Penin Andrei Semenovich (ITMO University, St. Petersburg)
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During the research work, the main biological markers of the human body were studied and those of them that met the requirements were selected for further research. A classifier of the employee's workload level was developed based on the decision tree method, the classification accuracy was 76%, the value of the loss function was 0.23. In the future, the classifier of the employee's workload level and biological markers will be combined into a model for assessing the state of the operator of a cyber-physical system.
Keywords:neural networks, multi-class classification, biomarkers, models, systems, state.
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Citation link: Penin A. S. Development of a load classifier for a model for assessing the state of a cyberphysical system operator // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2022. -№06. -С. 123-129 DOI 10.37882/2223-2966.2022.06.29 |
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