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Model fusion using fuzzy aggregation: Special applications to metal properties

Zhang, Qian, Mahfouf, Mahdi, Yates, John R., Pinna, Christophe (2012) Model fusion using fuzzy aggregation: Special applications to metal properties. Applied Soft Computing, 12 (6). pp. 1678-1692. ISSN 1568-4946. (doi:10.1016/j.asoc.2012.01.021) (KAR id:50509)

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To improve the modelling performance, one should either propose a new modelling methodology or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free modelling paradigm is proposed. It does not rely on a fixed structure and can combine various modelling techniques in ‘symbiosis’ using a ‘master fuzzy system’. This approach is shown to be able to include the advantages of different modelling techniques altogether by requiring less training and by minimising the efforts relating optimisation of the final structure. The proposed approach is then successfully applied to the industrial problems of predicting machining induced residual stresses for aerospace alloy components as well as modelling the mechanical properties of heat-treated alloy steels, both representing complex, non-linear and multi-dimensional environments.

Item Type: Article
DOI/Identification number: 10.1016/j.asoc.2012.01.021
Uncontrolled keywords: data-driven modelling; fuzzy system; model fusion; engineering material; residual stress; mechanical property; aluminium alloy; steel
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering
T Technology > TA Engineering (General). Civil engineering (General) > TA401 Materials engineering and construction
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Qian Zhang
Date Deposited: 18 Sep 2015 00:25 UTC
Last Modified: 16 Nov 2021 10:21 UTC
Resource URI: (The current URI for this page, for reference purposes)
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