Fuzzy modelling using a new compact fuzzy system: A special application to the prediction of the mechanical properties of alloy steels

Zhang, Qian, Mahfouf, Mahdi (2011) Fuzzy modelling using a new compact fuzzy system: A special application to the prediction of the mechanical properties of alloy steels. In: Fuzzy Systems (FUZZ), 2011 IEEE International Conference on. . pp. 1041-1048. IEEE ISBN 978-1-4244-7315-1. E-ISBN 978-1-4244-7316-8. (doi:10.1109/FUZZY.2011.6007730) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://doi.org/10.1109/FUZZY.2011.6007730

Abstract

In high-dimensional modelling cases, a fuzzy modelling approach based on the grid-partitioning of fuzzy sets always meets great challenges, as it cannot avoid the problem of introducing a huge number of fuzzy rules. To tackle this issue, a new grid-partitioning based fuzzy modelling paradigm is proposed in this paper to construct a compact fuzzy system by including 'short fuzzy rules', in which only a few but strategic premises are used. In the proposed approach, the generation of fuzzy rules is data-orientated, a consideration which can greatly reduce the computational complexity. A new framework for fuzzy reasoning and defuzzification is also devised, which employs some archived reference data to help choose the most suitable fuzzy rules. In material engineering, describing the behaviour of mechanical properties of alloys is often a high dimensional modelling problem, which involves the complexity of materials' chemical composites and their underlying physical processing mechanisms. In this paper, the proposed approach was successfully applied to generate models of ultimate tensile strength of alloy steel. Compared with the standard grid partitioning based fuzzy modelling paradigms, the new method shows an improvement in both complexity and interpretability. Compared with the clustering-based fuzzy modelling approaches, the proposed method can achieve the same accuracy level and is more transparent.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/FUZZY.2011.6007730
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering, cybernetics and intelligent systems
T Technology > TA Engineering (General). Civil engineering (General) > TA 403 Materials Science
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Qian Zhang
Date Deposited: 18 Sep 2015 15:30 UTC
Last Modified: 29 May 2019 16:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/50541 (The current URI for this page, for reference purposes)
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