Evaluation and comparison of type reduction algorithms from a forecast accuracy perspective

Khosravi, Abbas, Nahavandi, Saeid and Khosravi, Rihanna 2013, Evaluation and comparison of type reduction algorithms from a forecast accuracy perspective, in FUZZ-IEEE 2013 : Proceedings of the IEEE International Conference on Fuzzy Systems, IEEE, Piscataway, N.J., pp. 1-7.

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Title Evaluation and comparison of type reduction algorithms from a forecast accuracy perspective
Author(s) Khosravi, Abbas
Nahavandi, Saeid
Khosravi, Rihanna
Conference name Fuzzy Systems. IEEE International Conference (2013 : Hyderabad, India)
Conference location Hyderabad, India
Conference dates 7-10 Jul. 2013
Title of proceedings FUZZ-IEEE 2013 : Proceedings of the IEEE International Conference on Fuzzy Systems
Editor(s) [Unknown]
Publication date 2013
Conference series IEEE International Conference on Fuzzy Systems
Start page 1
End page 7
Total pages 7
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) type reduction
interval type-2 fuzzy logic system
forecasting
Summary A variety of type reduction (TR) algorithms have been proposed for interval type-2 fuzzy logic systems (IT2 FLSs). The focus of existing literature is mainly on computational requirements of TR algorithm. Often researchers give more rewards to computationally less expensive TR algorithms. This paper evaluates and compares five frequently used TR algorithms from a forecasting performance perspective. Algorithms are judged based on the generalization power of IT2 FLS models developed using them. Four synthetic and real world case studies with different levels of uncertainty are considered to examine effects of TR algorithms on forecasts accuracies. It is found that Coupland-Jonh TR algorithm leads to models with a better forecasting performance. However, there is no clear relationship between the width of the type reduced set and TR algorithm.
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 910299 Microeconomics not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2013, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30057148

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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