177 results about "Training simulation" patented technology

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

The invention relates to the technical field of training simulation, and discloses a VR-based gas safety emergency training system, which comprises a three-dimensional scene construction module, an interactive data acquisition module, an interactive data processing module, an examination data analysis module and an examination evaluation module, entity drilling is replaced, the same scene can be repeatedly trained for infinite times, and the training cost is remarkably reduced; the VR technology provides multi-sensory stimulation, the intuitive cognition of students on danger is enhanced, the safety awareness and the emergency response capability are effectively improved, and no danger exists; by collecting operation data of students, the system automatically calculates key coefficients such as equipment operation precision, process compliance, disposal timeliness and path planning rationality, and scientific quantification and accurate scoring of training effects are achieved; and automatic grading evaluation is carried out according to a grading result, and a customized remedy module is triggered for students with insufficient abilities, so that a'training-assessment-intervention 'closed loop is formed, and the overall training efficiency is improved.

The invention discloses artificial intelligence running equipment for physical training and relates to the field of treadmills, the artificial intelligence running equipment comprises a running platform, T-shaped sliding blocks are symmetrically arranged on the two sides of the running platform, T-shaped sliding grooves are formed in the outer wall of the running platform along the circumference, the two T-shaped sliding blocks are slidably connected with the T-shaped sliding grooves, and a support is arranged on the running platform; the support is composed of a first supporting rod, a second supporting rod and a transverse rod, the two T-shaped sliding blocks are fixedly connected with the outer walls of the bottoms of the first supporting rod and the second supporting rod respectively, a sliding rod is connected to the lower portion of the transverse rod, and a plurality of touch assemblies are distributed on the front face and the back face of the touch vest. The plurality of touch assemblies are used for the user to experience specific touch in the physical training simulation scene; the touch assemblies are reasonably distributed in the vest, and the airflow assemblies are arranged, so that when a user carries out physical training, training scenes in various complex environments can be simulated more truly, and the immersion feeling and the effect of training are effectively enhanced.

The invention discloses an unmanned aerial vehicle operation skill training system based on deep reinforcement learning, and the system comprises the following modules: an operation behavior data collection module which is used for constructing an operation behavior data set; the data preprocessing module is used for generating a time sequence joint input tensor; the behavior transformation module is used for outputting an operation behavior representation vector; the parameter updating module is used for carrying out non-momentum mode iteration updating on the training parameters of the behavior transformation Transform module based on a Lion optimizer; the disturbance adjusting module is used for obtaining disturbance behavior representation; the decoding module is used for decoding the disturbance behavior representation into a control action sequence; the reversible motivation generation network module is used for reasoning to obtain a reconstructed motivation vector; the motivation comparison module is used for identifying target cognitive deviation; and the training scheduling module is used for outputting a new training scene and a control strategy to the training simulation environment. According to the method, deep reinforcement learning and motivation modeling methods are fused, and personalized training of unmanned aerial vehicle operation skills is realized.

The invention belongs to the technical field of electric power automation, and discloses a DTS intelligent interaction method and system fusing a large language model and a vector database, and the method comprises the steps: obtaining the text data of an electric power regulation and dispatcher training simulation system DTS field, and constructing a semantic vector knowledge base; based on the constructed semantic vector space mapping and knowledge base, performing problem reconstruction representation on the proposed problem, and then converting the problem reconstruction representation into a vector through an embedded network; retrieving in the constructed semantic vector knowledge base based on the converted vector, calculating the comprehensive similarity between the problem vector and the vector in the knowledge base, and retrieving the most relevant knowledge fragment; and driving a large language model to generate a final intelligent question and answer response by taking the most relevant knowledge fragment and a dialogue context provided by a memory mechanism as input. Efficient, accurate and intelligent questioning and answering of complex dispatching business problems are achieved, and a new artificial intelligence interaction tool is provided for training of a digital intelligent novel power system dispatcher.

A system and method AI-enabled telematics and actuation for electronic entertainment, simulation, training, and remote operations systems. The system and method disclosed support neuro symbolic reasoning and generative AI enabled experience generation to allow a user or collection of users to experience a wide range of realistic scenarios where the user can pick and choose an experience that best fits their individual or collective preferences. Additionally, the system and method have wide applications to a variety of environments, including but not limited to, racing, sports, military training, vehicle and aircraft operation, and training simulations. The proposed system and method enable realistic, immersive video game, simulation, training, and remote operations environments which are applicable to a wide range of devices, platforms, and mediums for recreational, commercial, industrial, and security uses.

The present application relates to the technical field of electronic digital data processing, and particularly relates to a simulation optimization method and apparatus for a network architecture of an intelligent computing center, and a device and a medium. The method comprises: acquiring training configuration information of a large language model to be trained; on the basis of the training configuration information and a preset discrete event simulation strategy, using a preset simulator to perform training simulation on said large language model, so as to obtain a simulation result, wherein the preset simulator is obtained by using a preset ECS framework; and on the basis of the simulation result, adjusting a network architecture of an intelligent computing center, and obtaining an optimal network architecture of the intelligent computing center. In this way, a network simulator of an intelligent computing center is designed by using an entity component system framework, such that a complete simulation process of the training of a large language model can be implemented, so as to search for the optimal network architecture of the intelligent computing center; and the problem of it not being possible to support the simulation of a large-scale network of the intelligent computing center due to the fact that existing network simulators lack scalability is solved, thereby improving the efficiency and accuracy of simulating a large-scale network of an intelligent computing center.

The invention relates to the technical field of fire safety and simulation training, and discloses a rule-driven fire-fighting real smoke and real fire training simulation system, which comprises a data acquisition and modeling module, a rule driving module, a rendering output module and a training evaluation module. The data acquisition and modeling module is used for acquiring initial fire data and constructing a reference model of smoke diffusion and fire spreading; the rule driving module simulates the non-synchronous evolution process of the fire through a particle simulation algorithm, a time coordination rule and a feedback loop algorithm; the rendering output module is used for integrating the environment rendering data and the multi-factor propulsion mode and generating a training effect evaluation index; and the evaluation optimization module judges whether the simulation precision of the reference model reaches a preset standard or not according to the training effect evaluation index until a simulation result meeting a precision requirement is obtained. According to the invention, the reality and accuracy of fire-fighting simulation training are improved.

The utility model discloses a deep vein puncture training simulation device, which comprises a puncture training platform, a dummy man device and a puncture training device, the dummy man device comprises a dummy man body and simulated deep veins distributed in the dummy man body, and each simulated deep vein is filled with simulated blood. The surface of the simulation human body is coated with a transparent observation layer through which all the simulation deep veins can be observed; a body position adjusting device is arranged on the puncture training table; the puncture training device comprises a puncture training needle and a puncture feedback device; teaching and training requirements of different body positions can be met by adjusting the body position of the simulated human body, all simulated deep veins can be observed through the transparent observation layer, and puncture results can be fed back in time when puncture training is conducted through cooperation of the puncture training needle and the puncture feedback device. When puncture fails, failure causes can be known through observation of the transparent observation layer, so that trainees can adjust and correct in time, and accuracy, training efficiency and quality of puncture operation are improved.

A training simulator for healthcare provider training may include one or more of the following: a first body component; a second body component; and a joint located at a junction of the first body component and the second body component, where the first body component is rotatable relative to the second body component at the joint. An actuator system for the training simulator may include a linear slider-crank mechanism and an actuator for controlling the linear slider-crank mechanism, where the linear slider-crank mechanism is configured to control a torque required to move the first body component relative to the second body component at the joint, and where control of the linear slider-crank mechanism with the actuator adjusts the torque.

The utility model discloses a training simulation ejection seat capable of providing constraint simulation. The training simulation ejection seat comprises arm constraint simulation assemblies arranged on the two sides of an ejection seat body. The arm constraint simulation assembly comprises a shell, a first cavity is formed in the shell, a first cam is rotationally connected into the first cavity of the shell, a sliding rod is vertically arranged in a second cavity in the shell in a sliding mode, the sliding rod is located below the first cam, the first cam can push the sliding rod to move downwards when rotating to a set position, and a second cam is arranged below the sliding rod. When the sliding rod moves downwards, the sliding rod can impact the side face of the other end of the second cam, the second cam drives the arm limiting device to rotate, and the upper end of the arm limiting device moves downwards to restrain the arms of trainees. The seat can meet the simulated ejection requirement under the new situation.

The invention belongs to the technical field of virtual training analysis, and particularly relates to an online virtual psychological training scoring system and a scoring method thereof. Comprising a training simulation module, a simulation evaluation module, a database module, a wide area network module, a management end and a student end. The training simulation module comprises a simulation server and a simulation output unit; the simulation evaluation module comprises an identity management unit, an index management unit and an evaluation unit; the database module is used for providing data support and processing service for each resource of the system and generated data; the wide area network module is used for establishing contact between equipment in the system and the management end and the student end; the management end is used for establishing an interface and a control mechanism related to system configuration management and system monitoring; and the student end is used for establishing a simulation training and student interaction operation mechanism. The virtual psychological training system is used for online virtual psychological training, meets the requirements of vocational skill training of related posts and the like, and enables learners to be familiar with and master basic knowledge, basic processes and practical operation skills of psychological training.

The invention provides an artificial intelligence confrontation technology military training simulation system based on reinforcement learning, and belongs to the field of training simulation. The problem of poor confrontation simulation training effect is solved; the scene simulation module is used for constructing a differential equation set and setting a response area of a target or a response interval of a laser module; the training simulation module is used for acquiring the positions of trainees, counting, recording and analyzing the shooting interval and the effective score of each trainee in combination with a differential equation set and the response area of the target or the response interval of the laser module, and adjusting a training strategy; the score feedback module is used for recording and feeding back effective scores of the trainees; the target refreshing interval and position are adjusted by analyzing the score and shooting angle of the trainee, and the target moving route is distributed according to the position of the trainee, so that the model effect of confrontation training is improved.

The utility model provides material filling equipment, which belongs to the technical field of material carrying and comprises a double-layer transmission module, two lifting platforms, a tray feeding module, a bottle body feeding module, an electric manipulator module, a filling feeding module, a robot clamp storage frame, an industrial robot unit, a visual inspection and identification module, a three-dimensional storage module and a basic examination assembly. The dynamic simulation operation can be realized through the industrial robot unit; according to the utility model, not only can practical training simulation of an automatic filling assembly line be carried out on students, but also dynamic operation simulation of the industrial robot unit can be realized through the basic assessment assembly, so that the skill intensity of the students after practical training simulation is improved.

The utility model discloses an aircraft attitude simulation training device, which belongs to the technical field of aircraft training simulation and comprises a base, a support frame is connected above the base, one side of the base is connected with a fixing cylinder, an anti-slip mat is connected below the other side of the base, and a through groove is arranged below the base. According to the aircraft attitude simulation training device, a first motor is started to rotate a threaded rod, a U-shaped frame is promoted to move along the threaded rod through a threaded sleeve, then a connecting rod is pushed to move, a fixing rod is promoted to slide along a guide groove, a connecting plate is made to rotate, universal wheels are promoted to stretch out of a through groove, and then a base is obliquely supported; and during fixing, the threaded rod only needs to be reversely rotated, the connecting plate and the universal wheel are promoted to move into the cavity from the through groove again, the non-slip mat and the supporting block are promoted to make contact with the ground, fixing and supporting are completed, and stability is improved.

The utility model provides a new energy automobile training simulation device, which belongs to the technical field of automobile teaching equipment and comprises a support and a high-voltage system which are fixed on a table top of a table body, and a teaching demonstration screen used for theory learning is fixed on the support. The high-voltage system comprises an operation platform for controlling start and stop, a battery box assembly for providing power, a charging assembly for simulating power supply charging, a driving assembly for simulating an automobile load and a DC / DC converter for simulating high-voltage direct current to be converted into low-voltage direct current, and the operation platform, the battery box assembly, the charging assembly, the driving assembly and the DC / DC converter are connected through wire harnesses. According to the new energy automobile training simulation equipment, the composition of a high-voltage system can be visually observed, the training operation of the high-voltage system can be carried out, the understanding and coping ability of trainees to real scenes is improved, meanwhile, the learning combining theory and practice can be carried out, and related knowledge and working principles can be more quickly mastered.

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.

The invention relates to the technical field of virtual scene design analysis. The system comprises a data accuracy and credibility evaluation module, an exercise standard analysis module, an exercise load analysis module, an exercise mode difficulty evaluation module and a scene training dynamic adjustment module. The data accuracy and credibility evaluation module evaluates the accuracy and credibility of data collected by the equipment; the exercise standard analysis module analyzes an exercise standard composite score according to the exercise data; the user exercise load analysis module analyzes the comprehensive exercise load of the user according to the physiological data; a motion mode difficulty evaluation module analyzes a difficulty value of scene training simulation of the current motion mode; and the scene training dynamic adjustment module dynamically adjusts scene parameters according to the difficulty level of training simulation. According to the method, the difficulty degree of current training simulation is analyzed according to the data generated in the equipment wearing process, scene parameters are dynamically adjusted, and the training effect and the user experience can be remarkably improved.

The utility model relates to the technical field of escape training, provide a self -rescue training simulation device, including experiment cabin and the dynamic arm system of symmetry in its both sides, dynamic arm system includes first dynamic arm connecting rod, second dynamic arm connecting rod, first rocker arm subassembly and second rocker arm subassembly, in first rocker arm subassembly, first dynamic arm connecting rod front end is hinged in first rocker arm one end through second mandrel, first rocker arm other end is connected with second fixed support through third mandrel, both junctions all are equipped with first joint bearing, the third mandrel outer symmetry is equipped with third state gasket, in second rocker arm subassembly, second dynamic arm connecting rod front end is connected with second rocker arm one end through fourth mandrel and is equipped with copper bush, second rocker arm other end is connected with third fixed support through fifth mandrel and is equipped with second joint bearing, the fifth mandrel outer symmetry is equipped with fourth state gasket. According to the utility model, can realize the flexible, stable motion simulation of multiple degrees of freedom, effectively promotes the training authenticity and security.

The invention discloses an urban underground space comprehensive digital management system which comprises a digital management system body, and the digital management system body comprises a project application scene platform, a construction content platform, a project technical architecture platform and a technical route platform. The project application scene platform is based on urban underground space comprehensive digital management construction requirements, and the project is fused with an urban underground space business application scene through IOT, AI, big data, cloud computing, digital twinning, XR, GIS and BIM information technologies; according to the invention, IOT, AI, big data, cloud computing, digital twinning, XR, GIS and BIM information technologies are fused with an urban underground space business application scene, a digital twinning basic environment is established, a facility operation and maintenance platform, AI safety management and control, XR practical training simulation and a digital cockpit module are researched, developed and applied, and a virtuality and reality combined urban underground space full-scene digital operation and maintenance management platform is built. And the personnel safety guarantee service of people is met.

The present application discloses a method and device for cognitive information training for soccer players. While a soccer player is watching a soccer training simulation video, the method obtains the player's eye movement index data and physiological characteristic data. Based on the player's eye movement index data and soccer training program information, actual training index data corresponding to different soccer training programs is established. The actual training index data is compared with preset reference index data to obtain comparison data. The physiological characteristic data is input into a preset SVM model to determine whether the player is in a state of attention and readiness. If the comparison data does not meet the preset training requirements and / or the player does not appear to be in a state of attention and readiness, the playback speed of the soccer training simulation video is adjusted to retrain the player. The above method enhances the training efficiency of soccer players.

This invention provides a landslide susceptibility assessment method based on categorical feature enhancement, belonging to the field of landslide prediction. The method includes: preprocessing multi-class data of the landslide disaster research area, deriving the original values ​​of evaluation factors corresponding to landslide points to obtain an original dataset; training a categorical feature enhancement algorithm and performing grid search to obtain a categorical feature enhancement algorithm with optimal parameters; using an adaptive enhancement model as a meta-learner, and using the categorical feature enhancement algorithm with optimal parameters as a base learner for adaptive enhancement ensemble modeling to obtain an ensemble model; substituting the training set into the ensemble model for training simulation, and importing grid points into the trained ensemble model for landslide susceptibility assessment, outputting a landslide susceptibility prediction map. This invention solves the problems of low adaptability of existing machine learning models to complex data and low accuracy in susceptibility assessment.

The application discloses a kind of micro-integrated control and multi-scenario training method oriented main distribution system, method includes: obtaining the training data of simulation training input parameter;Set the initial environment of simulation training, including according to the training role and teaching plan information, according to the training range, the loading of simulation initial section data of control operation is carried out;Different scene, scene instance and the running mode of sub-scene are established, multi-person joint training simulation or multi-person independent training simulation is carried out, and the training process is scored, and evaluation report is generated.The application provides simulation training scene management, starts the simulation environment of specified scene, provides fault and abnormal setting function for instructor, provides two training modes of joint training and independent training for student, automatically records important information of student operation, carries out evaluation, realizes the control operation simulation of micro-integrated main distribution and multi-scenario training of distribution network, improves the ability of staff to quickly analyze and handle fault, improves the ability of power supply recovery.

The invention provides a training method of a steward training simulation model and a steward training simulation method, relates to the technical field of steward training simulation, and aims to understand the current environment state of a steward so as to improve the authenticity of aviation steward training simulation. The method comprises the following steps: acquiring multi-modal data of a passenger cabin environment; based on the multi-modal data, training the steward training simulation model; the multi-modal word segmentation device is used for encoding the multi-modal data into a multi-modal token sequence; the potential action model is used for acquiring potential action representation of the steward or the passenger based on the multi-modal token sequence; the state analyzer is used for obtaining a passenger cabin semantic state diagram based on the multi-modal token sequence, and the passenger cabin semantic state diagram is used for representing a semantic relationship between entities in a passenger cabin; the dynamic model is used for predicting a multi-modal token at the next moment based on the multi-modal token sequence, the potential action representation and the passenger cabin semantic state diagram, and the multi-modal token at the next moment is at least used for simulating the passenger cabin environment at the next moment.

The invention discloses an intelligent LED screen practical training simulation and fault diagnosis system and method. The system comprises a practical training scene configuration module, an LED control simulation module, a fault generation and diagnosis module, a data acquisition and analysis module, an interaction and feedback module, a plurality of cooperative control modules and a safety monitoring module. Multiple splicing modes such as single lamp panel, regular splicing and special-shaped combination are achieved through the practical training scene configuration module, free combination configuration of the control module is achieved, the limitation of traditional practical training scene solidification is broken through, and practical training requirements of different levels and different types are met; based on a diagnosis mechanism of fault feature similarity calculation, various fault types and superposed faults can be accurately simulated, rapid identification and root positioning of the faults are realized, scientific fault checking training is provided for practical trainees, and the fault diagnosis capability is improved.

A computational system and method for digital modeling of cardiac cell membrane electrophysiology is disclosed. The system generates a digital model representing the cell membrane as a dielectric lipid bilayer comprising a capacitor element and a resistor element, where the resistor element is emulated by a plurality of ion channels. The system calculates cell membrane potential based on intracellular and extracellular concentrations of key ions, such as Na+, K+, Ca2+, and Cl-, using the Goldman-Hodgkin-Katz equation. Generation of cellular membrane action potentials is simulated by modeling the opening and closing of voltage-gated ion channels in response to triggering events. The model provides dynamic visualizations of the distinct phases of the action potential, including depolarization and repolarization, offering a high-fidelity tool for research and for enhancing the realism of training simulations in electrophysiology procedures.

The invention discloses a three-dimensional power grid training simulation method based on a virtual reality technology, and relates to the technical field of power grid training simulation, and the method comprises the following steps: initializing a virtual reality environment, loading a mountainous area power grid three-dimensional model, and generating a power transmission line node; setting training environment parameters; calculating an effective wind speed at each line node according to the terrain gradient; calculating the line galloping amplitude in real time; dynamically rendering a line galloping effect in a VR environment, and visually displaying a dangerous section through color coding; students can deploy anti-galloping devices interactively, and the system updates the damping effect in real time and recalculates the galloping amplitude. The system continuously monitors the safety state, provides a real-time alarm and generates a training evaluation report. According to the invention, a terrain-adaptive galloping amplitude real-time calculation algorithm is introduced, and a virtual reality training system deeply fused with a real geographical environment is constructed, so that simulation and visualization of the galloping behavior of the high-voltage transmission line in a mountainous complex terrain can be realized.

The utility model provides an electric service workshop ZPW2000R practical training simulation platform, which is characterized by comprising a ZPW2000R interval blocking cabinet, an interval passing signal machine, a pull-in signal machine and a practical training operation console which are sequentially connected in series through a circuit, a lighting circuit relay combination, a mutual control appointment relay combination, a node relay combination and a track relay combination are arranged in the pull-in signal machine, and the mutual control appointment relay combination is used for achieving the interlocking relation of mutual control appointment between relays in the lighting circuit relay combination and controlling the relays to be sucked up and fall down. The node relay combination is used for increasing the number of nodes in the pull-in annunciator, the track relay combination is used for restoring an outdoor lighting circuit of the pull-in annunciator, and a pull-in annunciator repeating lamp combination is further arranged in the pull-in annunciator and used for distinguishing the normal state of display equipment. According to the utility model, an intelligent system is adopted to carry out line breaking and line mixing on the ZPW2000R interval automatic block circuit and the pull-in signal machine circuit, so that the practical training drilling of the railway electric service field work area is convenient.

The invention belongs to the technical field of reinforcement learning. The invention provides a heterogeneous patrol flight cluster autonomous collaborative planning method based on memory reasoning. The method comprises the steps that a simulation environment is trained for agents of a heterogeneous patrol flight cluster, and a Markov decision process is constructed for each agent; constructing an intelligent agent dynamic model; initializing a simulation environment; data are acquired through environment interaction sampling, the double-memory module is updated, data of the long-term memory module are processed through the memory reasoning module, an excitation coefficient is generated in combination with a plot excitation mechanism, the excitation coefficient and data in the short-term memory module jointly calculate a target Q value and a current Q value, and a loss function is weighted to update an action value network. Calculating loss based on the strategy network and the entropy network, updating parameters of the strategy network and the entropy network, and periodically updating the memory reasoning module; and if the ending condition is met, stopping training, and outputting the trained multi-agent reinforcement learning model.

The invention discloses a self-adaptive first-aid training human body strength model which comprises a thoracic cavity body, a sensor module and a main control system, and relates to the technical field of emergency rescue skill training equipment. Through rigidity adjustment of the nickel-titanium memory alloy frame, pressing force requirements of students of different age groups are accurately met, the students can form correct pressing manipulation memory in training, the springs do not need to be manually replaced, the master control system automatically adjusts chest hardness according to student information, teaching efficiency is effectively improved, and the training efficiency is improved. And the hardness of the thoracic cavity body is adjusted by responding to the pressing force and posture changes in real time, so that the thoracic cavity hardness presents nonlinear mechanical characteristics similar to a real human body, the training simulation authenticity is effectively enhanced, and the method is closer to an actual first-aid scene.