Mamdani-type inference

Mamdani-type inference is a method used in fuzzy logic systems to make decisions based on imprecise or ambiguous information. It works by applying a set of rules, where inputs are evaluated with fuzzy sets (which assign degrees of belonging to categories). These rules produce fuzzy outputs, which are then combined and processed through a method called 'defuzzification' to produce a single, clear result. This approach allows systems to handle real-world uncertainty effectively, making decisions that are more flexible and human-like, especially in complex, uncertain environments.