Reductive property of new fuzzy reasoning method based on distance measure
This work addresses incremental improvements in fuzzy logic for applications requiring human-like reasoning, such as AI decision-making systems.
The paper tackles the problem of evaluating and improving fuzzy reasoning methods by proposing a new criterion function and a distance-based method, showing through experiments that the proposed method outperforms previous methods in aligning with human thinking.
Firstly in this paper we propose a new criterion function for evaluation of the reductive property about the fuzzy reasoning result for fuzzy modus ponens and fuzzy modus tollens. Secondly unlike fuzzy reasoning methods based on the similarity measure, we propose a new fuzzy reasoning method based on distance measure. Thirdly the reductive property for 5 fuzzy reasoning methods are checked with respect to fuzzy modus ponens and fuzzy modus tollens. Through the experiment, we show that proposed method is better than the previous methods in accordance with human thinking.