Abstract
Fuzzy information processing in type-2 fuzzy systems has been implemented in most cases based on the Karnik and Mendel (KM) and Wu-Mendel (WM) approaches. However, both of these approaches are time consuming for most real-world applications, in particular for control problems. For this reason, a more efficient method based on evolutionary algorithms has been proposed by Castillo and Melin (CM). This method is based on directly obtaining the type reduced results by using an evolutionnary algorithm (EA). The basic idea is that with an EA the upper and lower membership functions in the output can be obtained directly based on experimental data available for a particular problem. A comparative study (in control applications) of the three methods, based on accuracy and efficiency is presented, and the CM method is shown to outperform both the KM and WM methods in efficiency while accuracy produced by this method is comparable.
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Castillo, O., Melin, P. (2011). Comparative Study of Fuzzy Information Processing in Type-2 Fuzzy Systems. In: Pedrycz, W., Chen, SM. (eds) Granular Computing and Intelligent Systems. Intelligent Systems Reference Library, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19820-5_5
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DOI: https://doi.org/10.1007/978-3-642-19820-5_5
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