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Rough-Fuzzy Rule Interpolation for Data-Driven Decision Making

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Advances in Computational Intelligence Systems (UKCI 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1409))

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Abstract

Any practical decision making strategy is required to ensure that the best decision is made with respect to the information available and the knowledge possessed by experts. A rule-based fuzzy decision making system typically works on the fuzzy rules generated from numerical data acquired in the problem domain. However, different expert opinions on fuzzy partitions may result in a range of uncertainties in representing the domain knowledge. The invention of rough-fuzzy sets offers a great potential in the representation, handling and utilisation of different levels of uncertainty in knowledge. Inspired by this observation, a rough-fuzzy rule interpolation method is introduced in this paper to enable decision making systems modelling and harnessing additional uncertain information, in order to implement a fuzzy reasoning system that can work with incomplete rule base. An initial experimental investigation is carried out and the results are presented to demonstrate the effectiveness of the proposed method in aiding the development of an intelligent decision making system.

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Acknowledgment

This research was partly supported by the Science and Technology Research Program of Chongqing Municipal Education Commission (Grant No. KJQN202101513) and the Research Foundation of Chongqing University of Science and Technology (Grant No. CK2016B04).

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Authors and Affiliations

  1. School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China

    Chengyuan Chen

  2. Department of Computer Science, Faculty of Business and Physical Sciences, Aberystwyth University, Aberystwyth, SY23 3DB, UK

    Qiang Shen

Authors
  1. Chengyuan Chen
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  2. Qiang Shen
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Correspondence to Chengyuan Chen .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Aberystwyth University, Aberystwyth, UK

    Thomas Jansen

  2. Department of Computer Science, Aberystwyth University, Aberystwyth, UK

    Richard Jensen

  3. Department of Computer Science, Aberystwyth University, Aberystwyth, UK

    Neil Mac Parthaláin

  4. Department of Electrical Engineering, Yuan Ze University , Taoyuan, Taiwan

    Chih-Min Lin

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Chen, C., Shen, Q. (2022). Rough-Fuzzy Rule Interpolation for Data-Driven Decision Making. In: Jansen, T., Jensen, R., Mac Parthaláin, N., Lin, CM. (eds) Advances in Computational Intelligence Systems. UKCI 2021. Advances in Intelligent Systems and Computing, vol 1409. Springer, Cham. https://doi.org/10.1007/978-3-030-87094-2_3

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