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- W2079934507 abstract "Abstract In this paper, authors propose an overview of feedforward-feedback learning control systems that can be adapted for human errors prediction. A State of the Art in existing approaches for machines of feedback and/or feedforward learning control systems is presented and a synthesis relevant for prediction purposes is detailed. The possible application for learning systems based on human errors applied to Human Machine System (HMS) is then identified. A feedforward-feedback learning system applied to car driving simulation in order to predict intentional human errors is proposed. The paper concludes on relevant perspectives for feedforward-feedback learning systems to predict human errors and to increase HMS resilience facing unplanned disruptions in transportation." @default.
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- W2079934507 date "2011-01-01" @default.
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- W2079934507 title "A State of the Art in Feedforward-Feedback Learning Control Systems for Human Errors Prediction" @default.
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- W2079934507 doi "https://doi.org/10.3182/20110828-6-it-1002.03483" @default.
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