Mamdani-Type Fuzzy Modelling via Hierarchical Clustering and Multi-Objective Particle Swarm Optimisation (FM-HCPSO)

Zhang, Qian and Mahfouf, Mahdi (2008) Mamdani-Type Fuzzy Modelling via Hierarchical Clustering and Multi-Objective Particle Swarm Optimisation (FM-HCPSO). International Journal of Computational Intelligence Research, 4 (4). pp. 314-328. ISSN 09741259. (doi: (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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In this paper, a systematic data-driven fuzzy modelling approach is proposed, which integrates transparent fuzzy systems (linguistic fuzzy systems) with an effective evolutionary computing based algorithm - the new structure Particle Swarm Optimisation (nPSO). In this modelling mechanism, a new data clustering technique via an improved hierarchical clustering algorithm is designed for the initial fuzzy model generation. Multi-objective optimisation techniques are then employed for the improvement of the generated fuzzy model, which takes into account both the accuracy and the interpretability performances of the fuzzy system. This proposed modelling approach is tested on two benchmark problems and a high-dimensional modelling problem using real industrial data. This latter concerns the prediction of the mechanical properties of alloy steels. Experimental results show that the proposed approach is very effective in eliciting accurate as well as interpretable Mamdani-type fuzzy models.

Item Type: Article
Uncontrolled keywords: Fuzzy, Data-driven Modelling, Particle Swarm Optimisation, Hierarchical Clustering, Multi-objective Optimisation
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
T Technology > TJ Mechanical engineering and machinery > Intelligent control systems
T Technology > TN Mining engineering. Metallurgy
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Qian Zhang
Date Deposited: 16 Sep 2015 16:32 UTC
Last Modified: 05 Oct 2015 13:21 UTC
Resource URI: (The current URI for this page, for reference purposes)
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