A proposal of automatic generation of fuzzy neural network and its application to precise adjustment system
Ichiro Ishimaru, Tomoaki Sakata, H. Matuura · 2003
Recently the need for automation of higher proficiency adjustment is increasing. However, it has taken an enormous amount of time to make the adjustment algorithm and timely development of the automation equipment has not happened. The purpose of the paper is to reduce the term for the development of the adjustment algorithm. The paper presents a construction method for fuzzy neural networks. We propose a method to select the input parameters that can recognize vague waveforms. To operate the learning method easily, we propose an automatic learning rate set-up method and also propose a method to avoid the local minimum automatically. We also propose a virtual experiment system using fuzzy neural networks to evaluate the ability of the learned algorithm. We have developed a system which integrates the proposed construction method of fuzzy neural networks and the virtual experiment system.