled person leans back and turns the body in the same direction as the leg being put on, and pulls the sock onto the heel. Next, tilting the body to the side of the leg being put on, the disabled person pulls the top of the sock onto the shin. The caregiver lowers the disabled person's shin to the floor; to remove the sock, use a hook grip with the thumb of the hand opposite the leg. The disabled person grasps the loop, or ring, or hole on the inside of the sock and moves the toe down and toward the front of the foot, bending and turning the torso forward and to the side opposite the leg being undressed within 5–15°.EFFECT: social and everyday adaptation of disabled people with tetraplegia.1 cl, 4 dwg, 3 ex

The invention relates to the field of fitness equipment, in particular to an interaction method of sports equipment and a control knob, the sports equipment, the knob and a mobile terminal are included, the knob is arranged on the sports equipment and electrically connected with a driving module of the sports equipment, and the mobile terminal is in communication connection with the knob; according to personal information, an AI training course which is more adaptive to a user is generated, the AI training course is imported into a rotary knob through communication with the rotary knob, the rotary knob controls sports equipment according to the speed requirement, the time requirement, the gradient requirement and the like of the AI training course, and the training effect is effectively improved.

The present application provides a car training system capable of appropriately evaluating driving of a driver. The car training system has a car capable of traveling on a training course, and a control device that acquires driving information of the driver when the driver drives the car on the training course, and extracts an inappropriate action in driving of the driver based on the acquired driving information and demonstration information that becomes a demonstration when the driver drives the car on the training course.

The invention provides a training course generation method and device. The training course generation method comprises the steps of obtaining course generation prompt information; the course generation prompt information is input to a course generation model, a to-be-trained course output by the course generation model is obtained, the to-be-trained course is generated according to course structure description information, the course structure description information is generated according to action structure information, and the action structure information is generated according to at least one data type; the data type is determined according to the course generation prompt information. According to the method, the to-be-trained courses suitable for learning and training of the user can be automatically output, the course generation model can adapt to different types of multi-modal input of the user, the limitation on user input is reduced, the input content cost can be reduced, high-quality courses are automatically produced, and the user experience is improved. The method can be used in multiple fields of artificial intelligence private teaching, personalized training schemes, automatic content production and the like.

The present application relates to a kind of based on electroencephalogram data and deep learning model's meta-cognition training method, comprising: through electroencephalogram equipment, the brain cognitive information data of participant is collected to carry out data preprocessing;Through fourier transform, the original electroencephalogram data obtained is transferred to the energy value on the preset frequency domain wave band, and the brain cognitive information data is obtained by calculating timing energy value;The brain cognitive data set obtained is divided into label set and feature set to carry out data marking and screening;According to brain cognitive preset training course, on-site teaching is carried out, and the training state and brain cognitive data form of participant are observed and recorded, form the label set corresponding to brain cognitive data set, for the model training of next step;LSTM network model is constructed, and brain cognitive data set is proportionally split into training set and test set to carry out model training;The training model currently obtained is verified and model is corrected, and the state of participant is automatically marked using training model, and report is generated for reference.

The invention discloses a team standardized construction informatization management system and method and a medium, and relates to the field of informatization management, and the system comprises a data collection module which is used for collecting team field data of a team production field in real time; the information management module is used for carrying out digital management on information of team basic management, team scheduling, safety activities, double prevention mechanisms, educational training and emergency management; the real-time monitoring module is used for dynamically monitoring the team field data and performing early warning when each monitoring index of the team field data exceeds a respective corresponding early warning threshold value; the data analysis and decision support module is used for analyzing the collected team field data to obtain a data analysis result; and the training and assessment module is used for providing online training courses according to the requirements of team members, and standardization, informatization and high efficiency of team safety management are realized.