Active Learning Method (ALM) is a soft computing method which is used for modeling and control, based on fuzzy logic. Although ALM has shown that it acts well in dynamic environments, its operators cannot support it very well in complex situations due to losing data. Thus ALM can find better membership functions if more appropriate operators be chosen for it. This paper substituted two new operators instead of ALM original ones; which consequently renewed finding membership functions in a way superior to conventional ALM. This new method is called Extended Active Learning Method (EALM).
@article{arxiv.1011.2512,
title = {Extended Active Learning Method},
author = {Ali Akbar Kiaei and Saeed Bagheri Shouraki and Seyed Hossein Khasteh and Mahmoud Khademi and Alireza Ghatreh Samani},
journal= {arXiv preprint arXiv:1011.2512},
year = {2019}
}
Comments
18 pages, 26 figures, 2 tables, submitted to the control engineering practice of Elsevier