Optimizing the CRI method by improving the implication step in MISO fuzzy expert systems

Abstract

In conventional MISO fuzzy expert systems, the implication step requires the excessive operations and spatial complexity using compositional rule based inference (CRI). This paper proposes a novel method, sort compositional rule-based inference (SCRI) aimed at reducing both temporal and spatial complexity by changing the implication step. It shows the advanced SCRI in MISO fuzzy systems. We also propose a divide-and-conquer technique, called Quicksort, to verify the accuracy of SCRI deployment to easily outperform the CRI method.