Abstract
In this work is proposed a new approach based on Evolving Fuzzy Neural Networks (EFuNNs) to on-line evaluation of training in virtual reality worlds. EFuNNs are dynamic connectionist feed forward networks with five layers of neurons and they are adaptive rule-based systems. Results of the technique application are provided and compared with another evaluation system based on a backpropagation trained multilayer perceptron neural network.
Keywords
- Evaluation System
- Virtual Reality
- Hide Markov Model
- Virtual Reality Simulator
- Virtual Reality System
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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de Moraes, R.M., dos Santos Machado, L. (2005). Evaluation System Based on EFuNN for On-Line Training Evaluation in Virtual Reality. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_81
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DOI: https://doi.org/10.1007/11578079_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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