On interval fuzzy negations

There exist infinitely many ways to extend the classical propositional connectives to the set [0,1], preserving their behaviors in the extremes 0 and 1 exactly as in the classical logic. However, it is a consensus that this issue is not sufficient, and, therefore, these extensions must also preserve some minimal logical properties of the classical connectives. The notions of t-norms, t-conorms, fuzzy negations and fuzzy implications taking these considerations into account. In previous works, the author, joint with other colleagues, generalizes these notions to the set U={[a,b]|[email protected][email protected][email protected]?1}, providing canonical constructions to obtain, for example, interval t-norms that are the best interval representations of t-norms. In this paper, we consider the notion of interval fuzzy negation and generalize, in a natural way, several notions related with fuzzy negations, such as the ones of equilibrium point and negation-preserving automorphism. We show that the main properties of these notions are preserved in those generalizations.

[1]  Chris Cornelis,et al.  ON THE PROPERTIES OF A GENERALIZED CLASS OF T-NORMS IN INTERVAL-VALUED FUZZY LOGICS , 2006 .

[2]  Witold Pedrycz,et al.  An alternative characterization of fuzzy complement functional , 2003, Soft Comput..

[3]  E. Walter,et al.  Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics , 2001 .

[4]  I. Turksen Interval valued fuzzy sets based on normal forms , 1986 .

[5]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[6]  R. Callejas Bedregal,et al.  Intervals as Domain Constructor , 2001 .

[7]  Samson Abramsky,et al.  Handbook of logic in computer science. , 1992 .

[8]  Ramon E. Moore,et al.  Interval analysis and fuzzy set theory , 2003, Fuzzy Sets Syst..

[9]  V. Kreinovich,et al.  Intervals (pairs of fuzzy values), triples, etc.: can we thus get an arbitrary ordering? , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[10]  H. Carter Fuzzy Sets and Systems — Theory and Applications , 1982 .

[11]  Glad Deschrijver,et al.  A representation of t-norms in interval-valued L-fuzzy set theory , 2008, Fuzzy Sets Syst..

[12]  Benjamín R. C. Bedregal,et al.  T-Normas, T-Conormas, Complementos e Implicações Intervalares , 2006 .

[13]  M. H. van Emden,et al.  Interval arithmetic: From principles to implementation , 2001, JACM.

[14]  Vladik Kreinovich,et al.  Beyond [0,1] to Intervals and Further: Do We Need All New Fuzzy Values? , 1999 .

[15]  Madan M. Gupta,et al.  Fuzzy automata and decision processes , 1977 .

[16]  Benjamín R. C. Bedregal,et al.  A Quasi-Metric Topology Compatible with Inclusion Monotonicity on Interval Space , 1997, Reliab. Comput..

[17]  Ivor Grattan-Guinness,et al.  Fuzzy Membership Mapped onto Intervals and Many-Valued Quantities , 1976, Math. Log. Q..

[18]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[19]  János Fodor,et al.  A new look at fuzzy connectives , 1993 .

[20]  Elena Castiñeira,et al.  Self-Contradiction and Contradiction between Two Atanassov's Intuitionistic Fuzzy Sets , 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[21]  B. Bedregal,et al.  Analyzing Properties of Fuzzy Implications Obtained via the Interval Constructor , 2006, 12th GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics (SCAN 2006).

[22]  Chris Cornelis,et al.  On the representation of intuitionistic fuzzy t-norms and t-conorms , 2004, IEEE Transactions on Fuzzy Systems.

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

[24]  Francesc Esteva,et al.  Review of Triangular norms by E. P. Klement, R. Mesiar and E. Pap. Kluwer Academic Publishers , 2003 .

[25]  S. Ovchinnikov General negations in fuzzy set theory , 1983 .

[26]  M. Sugeno FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .

[27]  R. B. Kearfott Rigorous Global Search: Continuous Problems , 1996 .

[28]  Dana S. Scott,et al.  Outline of a Mathematical Theory of Computation , 1970 .

[29]  Humberto Bustince,et al.  Automorphisms, negations and implication operators , 2003, Fuzzy Sets Syst..

[30]  Benjamín R. C. Bedregal,et al.  Formal Aspects of Correctness and Optimality of Interval Computations , 2006, Formal Aspects of Computing.

[31]  R. Lowen On fuzzy complements , 1977 .

[32]  Mirko Navara,et al.  A survey on different triangular norm-based fuzzy logics , 1999, Fuzzy Sets Syst..

[33]  Benjamín R. C. Bedregal,et al.  Interval Valued QL-Implications , 2007, WoLLIC.

[34]  Renata Reiser,et al.  Interval Valued R-Implications and Automorphisms , 2007 .

[35]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[36]  Hung T. Nguyen,et al.  A First Course in Fuzzy Logic , 1996 .

[37]  Radko Mesiar,et al.  Triangular Norms , 2000, Trends in Logic.

[38]  J. Montero,et al.  A Survey of Interval‐Valued Fuzzy Sets , 2008 .

[39]  Didier Dubois,et al.  Random sets and fuzzy interval analysis , 1991 .

[40]  G. Klir,et al.  ON MEASURES OF FUZZINESS AND FUZZY COMPLEMENTS , 1982 .

[41]  E. Walker,et al.  Some comments on interval valued fuzzy sets , 1996 .

[42]  Benjamín R. C. Bedregal,et al.  On interval fuzzy S-implications , 2010, Inf. Sci..

[43]  K. Jahn Intervall‐wertige Mengen , 1975 .

[44]  Benjamín R. C. Bedregal,et al.  The best interval representations of t-norms and automorphisms , 2006, Fuzzy Sets Syst..

[45]  Ramon E. Moore Methods and applications of interval analysis , 1979, SIAM studies in applied mathematics.

[46]  Ramon E. Moore Interval arithmetic and automatic error analysis in digital computing , 1963 .

[47]  Benjamín R. C. Bedregal,et al.  Interval Valued Versions of T-Conorms, Fuzzy Negations and Fuzzy Implications , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[48]  Benjamín R. C. Bedregal,et al.  Interval t-norms as Interval Representations of t-norms , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[49]  Renata Reiser,et al.  Interval Valued D-Implications , 2009 .

[50]  Vladik Kreinovich,et al.  Handbook of Granular Computing , 2008 .

[51]  Eunjin Kim,et al.  Characterization of Interval Fuzzy Logic Systems of Connectives by Group Transformations , 2004, Reliab. Comput..

[52]  Frank Mueller,et al.  Preface , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[53]  Alex M. Andrew,et al.  Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics , 2002 .

[54]  E. Trillas Sobre funciones de negación en la teoría de conjuntos difusos. , 1979 .

[55]  Mirko Navara,et al.  Characterization of Measures Based on Strict Triangular Norms , 1999 .

[56]  M. Gorzałczany A method for inference in approximate reasoning based on interval-valued fuzzy sets , 1987 .

[57]  Michal Baczynski,et al.  Fuzzy Implications , 2008, Studies in Fuzziness and Soft Computing.

[58]  George J. Klir,et al.  Fuzzy sets and fuzzy logic , 1995 .

[59]  Benjamín R. C. Bedregal,et al.  The Best Interval Representation of Fuzzy S-Implications and Automorphisms , 2007, 2007 IEEE International Fuzzy Systems Conference.

[60]  Renata Reiser,et al.  Power Flow with Load Uncertainty , 2004 .

[61]  George Bojadziev,et al.  Fuzzy Sets, Fuzzy Logic, Applications , 1996, Advances in Fuzzy Systems - Applications and Theory.

[62]  E. Walker,et al.  Algebraic Aspects of Fuzzy Sets and Fuzzy Logic , 1998 .

[63]  Abbas Edalat,et al.  A Domain-Theoretic Approach to Computability on the Real Line , 1999, Theor. Comput. Sci..

[64]  Bernard De Baets,et al.  Negation and affirmation: the role of involutive negators , 2007, Soft Comput..