| Summary: | Hierarchical fuzzy systems (HFSs) are claimed to be an excellent approach to reducing the number of rules in Fuzzy logic systems (FLSs). Further, HFSs have also been shown to have the potential to reduce complexity and improve interpretability for FLSs. However, designing an interpretable HFS is a challenging task. This is due to the HFSs' structures, which have multiple subsystems, layers and topologies. This paper put forward an approach to present a design guidelines framework to build interpretable HFSs. The framework consists of five key guidelines for interpretable HFSs. It is demonstrated using a real-world example to design interpretable HFS for the Iris classification problem. This study contributes to providing insight into a pathway for designing interpretable HFSs, as can be used in practice.
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