Abstract
The concept of Intuitionistic Fuzzy Generalized Net (IFGN) is defined in [1] as an extension of the ordinary Generalized Net (GN) [2]. The aim of this paper is to describe how IFGN models can be trained until a specified level of correctness is reached. This process of training is represented also by means of IFGNs.
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References
Atanassov, K. Generalized Nets and System Theory, ‘Prof. M. Drinov“ Academic Publishing House, Sofia, 1997.
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Atanassov, K., H. Aladjov, A Generalized Net Describing Learning of a Generalized Net, Sixth Scientific Session Of “Mathematical Foundations of Artificial Intelligence” Seminar, Sofia, 1998.
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Aladjov, H. (2001). Intuitionistic Fuzzy Generalized Net Model Describing the Process of Training of Intuitionistic Fuzzy Generalized Net Models. In: Larsen, H.L., Andreasen, T., Christiansen, H., Kacprzyk, J., Zadrożny, S. (eds) Flexible Query Answering Systems. Advances in Soft Computing, vol 7. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1834-5_37
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DOI: https://doi.org/10.1007/978-3-7908-1834-5_37
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1347-0
Online ISBN: 978-3-7908-1834-5
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