Skip to main content

Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach

Razak, Tajul Rosli, Garibaldi, Jonathan M., Wagner, Christian, Pourabdollah, Amir, Soria, Daniele (2020) Towards a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach. IEEE Transactions on Fuzzy Systems, . ISSN 1063-6706. (doi:10.1109/TFUZZ.2020.2969901) (KAR id:80213)

PDF Publisher pdf
Language: English

Download (878kB) Preview
[thumbnail of 08972601.pdf]
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL


Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve the interpretability of fuzzy logic systems (FLSs). However, challenges remain, such as: "How can we measure their interpretability?", "How can we make an informed assessment of how HFSs should be designed to enhance interpretability?". The challenges of measuring the interpretability of HFSs include issues such as their topological structure, the number of layers, the meaning of intermediate variables, and so on. In this paper, an initial framework to measure the interpretability of HFSs is proposed, combined with a participatory user design process to create a specific instance of the framework for an application context. This approach enables the subjective views of a range of practitioners, experts in the design and creation of FLSs, to be taken into account in shaping the design of a generic framework for measuring interpretability in HFSs. This design process and framework are demonstrated through two classification application examples, showing the ability of the resulting index to appropriately capture interpretability as perceived by system design experts.

Item Type: Article
DOI/Identification number: 10.1109/TFUZZ.2020.2969901
Uncontrolled keywords: Fuzzy Logic Systems, Hierarchical Fuzzy Systems, Interpretability assessments, Participatory design
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Daniel Soria
Date Deposited: 24 Feb 2020 10:51 UTC
Last Modified: 16 Feb 2021 14:11 UTC
Resource URI: (The current URI for this page, for reference purposes)
Soria, Daniele:
  • Depositors only (login required):


Downloads per month over past year