Footprint of uncertainty for type-2 fuzzy sets

Information Sciences

Volumn 272, Issue , 2014, Pages 96-110

  Mo, Hong ^a   Wang, F Y ^b,c   Zhou, Min ^a,d   Li, Runmei ^d   Xiao, Zhiquan ^e  

^a CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b INSTITUTE OF AUTOMATION   (China)

^c NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^d BEIJING JIAOTONG UNIVERSITY   (China)

^e WUHAN TEXTILE UNIVERSITY   (China)

Author keywords

Footprint of uncertainty (FOU); Interval type 2 fuzzy set (IT2 FS); Partition method of FOU; Type 2 fuzzy set (T2 FS)

Indexed keywords

ARTIFICIAL INTELLIGENCE; SOFTWARE ENGINEERING;

FOOTPRINT OF UNCERTAINTIES; INTERVAL TYPE-2 FUZZY SETS; INTERVAL TYPE2 FUZZY SET (IT2 FS); LOWER MEMBERSHIP FUNCTIONS; MULTIVALUED MAPPINGS; PARTITION METHODS; SECONDARY MEMBERSHIPS; TYPE-2 FUZZY SET;

FUZZY SETS;

EID: 84899477751     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.02.092     Document Type: Article

References (70)

1. D. Akay, O. Kulak, and B. Henson Conceptual design evaluation using interval type-2 fuzzy information axiom Comput. Indust. 62 2011 138 146
2. J. Aisbett, J.T. Richard, and D. Morgenthaler Multivariate modeling and type-2 fuzzy sets Fuzzy Sets Syst. 163 2011 78 95
3. R. Aliev, W. Pedrycz, and B. Guirimov et al. Type-2 fuzzy nueral networks with fuzzy clustering and differential evolution optimization Inform. Sci. 181 2011 1591 1608
4. O. Castillo, and P. Melin Optimization of type-2 fuzzy systems based on bio-inspired methods: a concise review Inform. Sci. 205 2012 1 19
5. O. Castillo, and P. Melin A review on the design and optimization of interval type-2 fuzzy controllers Appl. Soft Comput. 12 2012 1267 1278
6. O. Castillo, P. Melin, and W. Pedrycz Design of interval type-2 fuzzy models through optimal granularity allocation Appl. Soft Comput. 11 2011 5590 5601
7. N.R. Cazarez-Castro, L.T. Aguilar, and O. Castillo Designing type-1 and type-2 fuzzy logic controllers via fuzzy lyapunov synthesis for nonsmooth mechanical system Eng. Appl. Artif. Intell. 25 2012 971 979
8. S. Chakravarty, and P.K. Dash A PSO based integrated functional link net and interval type-2 fuzzy logic system for predicting stock market indices Appl. Soft Comput. 12 2012 931 941
9. S. Chen,Y. Chang, Fuzzy interpolative reasoning based on the footprints of uncertainty of interval T2 FSs, in: 2010 International Conference on Computer Aspects of Social Networks, Taiyuan, China, 2010, pp. 569-572.
10. B. Choi, and F. Rhee Interval type-2 fuzzy membership function generation methods for pattern recognition Inform. Sci. 179 2009 2102 2122
11. S. Couland, and R. John Geometric type-1 and type-2 fuzzy logic systems IEEE Trans. Fuzzy Syst. 15 1 2007 3 15
12. T. Dereli, A. Baykasoglu, and K. Altun et al. Industrial applications of type-2 fuzzy sets and systems: a concise review Comput. Indust. 62 2011 125 137
13. M.H. Fazel Zarandi, A. Doostaparast Torshizi, and I.B. Turksen et al. A new indirect approach to the type-2 fuzzy systems modeling and design Inform. Sci. 232 2013 346 365
14. M.H. Fazel Zarandi, M.R. Faraji, and M. Karbasian Interval type-2 fuzzy expert system for prediction of carbon monoxide concentration on mega-cities Appl. Soft Comput. 12 2012 291 301
15. M.H. Fazel Zarandi, R. Gamasaee, and I.B. Turksen A type-2 fuzzy c-regression clustering algorithm for Takagi-Sugeno system identification and its application in the steel industry Inform. Sci. 187 2012 179 203
16. M.H. Fazel Zarandi, B. Rezaee, and I.B. Turksen et al. A type-2 fuzzy rule-based expert system model for stock price analysis Expert Syst. Appl. 36 2009 139 154
17. M.H. Fazel Zarandi, I.B. Turksen, and O. Torabi Kasbi Type-2 fuzzy modeling for desulphurization of steel process Expert Syst. Appl. 32 2007 157 171
18. S.S. Gilan, M.H. Sebt, and V. Shahhosseini Computing with words for hierarchical competency based selection of personal in construction companies Appl. Soft Comput. 12 2012 860 871
19. C. Glackin, L. Maguire, and R. Mcivor et al. A comparison of fuzzy strategies for corporate acquistion analysis Fuzzy Sets Syst. 158 2007 2039 2056
20. S. Greenfield, and F. Chiclana Defuzzification of the discretised generalised type-2 fuzzy set: experimental evaluation Inform. Sci. 244 2013 1 25
21. S. Greenfield, F. Chiclana, and R. John et al. The sampling method of defuzzification for type-2 fuzzy sets:Experimental evaluation Inform. Sci. 189 2012 77 92
22. D. Hidalgo, P. Melin, and O. Castillo An optimization method for designing type-2 fuzzy inference system based on the footprint of uncertainty using genetic algorithms Expert Syst. Appl. 39 2012 4590 4598
23. R. Hosseini, S.D. Qanadli, and S. Barman et al. An automatic approach for learning and tuning Gaussian interval type-2 fuzzy membership function applied to lung CAD classification system IEEE Trans. Fuzzy Syst. 20 2 2012 224 234
24. B.Q. Hu, and C.K. Kwong On tpye-2 fuzzy sets and their t-norm operations Inform. Sci. 255 2014 58 81
25. C. Juang, R. Huang, and Y. Lin A recurrent self-evolving interval type-2 fuzzy neural network for dynamic system processing IEEE Trans. Fuzzy Syst. 17 5 2009 1092 1105
26. N.N. Karnik Operations on T2 FS Fuzzy Sets Syst. 122 2001 327 348
27. N.N. Karnik Centroid of a T2 FS Inform. Sci. 132 2007 195 220
28. N.N. Karnik, and J.M. Mendel Applications of type-2 fuzzy logic systems to forecasting of time-series Inform. Sci. 120 1999 89 111
29. C. Leal-Ramirez, O. Castillo, and P. Melin et al. Simulation of the bird age-structured population growth based on an interval type-2 fuzzy cellular structure Inform. Sci. 181 2011 519 535
30. Y. Li, and J. Huang Type-2 fuzzy mathematical modeling and analysis of the dynamical behaviors of complex ecosystems Simul. Modell. Pract. Theory 16 2008 1379 1391
31. Y. Li, and X. Sun Modelling dynamic niche and community model by T2 FS Ecol. Modell. 211 2008 375 382
32. Q. Liang, N.N. Karnik, and J.M. Mendel MPEG VBR video traffic modeling and classification using fuzzy technique IEEE Trans. Fuzzy Syst. 9 1 2001 183 193
33. Q. Liang, and J.M. Mendel Interval type-2 fuzzy logic systems: theory and design IEEE Trans. Fuzzy Syst. 8 5 2000 535 550
34. Y. Maldonado, O. Castillo, and P. Melin Particle swarm optimization of interval type-2 fuzzy systems for FPGA applications Appl. Soft Comput. 13 2013 496 508
35. P. Melin, L. Astudillo, and O. Castillo et al. Optimal design of type-2 and type-1 fuzzy tracking controllers for autonomous mobile robots under perturbed toques using a new chemical optimization paradigm Expert Syst. Appl. 40 2013 3185 3195
36. J.M. Mendel, Footprint of uncertainty and its importance to T2 FSs, in Proceedings of the 6th IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, Cananda, 2002, pp. 587-592.
37. J.M. Mendel On a 50% saving in the computation of the centroid of a symmetrical interval T2 FS Inform. Sci. 172 2005 417 430
38. J.M. Mendel Advances in type-2 fuzzy sets and systems Inform. Sci. 177 2007 84 110
39. J.M. Mendel Computing with words and its relationship with fuzzistcs Inform. Sci. 177 2007 988 1006
40. J.M. Mendel, and R.I. John Type-2 fuzzy set made simple IEEE Trans. Fuzzy Syst. 10 2 2002 117 127
41. J.M. Mendel, R.I. John, and F. Liu Interval type-2 fuzzy logic systems made simple IEEE Trans. Fuzzy Syst. 14 6 2006 808 821
42. J.M. Mendel, and H. Wu New results about the centriod of an interval type-2 fuzzy set, including the centriod of a fuzzy granule Inform. Sci. 177 2007 360 377
43. J.M. Mendel, and D. Wu Perceptual reasoning for perceptual computing IEEE Trans. Fuzzy Syst. 16 6 2008 1550 1564
44. M. Mizumoto, and K. Tanaka Some properties of fuzzy sets of type-2 Inform. Contr. 31 1976 312 340
45. H. Mo Linguistic dynamic orbits in the time varying universe of discourse Acta Automatica Sinica 38 10 2012 1585 1594 (in Chinese)
46. H. Mo, and F.-Y. Wang Linguistic Dynamic Systems and Type-2 Fuzzy Logic 2013 China Science and Technology Press Beijing (in Chinese)
47. H. Mo, and F.-Y. Wang Linguistic dynamic systems based on computing with words and their stabilities Sci. China, F-Ser.: Inform. Sci. 52 5 2009 780 796
48. H. Mo, T. Wang, Modification of FOU of type-2 fuzzy sets, in: Chinese Automation Conference, 2011, Beijing.
49. H. Mo, M. Zhou, On the definition of type-2 fuzzy sets, in: Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing, China, 2012, pp. 601-605.
50. S.F. Molaeezadeh, and M.H. Moradi Bifurcating fuzzy sets: theory and application Neurcomputing 118 2013 268 278
51. A. Niewiadomski A type-2 fuzzy approach to linguistic summarization of data IEEE Trans. Fuzzy Syst. 16 1 2008 198 212
52. A. Niewiadomski On finity, countability, cardinalities, and cylindric extension of type-2 fuzzy sets in linguistic summarization of databases IEEE Trans. Fuzzy Syst. 18 3 2012 532 545
53. Ondrej Linda, and Milos Manic Interval type-2 fuzzy voter design for fault tolerant systems Inform. Sci. 181 2011 2833 2950
54. I. Ozkan, and I.B. Turksen MiniMax ε-star cluster validity index for type-2 fuzziness Inform. Sci. 184 2012 64 74
55. W. Pedrycz Granular Computing: Analysis and Design of Intelligent Systems 2013 CRC Press/Francis Taylor Boca Raton
56. J.I. Richard, J. Aisbett, and G. Gibbon Fuzzy subsethood for fuzzy sets of type-2 and generalized type-n IEEE Trans. Fuzzy Syst. 17 1 2009 50 60
57. S.W. Tung, C. Quek, and C. Guan eT2FIS: an evolving type-2 neural fuzzy inference system Inform. Sci. 220 2013 124 148
58. Z. Takáč Inclusion and subsethood measure for interval-valued fuzzy sets and for continuous type-2 fuzzy sets Fuzzy Sets Syst. 224 2013 106 120
59. C. Ulu, M. Güzelkaya, and I. Eksin Granular type-2 membership functions: a new approach to formation of footprint of uncertainty in type-2 fuzzy sets Appl. Soft Comput. 13 2013 3713 3728
60. A. Visconti, and H. Tahayori Artificial immune system based on interval type-2 fuzzy set paradigm Appl. Soft Comput. 11 2011 4055 4063
61. F.-Y. Wang On the abstraction of conventional dynamic systems: from numerical analysis to linguistic analysis Inform. Sci. 171 1-3 2005 233 259
62. W. Wang, X. Liu, and Y. Qin Multi-attribute group decision making models under interval type-2 fuzzy environment Knowl.-Based Syst. 30 2012 121 128
63. D. Wu, and J.M. Mendel Uncertainty measures for interval type-2 fuzzy sets Inform. Sci. 177 2007 5378 5393
64. D. Wu, J.M. Mendel, and S. Coupland Enhanced interval approach for encoding words into interval type-2 fuzzy sets and its convergence analysis IEEE Trans. Fuzzy Syst. 20 3 2012 499 513
65. D. Wu, and W. Tan A simplified type-2 fuzzy logic controller for real-time control ISA Trans. 45 4 2006 503 516
66. L. Zadeh The concept of a linguistic variable and its application to approximate reasoning-1 Inform. Sci. 8 1975 199 249
67. D. Zhai, and J.M. Mendel Uncertainty measures for general type-2 fuzzy sets Inform. Sci. 181 2011 503 518
68. Z. Zhang, and S. Zhang A novel approach to multi attribute group decision making based on trapezoidal interval type-2 fuzzy soft sets Appl. Math. Model. 37 2013 4948 4971
69. Z. Zhang On interval type-2 fuzzy sests Knowl.-Based Syst. 35 2012 1 13
70. S. Zhou, F. Chiclana, and R.I. John et al. Type-1 OWA operators for aggregating uncertain information with uncertain weights induces by type-2 linguistic quantifiers Fuzzy Sets Syst. 159 2008 3281 3296