publication . Conference object . Part of book or chapter of book . 2015

On transitioning from type-1 to interval type-2 fuzzy logic systems

Aladi, JH; Wagner, C; Garibaldi, JM; Pourabdollah, A;
  • Published: 01 Jan 2015
  • Country: Italy
Capturing the uncertainty arising from system noise has been a core feature of fuzzy logic systems (FLSs) for many years. This paper builds on previous work and explores the methodological transition of type-1 (T1) to interval type-2 fuzzy sets (IT2 FSs) for given “levels” of uncertainty. Specifically, we propose to transition from T1 to IT2 FLSs through varying the size of the Footprint Of Uncertainty (FOU) of their respective FSs while maintaining the original FS shape (e.g., triangular) and keeping the size of the FOU over the FS as constant as possible. The latter is important as it enables the systematic relating of FOU size to levels of uncertainty and vic...
free text keywords: Fuzzy set, Artificial intelligence, business.industry, business, Machine learning, computer.software_genre, computer, Time series, Footprint, Control theory, Membership function, Versa, Fuzzy logic system, Noise measurement, Computer science
Related Organizations
33 references, page 1 of 3

[1] J.Aladi,C.Wagner, andJ.Garibaldi",Type-l or intervaltype-2 fuzzy logic systems -on the relationshipof the amount of uncertaintyandfou size," in IEEE Int. Conf on Fuzzy Systems, 2014, pp.2360-2367.

[2] L. A.Zadeh, "The concept of alinguistic variableandits application to approximate reasoning-I," Inofrmation Sciences, vol.8, no. 3, pp. 199-249, 1975. [OpenAIRE]

[3] J.Mendel, Uncertain rule-based fuzzy logic systems: introduction and new directions. Upper SaddleRiver, NJ, USA: Prentice-HaU,2001.

[4] D.Wu and J. M. Mendel, "Uncertainty measures for intervaltype-2 fuzzy sets," Inofrmation Sciences, vol.177, no.23, pp.5378-5393, 2007.

[5] C.WagnerandH.Hagras,"Towardgeneral type-2 fuzzylogic systems basedon zSlices," IEEE Trans. Fuzzy Syst., vol.18, no.4, pp.637-660, 2010.

[6] J.M.Mendel andR.B.John, "Type-2 fuzzy sets made simple," IEEE Trans. Fuzzy Syst., vol.10, no.2, pp.117-127, 2002.

[7] S.CouplandandR.John, "Geometric type-l andtype-2 fuzzy logic systems," IEEE Trans. Fuzzy Syst., vol.15, no.1, pp.3-15, 2007.

[8] J.M.Mendel andF.Liu, "On new quasi-type-2fuzzy logic systems," in IEEE Int. Conf on Fuzzy Systems, 2008, pp.354-360.

[9] F. Liu, "An eficient centroid type-reduction strategyfor general type-2 fuzzy logic system," Inofrmation Sciences, vol.178, no.9, pp.2224- 2236, 2008.

[10] S.Greenefild andR. John, "Optimised generalisedtype-2join andmeet operations," in IEEE Int. Fuzzy Systems Conf, 2007, pp.1-6.

[11] C.Wagner andH.Hagras,"zSlices-towardsbridging the gapbetween intervalandgeneraltype-2 fuzzy logic," in IEEE Int. Conf on Fuzzy Systems, 2008, pp.489-497.

[12] J. Mendel, R.John, and F. Liu",Intervaltype-2 fuzzy logic systems made simple," IEEE Trans. Fuzzy Syst., vol.14, no.6, pp. 808-821, 2006.

[13] N. N.Karnik and J. M.Mendel, "Applicationsof type-2 fuzzy logic systems to forecastingof time-series," Information Sciences, vol.120, no.1, pp.89-111, 1999.

[14] O. LindaandM. Manic, "Uncertainty-robust design of intervaltype2 fuzzy logic controller for delta parallerlobot," IEEE Tnras. Ind. Informat., vol.7, no.4, pp.661-670, 2011.

[15] N. SahabandH.Hagras,"Adaptive non-singleton type-2 fuzzy logic systems: a way forward for handling numerical uncertainties in real world applications,I"nt. 1. Comput. Commun. Contlro, vol.5, no.3, pp. 503-529, 2011.

33 references, page 1 of 3
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue