Choquet fuzzy integral based modeling of non-linear system

Srivastava, Smriti, Singh, Madhusudan, Madasu, Vamsi K., & Hanmandlu, Madasu (2008) Choquet fuzzy integral based modeling of non-linear system. Applied Soft Computing, 8(2), pp. 839-848.


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For dealing with the adjacent input fuzzy sets having overlapping information, non-additive fuzzy rules are formulated by defining their consequent as the product of weighted input and a fuzzy measure. With the weighted input, need arises for the corresponding fuzzy measure. This is a new concept that facilitates the evolution of new fuzzy modeling. The fuzzy measures aggregate the information from the weighted inputs using the λ-measure. The output of these rules is in the form of the Choquet fuzzy integral. The underlying non-additive fuzzy model is investigated for identification of non-linear systems. The weighted input which is the additive S-norm of the inputs and their membership functions provides the strength of the rules and fuzzy densities required to compute fuzzy measures subject to q-measure are the unknown functions to be estimated. The use of q-measure is a powerful way of simplifying the computation of @l-measure that takes account of the interaction between the weighted inputs. Two applications; one real life application on signature verification and forgery detection, and another benchmark problem of a chemical plant illustrate the utility of the proposed approach. The results are compared with those existing in the literature.

Impact and interest:

12 citations in Scopus
10 citations in Web of Science®
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ID Code: 12746
Item Type: Journal Article
Refereed: Yes
Keywords: Choquet Integral, λ, Measure, q, Measure, Fuzzy density, Fuzzy rule based identification
DOI: 10.1016/j.asoc.2007.07.001
ISSN: 1568-4946
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Simulation and Modelling (080110)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2008 Elsevier
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 29 Feb 2008 00:00
Last Modified: 10 Aug 2011 14:30

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