A monotonicity index for the monotone fuzzy modeling problem

Tay, Kai Meng, Lim, Chee Peng and Jee, Tze Ling 2012, A monotonicity index for the monotone fuzzy modeling problem, in FUZZ-IEEE 2012 : Proceedings of the IEEE 2012 International Conference on Fuzzy Systems, IEEE, [Piscataway, N. J.], pp. 1-8, doi: 10.1109/FUZZ-IEEE.2012.6250829.

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Title A monotonicity index for the monotone fuzzy modeling problem
Author(s) Tay, Kai Meng
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Jee, Tze Ling
Conference name International Conference on Fuzzy Systems (2012 : Brisbane, Qld.)
Conference location Brisbane, Qld.
Conference dates 10-15 Jun. 2012
Title of proceedings FUZZ-IEEE 2012 : Proceedings of the IEEE 2012 International Conference on Fuzzy Systems
Editor(s) [unknown]
Publication date 2012
Conference series International Conference on Fuzzy Systems
Start page 1
End page 8
Total pages 8
Publisher IEEE
Place of publication [Piscataway, N. J.]
Keyword(s) fuzzy inference system
monotonicity property
monotonicity index
the sufficient conditions
monto carlo
evolutionary computation optimization
system identification
Summary In this paper, the problem of maintaining the (global) monotonicity and local monotonicity properties between the input(s) and the output of an FIS model is addressed. This is known as the monotone fuzzy modeling problem. In our previous work, this problem has been tackled by developing some mathematical conditions for an FIS model to observe the monotonicity property. These mathematical conditions are used as a set of governing equations for undertaking FIS modeling problems, and have been extended to some advanced FIS modeling techniques. Here, we examine an alternative to the monotone fuzzy modeling problem by introducing a monotonicity index. The monotonicity index is employed as an approximate indicator to measure the fulfillment of an FIS model to the monotonicity property. It allows the FIS model to be constructed using an optimization method, or be tuned to achieve a better performance, without knowing the exact mathematical conditions of the FIS model to satisfy the monotonicity property. Besides, the monotonicity index can be extended to FIS modeling that involves the local monotonicity problem. We also analyze the relationship between the FIS model and its monotonicity property fulfillment, as well as derived mathematical conditions, using the Monte Carlo method.
ISBN 1467315079
ISSN 1098-7584
Language eng
DOI 10.1109/FUZZ-IEEE.2012.6250829
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048734

Document type: Conference Paper
Collections: Institute for Frontier Materials
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