384 results about "Skills training" patented technology

The invention discloses a low-voltage transformer area examination meter practical training device and a fault simulation control method, and relates to the technical field of electric power practical training. The device aims at the problems of single scene, extensive evaluation and low skill improvement efficiency in traditional electric power practical training. The meter simulation module is compatible with various meters and is matched with a dual-communication protocol to realize efficient data transmission; the intelligent interaction module provides high-quality interaction experience through a high-definition touch screen and low-delay transmission; the data generation module can quickly switch customized scenes, and the fault simulation module can accurately inject various faults; the training management module depends on advanced technologies of knowledge maps, deep learning and fuzzy comprehensive evaluation to realize full-process closed-loop management from project design and operation guidance to evaluation feedback and intelligent optimization; all the modules cooperate efficiently, and the professionality, the accuracy and the efficiency of power failure troubleshooting and operation and maintenance skill training of trainees are remarkably improved.

The invention relates to the technical field of online network teaching, and discloses an online network teaching practice method based on a virtual technology, and the method comprises the steps: obtaining virtual scene data, and carrying out the integration and building of a dynamic knowledge graph and a multi-modal teaching resource library; learning behavior features are extracted according to the cognitive features of the learner, knowledge difficulty levels are divided, and immersive learning is guided; constructing a cognitive evaluation model, optimizing a learning path through hierarchical reinforcement learning, and generating a self-adaptive teaching instruction; collecting interaction track data to generate an operation thermodynamic diagram, and evaluating the skill mastering degree; complexity parameters of the virtual scene are dynamically adjusted, a virtual-real linkage experiment simulation environment is constructed, and skill training closed-loop feedback is achieved. The invention further relates to specific implementation modes of resource integration, cognitive feature extraction, learning path optimization and the like. According to the method, the personalized and immersive experience and skill training effect of online teaching are improved, and the method is suitable for the field of online network teaching.

The invention provides a cardio-pulmonary resuscitation training system based on multi-modal artificial intelligence in combination with a virtual reality technology, and relates to the technical field of virtual reality, and the system comprises a multi-modal sensing module which is used for collecting posture data, mechanical data and environment data; the multi-source data collaboration module is used for generating an operation quality evaluation parameter set and establishing a mapping relation between the operation posture and the pressing efficiency; the virtual scene construction module is used for generating a virtual first-aid environment according to a preset first-aid scene template and the operation quality evaluation parameter set; the decision module is used for generating a feedback control signal; and the interactive closed-loop execution module is used for inputting the feedback control signal into the virtual first-aid environment and updating the operation quality evaluation parameter set according to the operation data after feedback response. According to the invention, standardized, intelligent and scene-diversified cardiopulmonary resuscitation skill training can be realized, and the technical problems of inaccurate posture evaluation, non-personalized feedback, single scene, high resource dependence and the like in traditional training are solved.

The invention discloses a driving skill training method constructed based on a diversified virtual examination room, and relates to the technical field of data processing, and the method comprises the steps: constructing a system based on the diversified virtual examination room, constructing a virtual examination room scene to carry out the driving training of a training user, outputting a driving behavior data set in real time, and carrying out the scoring, and analyzing the data according to the driving score, generating a personalized training path in combination with historical data when the driving score does not reach the standard, and training the user to carry out training step by step according to the training path until a preset skill scoring target is achieved. The technical problems that in the prior art, a traditional driving training method cannot dynamically adjust a training path to meet the actual skill requirements of trainees, consequently, training content lacks pertinence and is low in efficiency are solved, the individuation and pertinence of driving skill training are improved, it is ensured that the training content is highly matched with the actual skill requirements of the trainees, and the driving skill training efficiency is improved. And the training efficiency and effect are improved.

The invention, which relates to the technical field of artificial intelligence and skill training examination, discloses a multi-crowd adaptive training evaluation system comprising the following components: a user data management module, an RAG module, an answer processing module, a score analysis module, an intensive training module and a question bank updating module. According to the method, comprehensive and accurate assessment of the user ability is realized by constructing a multi-crowd adaptive training assessment system, the system constructs the user ability portrait by collecting historical data and real-time performance of the user in multiple dimensions and utilizing advanced data processing and analysis technologies, and dynamically adjusts the training content and difficulty, so that the user ability assessment efficiency is improved. According to the method and the system, the ability level and the learning requirement of different users are adapted, the personalized training mode not only improves the participation degree and the learning efficiency of the users, but also helps the users to quickly and accurately identify the ability weakness of the users, and powerful support is provided for subsequent improvement.

The invention provides a CT guided liver puncture training method and system based on virtual reality, and relates to the technical field of virtual reality. A deformable liver model and a virtual CT reconstruction engine under respiration driving are constructed, needle body posture mapping and image fusion display are achieved by fusing an inertia-electromagnetic dual-mode sensor, path interaction control, tissue dynamic response and score feedback are supported, the scene difficulty is automatically adjusted based on a training result, and the accuracy and the reliability of the system are improved. Progressive puncture skill training of static breath-holding, shallow breath and free breath scenes is achieved, the sense of reality of training, operation feedback and teaching efficiency are improved, and the system is suitable for development and clinical teaching application of an interventional therapy training system under the guidance of medical images.

The invention relates to the technical field of intelligent teaching, in particular to an intelligent teaching system for traditional Chinese medicine clinical skill cultivation. The system comprises a virtual reality simulation module, an operation interaction module, an operation data analysis module, an adaptive learning feedback module and a teaching evaluation module. The virtual reality simulation module constructs a vivid traditional Chinese medicine skill training scene through three-dimensional modeling, ray tracing and physical simulation technologies, and the vivid traditional Chinese medicine skill training scene covers pulse feeling, acupuncture and moxibustion, massage and other operations. The operation interaction module collects user operation data and extracts features in combination with a variational auto-encoder. The operation data analysis module analyzes user operation deviation by using a graph neural network and a generative adversarial network, the adaptive learning feedback module generates a personalized learning strategy, and the teaching evaluation module evaluates a learning effect through fuzzy evaluation and analytic hierarchy process. According to the invention, intelligence, individuation and high efficiency of traditional Chinese medicine clinical skill cultivation are realized, the fidelity of teaching and the accuracy of feedback are improved, and the skill level and the training effect of learners are also improved.

The invention discloses a pump station maintenance-oriented dismounting path practical training method and system, and relates to the technical field of pump station dismounting. The method comprises the following steps: constructing a virtual-real simulation environment of pump station equipment, carrying out dynamic dismounting monitoring identification on pump station parts in the pump station equipment based on the virtual-real simulation environment, and determining a dismounting path; the method comprises the following steps: acquiring operation track data of a training person in real time through a motion capture device, obtaining a somatosensory interaction motion signal, mapping the somatosensory interaction motion signal to a virtual-real simulation environment for disassembly and assembly analysis, and generating a disassembly and assembly motion deviation parameter set; and performing dynamic optimization based on the disassembly and assembly action deviation parameter set in combination with disassembly and assembly multi-dimensional feedback data, generating multi-stage practical training difficulty, performing adaptation on practical training personnel according to a disassembly and assembly path according to the multi-stage practical training difficulty, and determining a multi-stage practical training scheme. The technical problems that in the prior art, pump station maintenance dismounting practical training lacks real scene simulation, and efficient skill training is difficult to achieve are solved, and the technical effect of improving the practical training effect is achieved.

The invention discloses a disaster emergency rescue nursing skill training system based on virtual reality, and relates to the technical field of virtual reality. A high-simulation virtual disaster scene is constructed based on real data, diversified injury condition virtual objects matched with the scene are generated, a secondary disaster risk diffusion effect and emergency prompt information are overlaid in real time, physiological state changes such as blood pressure and respiration generated by nursing operation differences in the rescue process of wounded personnel are dynamically simulated, and the rescue effect of the wounded personnel is improved. The problems of single scene and fixed injury condition in traditional training are solved, real-time and multi-modal feedback of student operation is realized through accurate comparison and hierarchical identification of multi-dimensional operation characteristics, the defects of guidance lagging and general are overcome, a personalized and adaptive training scheme is generated according to a comprehensive evaluation result, the progress is dynamically adjusted, and the training efficiency is improved. And scene simulation, operation practice, accurate feedback and personalized improvement are integrated.

The invention discloses a conversation method and device for verbal skill training, computer equipment and a storage medium, which are applied to an engine end, the engine end, a user end and a large language model end form a verbal skill training system, and the engine end performs data interaction with the user end and the large language model end. The user side and the large language model side do not perform data interaction, and data of the large language model side is independent of the engine side. Sending a target question in the target question and answer set to the large language model end to generate a first question statement, receiving a first answer statement returned by the user end based on the first question statement, and sending the first answer statement and a standard answer to the large language model end together, and judging whether the semantics of the first answer statement and the standard answer are consistent or not by the large language model end, sending a next question to the large language model end to generate a next question statement when the semantics of the first answer statement and the standard answer are consistent, and sending feedback information to the large language model end to generate a feedback statement to prompt the user to answer again when the semantics of the first answer statement and the standard answer are inconsistent.

The invention provides an intelligent driving skill training method and system based on behavior cloning and reinforcement learning, and relates to the technical field, and the method comprises the steps: collecting the driving behavior data of a human driver, dividing a training set and a verification set to train a behavior cloning model, and obtaining an initial driving model; and determining to-be-optimized driving skill indexes such as safety, efficiency and comfort according to the performance of the initial model, and constructing diversified training scenes in the virtual training environment. And performing reinforcement learning training on the initial model through a deep reinforcement learning algorithm by using a reward function containing the indexes to obtain an optimized driving model. The optimized model is tested in the test scene set, and when the safety index, the efficiency index and the comfort index all reach preset threshold values, training is completed. By combining behavior cloning and reinforcement learning, the comprehensive performance of the intelligent driving model in the aspects of safety, efficiency, comfort and the like can be effectively improved.

The invention belongs to the field of medical technology and information technology, and discloses an AR-guided infusion port puncture navigation system, which collects and marks historical data of a large number of puncture operations, and uses a deep learning algorithm to train a model so as to identify a correct operation mode. The visual angle, motion trail, gesture change, force and space coordinate data of an operator are captured in real time, rapidly analyzed and input into a model for real-time judgment, a multi-sensory feedback mechanism is integrated on an AR interface, visual, auditory and tactile feedback is provided in real time according to a model judgment result, the operator is guided to adjust actions, and the real-time performance of the operator is improved. The feedback data in the operation process are continuously collected, the feedback effect is regularly evaluated, the model is iteratively optimized, and a continuously improved closed loop mechanism is formed, so that the accuracy and efficiency of medical operation are improved, the medical risk is reduced, the method can be widely applied to clinical teaching, skill training and actual operation, and the medical service quality is remarkably improved.

The invention relates to the technical field of hydrological survey skill training, in particular to a construction method and system of a hydrological survey knowledge model based on a large model. The method comprises the following steps: acquiring multi-source hydrological data, and constructing a hydrological knowledge graph; generating a confusion sample corresponding to the hydrological knowledge graph, and performing adversarial training on the confusion sample; according to the confrontation training result and historical test questions in the multi-source hydrological data, obtaining bidirectional mapping test questions; inputting the bidirectional mapping test questions into a question setting interface of a hydrological survey learning platform; collecting answer data and student physiological data corresponding to the bidirectional mapping test questions in real time, and updating a student knowledge state according to the answer data and the student physiological data; constructing a hydrological survey knowledge model based on the updated student knowledge state; and generating a student recommendation learning scheme by using the hydrological survey knowledge model. According to the invention, the intellectualization and practicability of hydrological survey education can be improved.

The invention provides an anesthesia virtual simulation training system fusing knowledge, skills and a thinking closed loop. The anesthesia virtual simulation training system comprises a medical knowledge base module, a clinical thinking module, a skill training module, an examination question brushing module, a knowledge graph module and an intelligent platform bottom layer framework. The intelligent platform underlying architecture comprises a data middle platform, an AI engine and a 3D engine, collects student behavior data of each module, constructs a dynamic student ability portrait through a gradient boosting tree algorithm and a collaborative filtering recommendation model, analyzes knowledge blind areas and skill shortages, plans a personalized learning path and pushes targeted training content, and provides a personalized learning result. A closed-loop process of evaluation, learning, practice and re-evaluation is formed; and deep fusion of theoretical knowledge, clinical thinking and skill operation is realized through a cross-module collaboration mechanism. The problems that traditional anesthesia teaching is high in practical operation risk, scattered in resource and insufficient in individuation are solved, and the clinical comprehensive ability and teaching quality of anesthetists are effectively improved.

The invention discloses an SDH communication equipment fault maintenance simulation teaching method based on digital twinning. The method comprises the following steps of S1, equipment simulation, S2, fault scene definition, S3, fault injection, S4, fault simulation, S5, fault diagnosis, S6, fault repair and S7, evaluation and feedback. The system has the advantages that a real SDH equipment fault scene can be simulated, fault checking and repairing training close to actual combat can be provided for students, excessive consumption and high purchase cost of entity equipment are avoided, virtual simulation of an SDH communication equipment fault mode is realized by constructing a high-precision SDH communication equipment digital twinborn body, and the simulation efficiency of the SDH communication equipment fault mode is improved. And fault processing training close to a real environment is provided for students. The invention provides an efficient, economic and safe SDH communication equipment fault maintenance skill training method so as to improve the practical ability and the troubleshooting efficiency of trainees.

The invention relates to the technical field of intelligent education, in particular to an AI-based nursing teaching scene construction and evaluation system. According to the system, a dynamic case script is generated through historical case data, and a virtual patient physiological model is constructed; creating three teaching scenes of community follow-up visit, emergency rescue and traditional Chinese medicine nursing fusion by using a mixed reality technology; a personalized learning portrait of the student is constructed through a pre-test, and accurate matching between the ability of the student and the teaching content is formed; a double-track system skill training module is built, and AI tutor guidance and teacher guidance are integrated; and an ability evaluation system based on operation data is established, and intelligent pushing of adaptive training content is realized. The problems that in traditional nursing teaching, scene authenticity is insufficient, personalized training is insufficient, and clinical thinking is difficult to cultivate are solved, and the clinical operation skill and decision judgment ability of students are improved.

The invention discloses a nursing medicine education system based on the Internet, and relates to the field of computer application technology and education management, and the system comprises a theory learning module which is used for achieving the online teaching and personalized learning pushing of nursing theory knowledge, the nursing skill training module is used for training and evaluating the standardized nursing operation ability of students, the virtual simulation practical training module is used for providing an immersive virtual clinical training environment, and the structured nursing document training module is used for improving the ability of the students to write standard nursing documents. The intelligent evaluation module is used for carrying out automatic, multi-dimensional and structured comprehensive evaluation on the learning and training process of students, and the system integration interface module is used for realizing data exchange and interaction between the teaching platform and an existing information system of a hospital. The system has the advantages of complete functions, closed-loop data and accurate intelligent evaluation, and can effectively improve the standardization, practicability and intelligent level of nursing education.

The invention relates to the technical field of artificial intelligence, in particular to a personalized soft skill training method and system based on artificial intelligence. The method comprises the following steps of performing evaluation by using a multi-dimensional questionnaire, and analyzing semantics of user answers in combination with a large language model to generate an initial user portrait; updating the initial user portrait; constructing a skill tree by using a word embedding technology and an improved Woltzz method; constructing and optimizing a global model based on the skill tree; and dynamically generating a personalized learning path according to the global model. By introducing an artificial intelligence large language model technology, a neural network word embedding algorithm and a graph theory algorithm and combining a'questionnaire-learning-practice 'closed-loop training mode, individuation, systematization and intelligentization of soft skill training are realized, the technical bottleneck of a traditional method in the aspect of subjective question type intelligent feedback is broken through, and the intelligent feedback of the subjective question type is realized. And the soft skill training effect and the user experience are obviously improved.

The invention discloses a complete-cycle information interaction system for a breast reconstruction patient, and relates to the technical field of information interaction of the breast reconstruction patient, and the system comprises the steps: collecting patient information and expert literature information, and carrying out the preprocessing of the collected information; creating a breast reconstruction patient rehabilitation exercise virtual simulation model for visual display, and synchronizing patient information in real time; calculating a patient rehabilitation coefficient, and evaluating a patient rehabilitation state; the patient and family members are assisted in virtual patient nursing learning; and encrypting the patient information, and storing the patient information. The rehabilitation state of the patient is evaluated, nursing skill training is performed on the patient and family members, the rehabilitation state of the patient is monitored in real time, the nursing risk prevention consciousness and the coping capacity of the patient and the family members are improved, nursing risks caused by misoperation and improper coping are reduced, problems occurring in the rehabilitation process are found in time, the treatment strategy is adjusted, and the rehabilitation effect of the patient is improved. A medical team is helped to formulate a personalized rehabilitation plan according to the unique condition of each patient, and long-term health and stability of the patients are maintained.

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 discloses a medical operation AR practical training system based on mixed reality and reinforcement learning and a training method thereof, and relates to the technical field of medical education and medical operation training. The system comprises an MR terminal presentation and interaction module, a case and scene management module, a multi-mode operation data acquisition and evaluation module, a reinforcement learning training strategy engine module, a practical training process control module, a training examination management module and the like, a vivid medical scene is constructed in an MR environment, and data such as operation tracks, force and step time sequences of students are acquired in real time; the evaluation result is coded into a state to be input into the reinforcement learning model, the case difficulty, the prompting mode and the training rhythm are adjusted in a self-adaptive mode, individualized, procedural and quantifiable skill training and assessment are achieved, and the method is suitable for various operations such as cardio-pulmonary resuscitation, endoscopic surgery and puncture catheterization.

The invention relates to the technical field of flight training, and particularly discloses an intelligent auxiliary training method and system for the driving skill of a helicopter pilot, and the method comprises the steps: deploying a plurality of sensors in a simulated helicopter cockpit for collecting operation, physiology, eye movement and other original data; after data standardization preprocessing, constructing a trainee training state comprehensive data model by using a multi-modal data fusion algorithm; dynamically generating a simulated flight scene by using VR and AR; carrying out comprehensive evaluation by adopting a multi-modal evaluation model based on deep learning in combination with multi-source data and student scene performance, and generating a multi-dimensional report; an evaluation result is fed back in real time through multiple channels such as voice and touch, and customized training resources are pushed; and formulating an exclusive training plan by using a personalized learning path planning algorithm based on multiple training data. Through multi-source data fusion and an intelligent algorithm, the training state of the trainee is comprehensively and accurately evaluated, a personalized training scheme is provided, and the driving skill training efficiency and quality of the helicopter pilot are effectively improved.

The invention discloses a personalized teaching skill training system based on a large language model, equipment, a medium and a product, and relates to the technical field of teaching skill training.In the system, firstly, a teaching skill learning module provides answers meeting teaching requirements for teaching questions proposed by teachers so as to help the teachers to learn teaching skills; secondly, a plurality of virtual student roles and live-action teaching scenes are generated through a live-action teaching simulation module, and the virtual student roles and the live-action teaching scenes are simulated by teachers in an online video mode, so that the actual teaching ability is trained and improved; the teaching feedback analysis module analyzes the teaching behavior performance data and the teacher-student interaction data, generates a report and provides suggestions for defects; and finally, proper teaching skill training resources are recommended through a teaching resource recommendation module, so that the teacher is helped to deeply learn and improve the teaching method. According to the scheme of the invention, the teaching ability of teachers can be effectively improved, and especially the coping ability of the teachers facing diversified student behaviors and demands can be effectively improved.

The invention provides a resource configuration and optimal scheduling method for supervision resources, and the method comprises the steps: building a cable laying three-dimensional visual model, enabling the attributes of supervision personnel to be matched with a supervision region, generating an initial configuration scheme, and carrying out the correlation analysis of a historical electrical engineering quality problem and the attributes of the supervision personnel, thereby achieving the optimal scheduling of the supervision resources. And dynamic adjustment of supervision personnel configuration is realized. And the construction process is monitored in real time by using the Internet of Things technology, and early warning and positioning are carried out on abnormal conditions. Quality of key processes is judged through image analysis, and professional supervisors are matched for disposal according to severity of problems. And skill training is carried out in combination with a virtual reality technology, and a personnel scheduling strategy is optimized. And through big data analysis, continuous evaluation and dynamic adjustment of supervision personnel configuration are carried out to form closed-loop optimization. According to the method, the supervisor and the supervision area are highly matched, the supervisor can quickly and efficiently complete the supervision work, the construction efficiency of the cable laying project is effectively improved, and the quality of the cable laying project is improved.

The invention discloses a person training scheme evaluation method and device based on a virtual reality environment, a storage medium and electronic equipment, and the method comprises the steps: obtaining the brain data, physiological data and behavior data of a to-be-evaluated person in a training process based on a training scheme; performing feature fusion on the brain data, the physiological data and the behavior data to obtain fusion features of the to-be-evaluated person; obtaining a plurality of state features of the to-be-evaluated person based on the fusion features; and determining an evaluation result of the training scheme according to the scores of the plurality of state features. According to the evaluation method, the training effect can be comprehensively and accurately evaluated, the monitoring accuracy and robustness are improved, and powerful support is provided for skill training and task preparation of the to-be-evaluated personnel.

The invention discloses an electric power skill training and scoring evaluation method based on a large model algorithm, and belongs to the technical field of electric power skill training and scoring evaluation, and the method comprises the steps: collecting and processing student information data and historical operation behavior data, and integrating the processed data into a unified data warehouse for storage; analyzing the information data and the power skill post demand of each student by using a natural language processing technology to generate a demand analysis result; generating a training content scheme according to the demand analysis result based on a pre-selected large model; by analyzing learning behavior data, constructing a student learning style model, and further optimizing a training content scheme to obtain an optimal training scheme; a three-dimensional electric power working scene model is constructed by using computer graphics and VR / AR technologies; through establishing an operation evaluation model, real-time scoring evaluation is carried out on electric power skill operation of students, and an evaluation result of each student is obtained.

The invention relates to the technical field of medical care, in particular to a lung cancer chemotherapy patient resilience intervention system and application thereof. According to the intervention system based on the PERMA mode, intervention is implemented in stages through comprehensive measures such as acute symptom management, psychological construction strengthening, chemotherapy adverse reaction cognition, home nursing skill training, physical recovery training, social support linkage and treatment compliance improvement. The method comprises the following steps: quantifying pain by using digital scoring equipment, and assisting pressing to relieve symptoms by using acupoint diagrams; the psychological toughness is enhanced through the positive voice listening and the anti-cancer brave diary recording; an online and offline combined mode is adopted, group lectures, scene simulation video teaching and online community interaction are carried out, and social support of patients is enhanced; personalized exercise prescriptions and home safety lists are formulated, and treatment compliance is improved. The system can significantly improve the recovery of a patient, improve the life quality during chemotherapy, and provide a scientific basis for innovation of a tumor nursing mode.

The invention relates to an AI intelligent management platform for maintenance of ship safety lifesaving emergency equipment. The AI intelligent management platform comprises a front-end function system and a rear-end storage system. The front-end function system comprises a sailor training module, an intelligent inspection module, a third-party maintenance supervision module and the like. Wherein the sailor training module adopts a panoramic VR camera to carry out live-action shooting on a scene on a ship, a virtual reality (VR) technology is applied to provide real scene boarding experience, sailors are helped to remotely realize immersive ship visiting, and a real ship environment is comprehensively understood; through the combination of videos and characters, skill training of sailors before on-ship work is provided. The sailors can remotely realize immersive ship visiting through the sailors training module, comprehensively understand the actual ship environment and remarkably improve the practical operation skills of the sailors; the personalized training path system customizes an exclusive training plan for each sailor through AI algorithm intelligent analysis according to the post demand, experience level and skill weakness of the sailor, and achieves the precision and high efficiency of training.

The invention discloses a quantitative evaluation method for a high-altitude air route emergency handling effect. The method comprises the following steps: dividing emergency types; establishing an evaluation index system for handling different types of emergencies; setting a secondary evaluation index calculation method and an evaluation standard; objective operation data of each secondary evaluation index is extracted and calculated; calculating the specific numerical value of each secondary evaluation index; and obtaining a quantitative score of the emergency command level of the controller in the high-altitude route emergency. The method solves the problem that the ability and effect of the controller to deal with unconventional emergencies of a high-altitude air route cannot be accurately and quantitatively described in the existing air traffic control command work, and provides support for scientifically evaluating the skills of the controller and guaranteeing the safe operation of an air traffic control system. An air traffic control unit can use the method to comprehensively evaluate the emergency command capability of the controller, and can apply the method to annual retraining or skill fighting of the controller, so that special skill training and targeted review training can be conveniently organized to improve the training effect and quality.

The invention relates to the technical field of medical education, and discloses a virtual simulation method for an interactive anesthesia crisis skill training scene, and the method comprises the following steps: constructing a high-fidelity operating room and a crisis processing scene in a virtual environment; physiological parameter changes of the patient are simulated in real time and fed back to the student interface; recording and analyzing operation steps, decision-making time and physiological feedback of the trainee in training; and the learning path of the trainee is dynamically adjusted through a multi-objective optimization algorithm, so that the training effect is enhanced. According to the invention, through a personalized learning path and a real-time feedback mechanism, the effectiveness of anesthesia crisis skill training is improved. Students practice in a vivid virtual environment, and the clinical decision-making ability and the operation accuracy are enhanced. Meanwhile, the system is continuously updated to ensure that the training content is consistent with the latest medical practice, high-quality medical professionals are cultivated, and the medical service quality is comprehensively improved.