[1]WANG Shi-tong,XIE Zhen-ping,LI Han-xiong.Statistical sensitivity analysis of fuzzy reasoning[J].CAAI Transactions on Intelligent Systems,2007,2(2):57-64.
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Statistical sensitivity analysis of fuzzy reasoning

References:
[1] TORRA V. OWA operators in data modeling and reidentification [J]. IE EE Trans on Fuzzy Systems, 2004, 12(5): 652-660.
[2]CAI K C. Robustness of fuzzy reasoning and δequalities of fuzzy sets [J]. IEEE Trans on Fuzzy Systems, 2001, 9(5): 738-750.
[3]YING M S. Perturbation of Fuzzy reasoning [J]. IEEE Trans on Fuzzy Sy stems, 1999, 7(5): 625-629.
[4]ZADEH L A. The concept of a linguistic variable and its applications to approximate reasoning (I)[J]. Information Science, 1974, 8(2): 199-249.
[5]ZADEH L A. The concept of a linguistic variable and its applications to approximate reasoning (II) [J]. Information Science, 1974, 8(3): 301-357.
[6]ZADEH L A. The concept of a linguistic variable and its applications to approximate reasoning (III) [J]. Information Science, 1975, 9(1): 43-80.
[7]DUBOIS D, PRADE H. Fuzzy sets in approximate reasoning, Part 1:Inference w ith possibility distributions [J]. Fuzzy Sets and Systems, 1991, 40(1): 143-20 2.
[8]DUBOIS D, PRADE H. Fuzzy sets in approximate reasoning, Part 2:Logical a pproaches [J]. Fuzzy Sets and Systems, 1991, 40(1): 203-244.
[9]LIU Y, KERRE F E. An overview of fuzzy quantifiers (Ⅱ): reasoning and a pplications [J]. Fuzzy Sets and Systems, 1998, 95(2): 135-146.
[10]NAKANISHI H, TURKSEN I B, SUGENO M. A review and comparison of si x reasoning methods [J]. Fuzzy Sets and Systems, 1993, 57(3): 257-294.
[11]WANG G J. On the logic foundation of fuzzy reasoning [J]. Information Science, 1999, 117(1): 47-88.
[12]MIZUMOTO M, ZIMMERMANN H J. Comparison of fuzzy reasoning methods [J] . Fuzzy Sets and Systems, 1982, 8(3): 151-186.
[13]CAO Z, KANDEL A. Applicability of some fuzzy implication operators [J ]. Fuzzy Sets and Systems, 1989, 31(2): 151-186. 
[14]WANG L X. A course in fuzzy systems and control[M]. Englewood Cliffs, NJ: PrenticeHall, 1997.
[15]CAI KY, δequalities of fuzzy sets [J]. Fuzzy Sets and Systems, 19 97, 76(1): 97-112.
[16]PAPPIS C P. Value approximation of fuzzy systems variables [J]. Fuzzy Sets and Systems, 1991, 39(1): 111-115.
[17]HONG D H, HWANG SY. A note on the value similarity of fuzzy systems var iables [J]. Fuzzy Sets and Systems, 1994, 66(3): 383-386.
[18]LEE E S, ZHU Q. Fuzzy and evidence reasoning [M]. Hiedelberg: PhysicaV erlag, 1995.
[19]GUAN J W, BELL D A. Approximate reasoning and evidence theory [J]. Info rmation Science, 1997, 96(3): 207-235
[20]HSIAO W H, CHEN S M, LEE C H. A new interpolative reasoning method in s parse rulebased systems [J]. Fuzzy Sets and Systems, 1998, 93(1): 17-22.
[21]CASTRO J L, TRILLAS E, ZURITA J M. Nonmonotic fuzzy reasoning [J]. Fuzzy Sets and Systems, 1998, 94(3): 217-225.
[22]DRIANKOV D, HELLENDOORN H, REINFRANK M. An Introduction to Fuzzy Contro l [M]. New York: SpringerVerlag, 1993.
[23]PAPPIS C P, KARACAPILIDIS N I, A comparative assessment of measures of similarity of fuzzy values [J]. Fuzzy Sets and Systems, 1994, 56(2): 171-174. 
[24]CHANG T C, HASEGAWA K, IBBS C W. The effects of membership functions on fuzzy reasoning [J]. Fuzzy Sets and Systems, 1991, 44(2): 169-186.
[25]CORDóN O, HERRERA F, PEREGRíN A. Searching for basic properties obtai ning robust implication operators in fuzzy control [J]. Fuzzy Sets and Systems , 2000, 111(2): 237-251.
 [26]MELEK W W, GOLDENBERG A A. The development of a robust fuzzy inference mechanism [J]. Int J of Approximate Reasoning 2005, 39(1): 29-47.
[27]ZHANG L, CAI K. Optimal fuzzy reasoning and its robust analysis [J]. Int J Intelligent Systems, 2004, 19(11): 1033-1049.
[28]LI Y, LI D, PEDRYCZ W, WU J. An approach to measure the robustness of f uzzy reasoning [J]. Int J Intelligent Systems, 2005, 20(4): 393-413.
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