On the use of fuzzy rule interpolation techniques for monotonic multi-input fuzzy rule base models

Tay, Kai Meng and Lim, Chee Peng 2009, On the use of fuzzy rule interpolation techniques for monotonic multi-input fuzzy rule base models, in FUZZ-IEEE 2009 : Proceedings of the IEEE International Conference on Fuzzy Systems, IEEE, Piscataway, N. J., pp. 1736-1740.

Attached Files
Name Description MIMEType Size Downloads

Title On the use of fuzzy rule interpolation techniques for monotonic multi-input fuzzy rule base models
Author(s) Tay, Kai Meng
Lim, Chee Peng
Conference name International Conference on Fuzzy Systems (2009 : Jeju Island, Korea)
Conference location Jeju Island, Korea
Conference dates 20-24 Aug. 2009
Title of proceedings FUZZ-IEEE 2009 : Proceedings of the IEEE International Conference on Fuzzy Systems
Editor(s) [Unknown]
Publication date 2009
Conference series International Conference on Fuzzy Systems
Start page 1736
End page 1740
Total pages 5
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) brute force
engineering problems
fuzzy inference systems
fuzzy rule base models
fuzzy rule interpolation
interpolation process
interpolation techniques
mathematical derivation
monotonicity
multiinput
ordering criteria
rule selection
search algorithms
Summary Constructing a monotonicity relating function is important, as many engineering problems revolve around a monotonicity relationship between input(s) and output(s). In this paper, we investigate the use of fuzzy rule interpolation techniques for monotonicity relating fuzzy inference system (FIS). A mathematical derivation on the conditions of an FIS to be monotone is provided. From the derivation, two conditions are necessary. The derivation suggests that the mapped consequence fuzzy set of an FIS to be of a monotonicity order. We further evaluate the use of fuzzy rule interpolation techniques in predicting a consequent associated with an observation according to the monotonicity order. There are several findings in this article. We point out the importance of an ordering criterion in rule selection for a multi-input FIS before the interpolation process; and hence, the practice of choosing the nearest rules may not be true in this case. To fulfill the monotonicity order, we argue with an example that conventional fuzzy rule interpolation techniques that predict each consequence separately is not suitable in this case. We further suggest another class of interpolation techniques that predicts the consequence of a set of observations simultaneously, instead of separately. This can be accomplished with the use of a search algorithm, such as the brute force, genetic algorithm or etc.
ISBN 142443596X
9781424435968
ISSN 1098-7584
Language eng
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:30048727

Document type: Conference Paper
Collection: Institute for Frontier Materials
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 34 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Wed, 26 Sep 2012, 09:12:40 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.