Accuracy and complexity evaluation of defuzzification strategies for the discretised interval type-2 fuzzy set

[1]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[2]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[3]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[4]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[5]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[6]  Siegfried Gottwald,et al.  Fuzzy Sets and Fuzzy Logic , 1993 .

[7]  Douglas C. Montgomery,et al.  Applied Statistics and Probability for Engineers, Third edition , 1994 .

[8]  Dimitar P. Filev,et al.  Fuzzy SETS AND FUZZY LOGIC , 1996 .

[9]  Etienne E. Kerre,et al.  Defuzzification: criteria and classification , 1999, Fuzzy Sets Syst..

[10]  Francisco Herrera,et al.  Multiperson decision-making based on multiplicative preference relations , 2001, Eur. J. Oper. Res..

[11]  Francisco Herrera,et al.  Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations , 2001, Fuzzy Sets Syst..

[12]  Jerry M. Mendel,et al.  Centroid of a type-2 fuzzy set , 2001, Inf. Sci..

[13]  J. Mendel Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .

[14]  Francisco Herrera,et al.  A note on the internal consistency of various preference representations , 2002, Fuzzy Sets Syst..

[15]  Jerry M. Mendel,et al.  Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..

[16]  Francisco Herrera,et al.  A consensus model for multiperson decision making with different preference structures , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[17]  Jerry M. Mendel,et al.  Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems , 2002, IEEE Trans. Fuzzy Syst..

[18]  Fernando Gomide,et al.  Book Review: "Uncertain rule-based fuzzy logic systems: introduction and new directions" by Jerry M. Mendel , 2003, Fuzzy Sets Syst..

[19]  Robert V. Brill,et al.  Applied Statistics and Probability for Engineers , 2004, Technometrics.

[20]  R. John,et al.  Type-2 Fuzzy Logic: A Historical View , 2007, IEEE Computational Intelligence Magazine.

[21]  Simon Coupland Type-2 Fuzzy Sets: Geometric Defuzzification and Type-Reduction , 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

[22]  Myriam Regattieri Delgado,et al.  General Type-2 Fuzzy Inference Systems: Analysis, Design and Computational Aspects , 2007, 2007 IEEE International Fuzzy Systems Conference.

[23]  Robert Ivor John,et al.  Geometric Type-1 and Type-2 Fuzzy Logic Systems , 2007, IEEE Transactions on Fuzzy Systems.

[24]  Janusz T. Starczewski On Defuzzification of Interval Type-2 Fuzzy Sets , 2008, ICAISC.

[25]  Feilong Liu,et al.  An efficient centroid type-reduction strategy for general type-2 fuzzy logic system , 2008, Inf. Sci..

[26]  Woei Wan Tan,et al.  Towards an efficient type-reduction method for interval type-2 fuzzy logic systems , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[27]  Robert Ivor John,et al.  Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers , 2008, Fuzzy Sets Syst..

[28]  Hani Hagras,et al.  Introduction to Interval Type-2 Fuzzy Logic Controllers - Towards Better Uncertainty Handling in Real World Applications , 2009 .

[29]  Robert Ivor John,et al.  The Collapsing Method: Does the Direction of Collapse Affect Accuracy? , 2009, IFSA/EUSFLAT Conf..

[30]  R. John,et al.  Type-reduction of the discretised interval type-2 fuzzy set , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[31]  Jerry M. Mendel,et al.  Enhanced Karnik--Mendel Algorithms , 2009, IEEE Transactions on Fuzzy Systems.

[32]  Robert Ivor John,et al.  The collapsing method of defuzzification for discretised interval type-2 fuzzy sets , 2009, Inf. Sci..

[33]  Robert Ivor John,et al.  An Interval Type-2 Fuzzy Distribution Network , 2009, IFSA/EUSFLAT Conf..

[34]  Janusz T. Starczewski Efficient triangular type-2 fuzzy logic systems , 2009, Int. J. Approx. Reason..

[35]  Hani Hagras,et al.  Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks , 2009, IEEE Transactions on Fuzzy Systems.

[36]  Jonathan M. Garibaldi,et al.  A novel dual-surface type-2 controller for micro robots , 2010, International Conference on Fuzzy Systems.

[37]  Robert Ivor John,et al.  Type-2 defuzzification: Two contrasting approaches , 2010, International Conference on Fuzzy Systems.

[38]  John T. Rickard,et al.  Type-2 Fuzzy Sets as Functions on Spaces , 2010, IEEE Transactions on Fuzzy Systems.

[39]  J. Yi,et al.  SIRMS BASED INTERVAL TYPE-2 FUZZY INFERENCE SYSTEMS: PROPERTIES AND APPLICATION , 2010 .

[40]  Miguel A. Melgarejo,et al.  Implementing an interval type-2 fuzzy processor onto a DSC 56F8013 , 2010, International Conference on Fuzzy Systems.

[41]  Hani Hagras,et al.  A type-2 fuzzy logic based model for renewable wind energy generation , 2010, International Conference on Fuzzy Systems.

[42]  Okyay Kaynak,et al.  Design of an adaptive interval type-2 fuzzy logic controller for the position control of a servo system with an intelligent sensor , 2010, International Conference on Fuzzy Systems.

[43]  Okyay Kaynak,et al.  A novel training method based on variable structure systems approach for interval type-2 fuzzy neural networks , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[44]  Type-reduction of the discretised interval type-2 fuzzy set: What happens as discretisation becomes finer? , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[45]  Humberto Bustince,et al.  Representing images by means of interval-valued fuzzy sets. Application to stereo matching , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[46]  Francisco Herrera,et al.  A case study on medical diagnosis of cardiovascular diseases using a Genetic Algorithm for Tuning Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[47]  Federico Sanabria,et al.  Towards a coevolutionary approach for interval type-2 fuzzy modeling , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[48]  Héctor Pomares,et al.  On comparing non-singleton type-1 and singleton type-2 fuzzy controllers for a nonlinear servo system , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[49]  Milos Manic,et al.  Uncertainty modeling for interval Type-2 Fuzzy Logic Systems based on sensor characteristics , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[50]  Francisco Chiclana,et al.  Combining the -Plane Representation with an Interval Defuzzification Method , 2011, EUSFLAT Conf..

[51]  Xinwang Liu,et al.  Some extensions of the karnik-mendel algorithms for computing an interval type-2 fuzzy set centroid , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[52]  Dongrui Wu,et al.  Comparison and practical implementation of type-reduction algorithms for type-2 fuzzy sets and systems , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

[53]  Karim Djouani,et al.  On an interval type-2 TSK FLS A1-C1 consequent parameters tuning , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[54]  Francisco Herrera,et al.  A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position , 2011, Int. J. Approx. Reason..

[55]  Humberto Bustince,et al.  A construction method of interval-valued Fuzzy Sets for image processing , 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

[56]  Robert Ivor John,et al.  The sampling method of defuzzification for type-2 fuzzy sets: Experimental evaluation , 2012, Inf. Sci..

[57]  Babak Rezaee,et al.  A multi-objective approach to design of interval type-2 fuzzy logic systems , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[58]  H. Nurmi On the Relevance of Theoretical Results to Voting System Choice , 2012 .

[59]  Ali Kashif Bashir,et al.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2013, ICIRA 2013.

[60]  Engin Yesil,et al.  Exact inversion of decomposable interval type-2 fuzzy logic systems , 2013, Int. J. Approx. Reason..

[61]  Mohammad Hassan Moradi,et al.  A 2uFunction representation for non-uniform type-2 fuzzy sets: Theory and design , 2013, Int. J. Approx. Reason..