224 results about "Training evaluation" patented technology

The present invention analyzes the impact of known or unknown events on the fulfillment of business goals. In light of a defined business strategy, a performance outcome related to the business goal is analyzed to determine the effect of an event on the business goal. For training evaluation, the actual impact of training given for particular skills on job and business performance is readily determined.

The invention discloses an unmanned aerial vehicle simulation training system and a control method of the unmanned aerial vehicle simulation training system, and relates to the technical field of simulation training. The unmanned aerial vehicle simulation training system comprises human-computer interaction unit, a training unit, a behavior interaction unit, a virtual simulation model unit, a training evaluation data unit and a multimedia source unit. The human-computer interaction unit provides a visual window of a virtual unmanned aerial vehicle three-dimensional simulation model. The training unit provides a system operation manual, and represents a guide unit, an exploration unit and an assessment unit. The behavior interaction unit converts instructions of the human-computer interaction unit into control instructions on the virtual unmanned aerial vehicle three-dimensional simulation model, and drives the corresponding virtual simulation model unit to act. The virtual simulation model unit provides appearance and function states of the virtual unmanned aerial vehicle three-dimensional simulation model. The training evaluation data unit records operation behavior in the evaluation process, judges operation correctness and displays and stores the evaluation result. The multimedia source unit provides multimedia sources of equipment. The unmanned aerial vehicle simulation training system and the control method of the unmanned aerial vehicle simulation training system are high in interactivity and autonomous learning capacity, and training missions are carried out conveniently.

The invention discloses an intelligent training system and method; the system comprises a training teaching module, a motion determination analysis module and a motion acquisition module; the motion acquisition module is used for acquiring user motion posture information and user life index data in motion, and sending the data to the motion determination analysis module; the motion determination analysis module is used for building a motion model, using the motion model to analyze the user motion posture information and user life index data, obtaining an analysis result, and sending the resultto the training teaching module; the training teaching module is used for displaying training teaching contents, and displaying the analysis result of the motion determination analysis module for theuser in real time. The motion determination analysis module further forms user motion training evaluation, suggestions and a whole motion condition report according to the analysis result; based on artificial intelligence technology, the motion determination analysis module can interact with a cloud server or be deployed on the cloud server; the motion determination analysis module makes postureidentification according to the user posture information acquired by the motion acquisition module, builds a user real time motion model and analyzes user motions according to standard postures in real time, and combines with the user motion life index data, thus obtaining the analysis result. The method and system acquire the user motion posture information and the user motion life feature indexdata, build the motion model and make real time comparison and analysis, make training evaluation and suggestions for user motions without needing artificial participation, thus training and guiding user motions in real time.

The invention provides an information processing method and device implemented by a computer. The method comprises the following steps: acquiring data of a plurality of training evaluation objects, constructing a knowledge map, and creating a map database based on the knowledge map, wherein nodes of the knowledge map are evaluation objects or association objects having an association relation with the evaluation objects, and sides of the knowledge map describe the relation between the nodes and have corresponding weights; calculating feature vectors of the training evaluation objects based on the distances between the training evaluation objects, wherein the distance is at least based on a path weight between the training evaluation objects, and the feature vectors indicate the number of other training evaluation objects in the map databases with different dimensions within a certain distance for the training evaluation objects; using the feature vectors and the evaluation categories of the plurality of training evaluation objects as a sample set, and creating an evaluation module; responding to received data of a new evaluation object, calculating the feature vector and an evaluation index of the new evaluation object; and completing an audit operation of the new evaluation object by the computer according to discrimination conditions based on the evaluation index.

The invention discloses an upper limb training system based on monocular video human body action sensing. The upper limb training system comprises a computer and a video camera, wherein the video camera performs video data transmission with the computer, and is used for capturing the human body movement and transmitting the video data through a USB (Universal Serial Bus); the computer is used for receiving the video data, analyzing the video data, completing the hand moving trace tracking and identifying the gesture action according to the tracking result; and the computer is also used for realizing the interaction with a game platform, obtaining a training evaluation parameter and feeding the training evaluation parameter to a user. The training system has the advantages that a quantitative evaluation system is used; the training initiative of a user can be aroused; the defects of the existing training measure are overcome; and the upper limb training system can be applied to communities and families. The immersion feeling of the virtual reality technology of the training system is strong; the interestingness of the training process and the enthusiasm of the user are enhanced; and meanwhile, the safety of the user in the training process is improved by the virtual reality technology.

The invention provides a Hadoop malicious node detection system based on network behavior analysis for protecting the internal security of a cluster in view of a present situation that most malicious programs have certain network behaviors and even permeate inside the cluster to perform malicious behaviors. The Hadoop malicious node detection system comprises a network behavior monitoring module, a node log analyzing module, a node load analyzing module, and a training evaluation module malicious detection module. The network behavior monitoring module, the node log analyzing module, and the node load analyzing module operate on each node to acquire, monitor and preliminarily analyze information. The training evaluation module malicious detection module operates in an analysis host, performs model training and malicious detection after receiving information acquired by each node, and updates and stores the model regularly.

The invention provides a self-adaptive dynamic planning control method and system for a large-scale energy storage power station. The method includes steps of setting a structure and control target parameters of a self-adaptive dynamic planning control system; initiating the parameters and importing an initial state of a controlled object; calculating the original wind electricity power fluctuation rate of a current moment t and performing smoothing treatment on the original wind electricity power by using a change rate control method; calculating the wind storage power fluctuation rate subjected to the smoothing treatment, the energy storage power and the SOC (State Of Charge) of the energy storage system; initiating a training evaluation module and an evaluation module; calculating and saving the control strategy, the wind storage power fluctuation rate, the energy storage power and the SOC of the energy storage system of each moment; outputting the control strategy, the wind storage power fluctuation rate subjected to the smoothing treatment, the energy storage power and the SOC of the energy storage system of each moment. The system includes a parameter initializing module, a data acquisition and calculation module, an execution module, an evaluation module and an output module and the like. By adopting the method and system provided by the invention, optimization control of the large-scale energy storage system is realized and the technical economical efficiency of the energy storage system is improved.

The invention belongs to the technical field of physical fitness training, and provides an advanced type physical training system and method. The system comprises a remote server, a management terminal, a collection terminal, a wearable terminal and site terminals located on N training sites, each site terminal comprises a display terminal, a fingerprint identification device, a camera and a loudspeaker, the display terminals are electrically connected with the fingerprint identification devices, the cameras and the loudspeakers respectively, and the remote server is in communication with themanagement terminal, the collection terminal, the wearable terminal and the display terminal separately; the remote server includes an index acquisition unit, a scheme selection unit, a monitoring recommendation unit and a training evaluation unit. By means of the advanced type physical fitness training system and method, the optimal training scheme is selected by evaluating the physical fitness of an exerciser, teaching videos are applied to assist a coach in teaching in the training process, music is played to help and encourage the exerciser to complete training, the exercise data of the exerciser is collected in real time, and the occurrence of accidents is prevented.

A medical training apparatus that is capable of recording a training history based on a medical training scenario and storing an evaluation of training that corresponds to the training history is provided. The medical training apparatus includes a training-history-information storage unit, an evaluation input unit, an operation unit, and a training-evaluation-information storage unit. The training-history-information storage unit stores history information about a training session that has been performed under a preset medical training scenario. The evaluation input unit inputs an evaluation result for either the training session or the history information stored in the training-history-information storage unit, with respect to a predetermined evaluation item for each predetermined matter. The operation unit performs an arithmetic operation on the evaluation result that has been input with the evaluation input unit. The training-evaluation-information storage unit stores the result of operation unit and the evaluation result in association with the history information.

The invention relates to a dance training evaluation system based on a digitized place and a wireless motion capture device. Two-dimensional plantar pressure distribution information and space posture information of a dancer are synchronously collected through the digitized place and the wireless motion capture device in real time, and motion information of the dancer is obtained through information fusion and sent to a computer through the Ethernet; the computer drives a human body model to move in a three-dimensional space through data of the motion information, the motion reconstruction of the dancer is achieved, and meanwhile biomechanics parameters and kinematics parameters of motions are extracted, analyzed and displayed; dancing postures of the dancer are evaluated online by establishing a dancing motion template and a knowledge base, and guidance and demonstration are achieved for the dancer in real time. On the basis of the movable digitized place which can be spliced and the wearable wireless motion capture device, the motion information of the dancer can be captured on the premise of not influencing the dancing motions of the dancer, and the dance training evaluation system is suitable for teaching training and evaluation of various dances.

The invention discloses a power transmission line inspection-based multi-rotor unmanned aerial vehicle inspection operation simulation training system. The power transmission line inspection-based multi-rotor unmanned aerial vehicle inspection operation simulation training system is established by using the virtual reality technology. The system includes a training host as well as an unmanned aerial vehicle remote controller, a keyboard, a mouse, a display, and a virtual reality helmet which are all connected with the training host in a wireless or wired manner; the training host is the mastercontrol device of the system, and is provided with a virtual unmanned aerial vehicle flight control simulation unit, a virtual unmanned aerial vehicle flight simulation unit, a training evaluation management unit, a defect location and identification unit, a database unit and a background management unit; the unmanned aerial vehicle remote controller, the keyboard and the mouse are all the inputdevices of the system; and the display and virtual reality helmet are the display devices of the system. The simulation training system of the present invention can be used not only to improve the unmanned aerial vehicle inspection operation control skills of operators and but also to prevent unnecessary loss of personnel, grid lines, or unmanned aerial vehicles due to the improper handling of special circumstances.

The invention discloses a social network user behavior prediction method based on quantified social influence. The method comprises the following steps: data crawling, data preprocessing, network graph construction, user interesting extraction, inter-user influence quantification, modeling prediction, and model training evaluation. The prediction method is mainly used for predicting the user behavior such as tweeting behavior on the Twitter of the social network in the large-scale social network. Compared with the prior art, the method disclosed by the invention further considers the quantification of inter-user social influence in the social network, and the quantified influence is brought into a prediction model, so that the prediction model can sufficiently consider the influence on the user behavior by other users around a given user; and the user behavior is predicted from the angle of the user interests, the interests of the user are computed through the quantified social influence, and the user behavior is speculated through the user interests at last, and the method has higher accuracy.

The invention relates to a wearable physical training evaluation system and an evaluation device. The system comprises an intelligent terminal, a microprocessor, a sign parameter collection unit, a kinetic energy consumption measuring unit and an abdominal fat content measuring unit, wherein the intelligent terminal is used for collecting and storing human personalized parameters; the abdominal fat content measuring unit, controlled by the microprocessor, is used for collecting electrical impedance information in an abdomen by a corresponding fat depth; the intelligent terminal, in accordance with the electrical impedance information in the abdomen by the corresponding fat depth and the human personalized parameters, is used for computing a fat content, and is used for making a physical training scheme of a corresponding intensity in accordance with the fat content in the abdomen as well as the human personalized parameters; the microprocessor is used for controlling the kinetic energy consumption measuring unit to collect human motion heart rates and a motion acceleration, and the intelligent terminal, by virtue of the human motion heart rates, the motion acceleration and the human personalized parameters, is used for calculating kinetic energy consumption; and the microprocessor is used for controlling the sign parameter collection unit to collect human sign parameters, and the intelligent terminal is used for judging whether an abnormity occurs in the sign parameters, if so, outputting an alarm signal.

The invention belongs to the technical field of oilfield seismic big data reconstruction, in particular to a seismic data reconstruction method based on a generative adversarial network. The seismic data reconstruction method comprises the following steps: seismic slice data reduced to the uniform size are used as a training set; the training set is trained by using a deep convolution generative adversarial network, and the Wasserstein distance is used as the training evaluation index of aseismic data generation model; and the seismic data generation model is applied to reconstruct the seismicdata, and the back propagation algorithm and the optimization algorithm based on the standard gradient are applied to optimize the gradient of the objective function so that the difference between the reconstructed data and the missing data is minimized. The method has the beneficial effects that the problem that the traditional seismic data reconstruction algorithm needs to meet the limitation of Nyquist sampling theorem is solved; the problem that it is difficult to select the sparse base for seismic data reconstruction by using the compression sensing algorithm is solved; and the problem that the compression sensing algorithm and the traditional reconstruction algorithm have poor reconstruction effect under the condition of extremely low sampling rate is solved.

The invention discloses a basketball shooting training evaluation system, comprising a basketball shooting training apparatus, a video acquisition module, a vital sign acquisition module, a data processing module, a movement standard judging module, an auxiliary guide module, a three-dimensional teaching module, a comprehensive evaluation module, a vital sign state evaluation module, a human-machine operation module and a central processing unit. The basketball shooting training evaluation system provides automatic judging and guiding for basketball shooting movements; three-dimensional projection is used in the training process such that a trainee has a vivid feeling of being there, it is convenient to observe and learn basketball shooting movements at multiple angles, and training efficiency is improved; in addition, it is possible to coordinate a training obstacle, a mechanical arm and the like, such that different training environments are created for the trainee.

A medical training apparatus that is capable of recording a training history based on a medical training scenario and storing an evaluation of training that corresponds to the training history is provided. The medical training apparatus includes a training-history-information storage unit, an evaluation input unit, an operation unit, and a training-evaluation-information storage unit. The training-history-information storage unit stores history information about a training session that has been performed under a preset medical training scenario. The evaluation input unit inputs an evaluation result for either the training session or the history information stored in the training-history-information storage unit, with respect to a predetermined evaluation item for each predetermined matter. The operation unit performs an arithmetic operation on the evaluation result that has been input with the evaluation input unit. The training-evaluation-information storage unit stores the result ofoperation unit and the evaluation result in association with the history information.

The invention relates to a statistic marking method of a power grid interconnection training simulation system, and belongs to the field of electric power system dispatching automation and simulation. The statistic marking method of the power grid interconnection training simulation system is characterized by comprising the steps that a comprehensive training evaluation and statistic function is achieved based on a 'weighted deduction method'; and a benchmark score is set firstly, then the coefficients of difficulty of teaching plans are determined according to the difficulty each teaching plan, and the teaching plans are subjected to automatic classification and weighted deduction to obtain final scores according to several aspects, such as misoperation, power supply reliability, safety and economical performance, of power grid operation in a training process. Self-definition and management of marking standards are realized; different marking modes can be defined and selected according to the different power grid simulation training teaching plans so as to meet different requirements of users on selection and emphasis of training content; automatic full-time recording of the simulation training process is realized; the power grid interconnection training simulation system conducts automatic evaluation and records all operation conditions of teachers and students, power grid equipment and current distribution conditions in the training process at the same time so as to provide marking bases; on-line statistics, evaluation and issue based on interconnection training simulation are realized; and the fact that combined training operation conditions and evaluation scores in each sub system are inquired according to user rights is supported. The statistic marking method of the power grid interconnection training simulation system provides an on-line statistic marking method for training simulation of power grids at different levels, and has important significance for improving the practicability of the power grid interconnection training simulation system.

The invention discloses a criminal investigation actual combat intelligent training assessment system based on a VR technology and a creation method. The assessment system comprises an investigation VR host, investigation VR equipment, an assessment subsystem, a trace material evidence editor, a trainee mobile client and an investigation practical training big data platform which are connected with an investigation practical training data server. According to the invention, the technical problems of unreal investigation operation and too large operation error in a virtual scene and poor user experience are solved through binding and manufacturing of the investigation tool and the trace material evidence. In addition, the technical threshold that differentiation is difficult to realize in investigation and practical training is broken through by establishing investigation and practical training big data and establishing an investigation and practical training evaluation neural network;meanwhile, the trainees can participate in training or assessment in respective units at any time through the network, the training organization does not consume time, labor and money any more, and the manpower, material and financial costs are greatly reduced.

The invention discloses an evaluation model selection method and device, computer equipment and a storage medium. The evaluation model selection method comprises the steps: inputting training samplesinto an evaluation model in batches for training; according to a preset rule, selecting an evaluation model needing to be subjected to a first test from the evaluation models trained in batches, and marking the evaluation model as a to-be-evaluated model; respectively inputting a first preset number of first test samples into each to-be-evaluated model, carrying out the first test, obtaining a first test result, and calculating first accuracy of each to-be-evaluated model; after training of the evaluation models is completed, selecting a specified number of preferred evaluation models, carrying out a second test, and calculating a second accuracy rate of each preferred evaluation model; and selecting an optimal evaluation model according to the second accuracy. According to the invention,the optimal evaluation model can be quickly selected from a plurality of training evaluation models.

The invention relates to the train shunting simulation technical field, and specifically relates to a railway shunting 3D simulation practical training evaluation system comprising an application server, client ends, a data pool, a database, and an evaluation management system; the application server receives feedback information from a plurality of client ends, and distributes said information; the application server communicates with the data pool about the locomotive, signalling unit and track switch equipment state information sent by the client ends; the client ends read the data pool information so as to real time update the inherent equipment states in a station yard; the application server writes a test question flow, scores and student information into the database, and distributes management messages to the evaluation management system. The system uses the VR virtual reality technology to simulate a virtual shunting work scene in a three dimension space, can directly dynamically display the shunting works, so students can finish the shunting works in visual, hearing and touch sense organ simulation experiences, thus greatly improving usage and training effects.

The invention discloses a service platform for guiding exercise based on evaluation feedback. The service platform comprises a user classifying management module, an information release system, a motion testing system, an evaluation feedback system, an action management system module and a course management system module. The evaluation feedback system carries out classification through user subjective feeling evaluation, different kinds of feedback of the systems are obtained through different kinds of feeling evaluation, and the exercise intensity of next training is pushed according to the feedback. Targeted and scientific training courses can be provided for users according to the self conditions of the users and the exercise testing result, the training plan can be adjusted in time according to the training evaluation and feeling of the users in combination with the testing condition of training in the training process of the courses, the training intensity is arranged more scientifically, and therefore the exercise training effect of the users is improved.

The invention provides a cognitive disorder training and evaluating system and method. The system comprises a client, a web layer, a background service layer and a data storage module; the client establishes connection with the web layer, initiates a request for cognitive impairment training evaluation and indicates a user identifier; the background service layer determines whether to provide a cognitive impairment training evaluation scale for the user or not by matching the user identifier according to the received cognitive impairment training evaluation request, so that the user answers questions; and the background server receives answer data of the cognitive impairment training evaluation scale submitted by the user and stores the answer data in the data storage module for subsequentquery of the user. According to the invention, the efficiency and operability of cognitive assessment can be improved.

The invention belongs to the field of somatosensory interaction and particularly provides an exercise training evaluation method based on a virtual environment. The method comprises the following steps that 1, a virtual teaching platform is established; 2, exercise trajectories are calculated; 3, exercise training is evaluated. The virtual teaching platform designed by adopting Unity 3D uses skeleton points acquired by Kinect V2 as a basis, keeps 30 frames per second to acquire standard vectors of standard actions and coordinates of spine points and calculates heights of standard action persons. By comparing the heights of persons participating in training with the heights of the standard action persons, offset coordinates of the spine points are determined, spatial exercise curves of standard actions are calculated according to the skeleton lengths of the persons participating in training, and accordingly continuous exercises are identified and graded.

The invention relates to the technical field of medical rehabilitation, and particularly relates to a rehabilitation training system and method based on the AR technology. The system is applied to the method. The system comprises an action sensor, AR glasses and a server, wherein the action sensor is used for collecting limb action information of a patient; the AR glasses comprise a camera used for collecting real scene information in real time; the server comprises a data storage module which is used for receiving the limb action information, the real scene information and rehabilitation training plan information, a game management module used for selecting a rehabilitation training game, a data processing module used for transmitting the image information to the AR glasses and calculating the completion degree of the rehabilitation training game, and a training evaluation module used for performing completeness evaluation. The problems that different supervisors perform different evaluation on whether a bedridden patient completes the rehabilitation training plan in a qualified manner or not due to subjectivity of people, so that the interest of the bedridden patient in rehabilitation training is insufficient, and the rehabilitation training effect are poor are solved.

The invention discloses a deep reinforcement learning model training method and device based on hyper-parameter optimization, wherein the method comprises the steps of obtaining a plurality of initial hyper-parameter combinations and a plurality of first deep reinforcement learning models; training a plurality of first deep reinforcement learning models by adopting a plurality of hyper-parameters in the initial hyper-parameter combination to obtain training evaluation indexes respectively corresponding to the plurality of first deep reinforcement learning models; screening out a second deep reinforcement learning model from the plurality of first deep reinforcement learning models according to the training evaluation index; performing optimization processing on the initial hyper-parameter combination by adopting a plurality of target hyper-parameters corresponding to the second deep reinforcement learning model to form a target hyper-parameter combination; and obtaining a target deep reinforcement learning model. Therefore, hyper-parameter optimization and model training are combined to achieve training of the deep reinforcement learning model, the deep reinforcement learning model with higher performance can be trained, and the trained model can adapt to wider application scenes.

Examples related to facilitating the training, assessment, and dispatching of technicians to a customer location for at least the purpose of servicing or repairing machines, devices, or systems present at the customer location are presented. The technician can be selected for dispatch to the customer location by review of database information, including training information for the technician, among other things. While at the customer location, the technician can be provided with training information delivered via a training module, where such training material content can comprise written materials, photos, video, virtual assistance, remote assistance, games, or the like. The technician can generate videos or other collateral while at the customer location, which can be included for use in a library of training materials for subsequent use, or for other purposes. Various systems and processes for facilitating the selection, management and deployment of training materials for technicians are also provided herein.

The invention discloses a distribution network fault judgment training evaluation method based on a locus array. The method comprises: establishing a fault isolation standard rule array FIS; establishing a standard fault isolation range equipment set C; establishing a fault isolation operation locus array FIP, and determining a fault isolation range equipment set CP via the fault isolation operation locus array FIP; determining an anti-misoperation rule array MOR; according to the matching situations between the fault isolation operation locus array and the fault isolation standard rule array and between the fault isolation operation locus array and the anti-misoperation rule array, giving a fault isolation operation sequence and time evaluation method; giving a fault isolation range evaluation method according to the inclusivity of the fault isolation range equipment set CP and the standard fault isolation range equipment set C; and determining a distribution network fault judgment training evaluation method based on a locus array. The evaluation method can well reflect a dispatcher's operation process of fault isolation, and has good practical training evaluation significance.

The invention discloses an intelligent training evaluation system and method, and the system comprises: an intelligent training evaluation website which is used for issuing training registration information to remind a user of registration according to a preset training plan; a resource management module which is used for establishing learning resources according to a preset training plan; an online learning module which is used for providing online learning according to the learning resources; a question bank module which is used for providing tests according to the learning resources; a personal center module which is used for performing personal data management according to the online learning result, the learning resources and the test result; and a training housekeeper module which isused for establishing a training project according to the registration result, the learning resources and the test result, and the training project comprises training effect feedback. According to the invention, training effects of high efficiency, low cost, timely mastering of self conditions by users and good feedback can be achieved. The system and method can be widely applied to the technicalfield of Internet of Things.

The invention provides a simulation system for oil spill accident simulation training, which is characterized by comprising a simulation model database, a three-dimensional modeling module, a port modeling module and an emergency plan simulation module, wherein the three-dimensional modeling module comprises a self-defined simulation model calling sub-module, a simulation model establishing sub-module and a particle editing sub-module; the port modeling module is used for comprising a large-scale three-dimensional scene modeling sub-module, an oil spill accident scene editing sub-module and a line and viewpoint editing sub-module; the emergency plan simulation module comprises an overflow information simulation sub-module, an oil spill warning and emergency guarantee visualization sub-module, an emergency disposal deduction sub-module, a pollutant control removing operation visualization sub-module and a training evaluation sub-module. The simulation system provided by the invention solves the problem that a conventional simulation system cannot carry out the oil spill accident simulation training, and can replace currently conventional practical exercise; feasibility of an oil spill accident emergency disposal scheme can be predicted and bugs of a preset scheme can be found under low cost; risks of the scheme are evaluated; experience and lessons are summarized.

The present application relates to the field of training management, in particular to an employee training evaluation method based on big data analysis and related equipment. The invention Gives the user the right to use the training platform and obtain the training materials uploaded by the user; Calling a violation list composed of violation characters, querying and obtaining the content of thetraining materials, and comparing the content with the content in the violation list; Obtaining a material keyword of the training material, obtaining a material classification table and an employee classification table, comparing the material keyword with the material classification table and the employee classification table respectively, obtaining the training personnel situation correspondingto the training material, and scoring the learning status of the training personnel; Send test questions to the trainer to obtain the training effect of the trainer. This application is aimed at the skill training of the employees of the enterprise, so that the training materials of different kinds and different grades can be accurately matched with the employees to be trained, thereby reducing the possibility of the leakage of the enterprise materials.