16-17 May 2019 • Sofia, Bulgaria

Submission: 1 February 2019 • Notification: 1 March 2019 • Final Version: 1 April 2019

Issue:Fuzzy justification of heuristic methods in inverse problems and in numerical computations, with applications to detection of business cycles from fuzzy and intuitionistic fuzzy data

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Title of paper: Fuzzy justification of heuristic methods in inverse problems and in numerical computations, with applications to detection of business cycles from fuzzy and intuitionistic fuzzy data
Author(s):
Vladik Kreinovich
Department of Computer Science University of Texas at El Paso, El Paso, TX 79968
Hung Nguyen
Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM 88003, USA
Berlin Wu
Department of Applied Mathematics National Chengchi University, Taipei, Taiwan, China
Krassimir Atanassov
CLBME - Bulgarian Academy of Sciences, Sofia-1113, P.O.Box 12, Bulgaria
Presented at: 2nd ICIFS, Sofia, 3—4 Oct. 1998
Published in: Conference proceedings, "Notes on IFS", Volume 4 (1998) Number 2, pages 47—56
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References:
  1. K. Atanassov, "Intuitionistic fuzzy sets", Fuzzy sets and Systems, Vol. 20 (1986), No. 1, 87-96.
  2. G. Klir and B. Yuan, Fuzzy sets and fuzzy logic: theory and applications. Prentice Hall, Upper Saddle River, NJ, 1995.
  3. V. Kreinovich, C.-C. Chang, L. Reznik, and G. N. Solopchenko, "Inverse problem-s: fuzzy representation of uncertainty generates a regularization", In: Proceedings of NAFIPS'92: North American Fuzzy Information Processing Society Conference, Puerto Vallarta, Mexico, December 15-17, 1992, NASA Johnson Space Center, Hous¬ton, TX, 1992, pp. 418-426.
  4. H. T. Nguyen, V. Kreinovich, and B. Bouchon-Meunier, "Soft Computing Explains Heuristic Numerical Methods in Data Processing and in Logic Programming", Working Notes of the AAAI Symposium on Frontiers in Soft Computing and Decision Systems, Boston, MA, November 8-10, 1997, pp. 40-45.
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  8. N. A. Zheludeva, V. Kreinovich, and G. N. Solopchenko, Applicability criteria and accuracy estimates for heuristic methods of solving inverse problems, Leningrad Center of New Technology "Informatika", Technical Report, Leningrad, 1989 (in Russian).
  9. B. Wu and S.-L. Hung, "Pattern recognition for nonlinear time series: with examples for distinguishing ARCH and bilinear models", Fuzzy Sets and Systems, 1998 (to appear).
  10. B. Wu and M.-C. Liaw, Application of fuzzy time series analysis to change period detection, Technical Report, Department of Mathematical Sciences and Statistics, National Chengchi University, Taipei, Taiwan, China, 1998.
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