Abstract
A permutation (s 0 , s 1, ⋯, s N −1) of symbols 0,1, ,⋯ , N − 1 is called “good” if the set (t 0 , t 1,⋯, t N −1) formed by the rule t i= i + s i (mod N),i = 0,1,⋯, N −1, is also a permutation. The author proposes the fast simulation method. Its implementation on the SCIT-4 multiprocessor computer complex makes it possible to evaluate the number of “good” permutations for N ≤ 305 with relative accuracy no greater than 1%. The number of “good” permutations is estimated for N 25, 35, ⋯, 305.
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L. A. Zadeh, “Fuzzy sets,” Information and Control, 8, No. 3, 338–353 (1965).
K. S. Leung and M. H. Wong, “Fuzzy concepts in an object oriented expert system shell,” International Journal of Intelligent Systems, 7, No. 2, 171–192 (1992).
F. Berzal, N. Marin, O. Pons, and M. A. Vila, “Managing fuzziness on conventional object-oriented platforms,” International Journal of Intelligent Systems, 22, No. 7, 781–803 (2007).
N. Marin, O. Pons, and M. A. Vila, “Fuzzy types: A new concept of type for managing vague structures,” International Journal of Intelligent Systems, 15, No. 11, 1061–1085 (2000).
T. D. Ndousse, “Intelligent systems modeling with reusable fuzzy objects,” International Journal of Intelligent Systems, 12, No. 2, 137–152 (1997).
D. O. Terletskyi and A. I. Provotar, “Object-oriented dynamic networks,” in: G. Setlak and K. Markov (eds.), Computational Models for Business and Engineering Domains, ITHEA, Rzeszow (2014).
D. A. Terletskyi and A. I. Provotar, “Fuzzy object-oriented dynamic networks. I,” Cybernetics and Systems Analysis, 51, No. 1, 34–40 (2015).
Z. M. Ma, W. J. Zhang, and W. Y. Ma, “Extending object-oriented databases for fuzzy information modeling,” Journal Information Systems — Databases: Creation, Management and Utilization, 29, No. 5, 421–435 (2003).
F. Zhang and Z. M. Ma, “Construction of fuzzy ontologies from fuzzy UML models,” International Journal of Computational Intelligence Systems, 6, No. 3, 442–472 (2013).
G. Bordogna, G. Pasi, and D. Lucarella, “A fuzzy object-oriented data model for managing vague and uncertain information,” International Journal of Intelligent Systems, 14, No. 7, 623–651 (1999).
B. Stroustrup, The C++ Programming Language: Fourth Edition, Addison-Wesley, Upper Saddle River (N.J.) (2013).
I. Graham and P. L. Jones, “A theory of fuzzy frames: Part 1,” Bulletin for Studies and Exchanges on Fuzziness and its Applications, No. 31, 109–132 (1987).
I. Graham and P. L. Jones, “A theory of fuzzy frames: Part 2,” Bulletin for Studies and Exchanges on Fuzziness and its Applications, No. 32, 120–135 (1987).
R. J. Brachman and H. J. Levesque, Knowledge Representation and Reasoning, Morgan Kaufmann, San Francisco (2004).
M. Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems, 2nd Edition, Addison-Wesley, Harlow (2004).
D. O. Terletskyi and O. I. Provotar, “Mathematical foundations for designing and development of intelligent systems of information analysis,” Problems in Programming, Nos. 2–3, 233–241 (2014).
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Translated from Kibernetika i Sistemnyi Analiz, No. 1, January–February, 2016, pp. 57–63.
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Kuznetsov, N.Y. Using the Monte Carlo Method for Fast Simulation of the Number of “Good” Permutations on the SCIT-4 Multiprocessor Computer Complex. Cybern Syst Anal 52, 52–57 (2016). https://doi.org/10.1007/s10559-016-9799-0
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DOI: https://doi.org/10.1007/s10559-016-9799-0