New S-norm and T-norm Operators for Active Learning Method
  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.
