Gradient Descent Based Optimization of Transparent Mamdani Systems
Andri Riid, Ennu Rüstern · 2003
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 0 th 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. 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.