Active Learning Method (ALM) is a soft computing method used for modeling and control based on fuzzy logic. All operators defined for fuzzy sets must serve as either fuzzy S-norm or fuzzy T-norm. Despite being a powerful modeling method, ALM does not possess operators which serve as S-norms and T-norms which deprive it of a profound analytical expression/form. This paper introduces two new operators based on morphology which satisfy the following conditions: First, they serve as fuzzy S-norm and T-norm. Second, they satisfy Demorgans law, so they complement each other perfectly. These operators are investigated via three viewpoints: Mathematics, Geometry and fuzzy logic.
@article{arxiv.1010.4561,
title = {New S-norm and T-norm Operators for Active Learning Method},
author = {Ali Akbar Kiaei and Saeed Bagheri Shouraki and Seyed Hossein Khasteh and Mahmoud Khademi and Ali Reza Ghatreh Samani},
journal= {arXiv preprint arXiv:1010.4561},
year = {2011}
}
Comments
11 pages, 20 figures, under review of SPRINGER (Fuzzy Optimization and Decision Making)