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Fuzzy Bayes Rule for On-Line Training Assessment in Virtual Reality Simulators
Ronei Marcos de Moraes and Liliane dos Santos Machado

Simulators based on Virtual Reality (VR) provide significant benefits over other methods of training, mainly in critical procedures. The assessment of training performed in this kind of system is necessary to assess the training quality and provide some feedback about the user performance. Because VR simulators are real-time systems, on-line assessment tools attached to them must have a low complexity algorithm to not compromise the performance of the simulators. This work presents a new approach to online assessment using a tool based on Fuzzy Bayes Rule for modeling and classification of simulation in pre-defined classes of training. This method allows the use of continuous variables without loss of information. It also solves the problem of low complexity in on-line assessments without compromise performance of the simulator. Results of its application are provided and compared with another assessment system based on classical Bayes rule.

Keywords: On-line Training Assessment, Assessment based on Fuzzy Bayes Rule, Virtual Reality.

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