Abstract
The tradeoff between accuracy and interpretability in fuzzy modeling has shifted into focus in last few years. This paper aims at improving accuracy of linguistic models while maintaining a good interpretability. A new gradient-based method, extended version of Jager approach, is proposed for the optimization of transparent Mamdani systems. The advantage of Mamdani systems if compared to 0th order TS systems in Jager approach is that their interpolation properties allow one to obtain less complex models without loss of accuracy. Several modeling examples confirming the advantages of the chosen algorithm are included.
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Riid, A., Rüstern, E. (2003). Gradient Descent Based Optimization of Transparent Mamdani Systems. In: Rutkowski, L., Kacprzyk, J. (eds) Neural Networks and Soft Computing. Advances in Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1902-1_83
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DOI: https://doi.org/10.1007/978-3-7908-1902-1_83
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-0005-0
Online ISBN: 978-3-7908-1902-1
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