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Tytuł artykułu

A Sign Function Approach to Solve Algebraically Interval System of Linear Equations for Nonnegative Solutions

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper deals with solving interval system of linear equations. The problem is to find a nonnegative algebraic solution. Based on sign function approach and using interval center and radius arithmetic operations, we propose an algorithm for computation of an algebraic interval solution vector. We also discuss fundamental properties of this solution vector, such as existence and uniqueness. Further, the nonnegative solution algorithm has been extended to other signrestricted approach. Numerical examples of interval system of linear equations show efficiency of the algorithms presented.
Wydawca
Rocznik
Strony
13--31
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
  • Department of Mathematics, National Institute of Technology, Rourkela Odisha, India
autor
  • Department of Applied Mathematics, Faculty of Mathematics and Physics, Charles University, Malostranské nám. 25, 11800 Prague, Czech Republic
autor
  • Department of Mathematics, National Institute of Technology, Rourkela Odisha, India
Bibliografia
  • [1] Alefeld G, Herzberger J. Introduction to Interval Computation. Academic Press, London, 2012. ISBN:9780120498208, 9780080916361.
  • [2] Moore RE, Kearfott RB, Cloud MJ. Introduction to Interval Analysis. SIAM Publications, Philadelphia, PA, 2009. ISBN:0898716691, 9780898716696.
  • [3] Rohn J. Systems of linear interval equations. Linear Algebra and its Applications, 1989;126:39–78.
  • [4] Neumaier A. Linear interval equations. In: Interval Mathematics 1985, pp. 109–120. Springer, 1986.
  • [5] Neumaier A. Interval Methods for Systems of Equations. Cambridge University Press, Cambridge, 1990. ISBN-13:9780521331968, 10:052133196X.
  • [6] Ning S, Kearfott RB. A comparison of some methods for solving linear interval equations. SIAM Journal on Numerical Analysis, 1997;34(4):1289–1305. doi:10.1137/S0036142994270995.
  • [7] Hladík M. New operator and method for solving real preconditioned interval linear equations. SIAM J. Numer. Anal., 2014;52(1):194–206. doi:10.1137/130914358.
  • [8] Hladík M, Horáček J. A shaving method for interval linear systems of equations. In: Wyrzykowski et al R (ed.), Parallel Processing and Applied Mathematics, volume 8385 of LNCS, pp. 573–581. Springer, 2014. doi:10.1007/978-3-642-55195-6_54.
  • [9] Rahgooy T, Yazdi HS, Monsefi R. Fuzzy Complex System of Linear Equations Applied to Circuit Analysis. International Journal of Computer and Electrical Engineering, 2009;1(5):535. doi:10.7763/IJCEE.2009.V1.82.
  • [10] Das S, Chakraverty S. Numerical Solution of Interval and Fuzzy System of Linear Equations. Applications and Applied Mathematics, 2012;7(1):334–356. ISSN: 1932-9466.
  • [11] Qiu Z, Elishakoff I. Antioptimization of structures with large uncertain-but-non-random parameters via interval analysis. Computer methods in applied mechanics and engineering, 1998;152(3):361–372.
  • [12] McWilliam S. Anti-optimisation of uncertain structures using interval analysis. Computers & Structures, 2001;79(4):421–430. doi:10.1016/S0045-7949(00)00143-7.
  • [13] Behera D, Chakraverty S. Fuzzy analysis of structures with imprecisely defined properties. Computer Modeling in Engineering and Sciences, 2013;96(5):317–337.
  • [14] Popova ED. Parametric interval linear solver. Numerical Algorithms, 2004;37(1-4):345–356. doi:10.1023/B:NUMA.0000049480.57066.fa.
  • [15] Popova E, Krämer W. Inner and outer bounds for the solution set of parametric linear systems. Journal of Computational and Applied Mathematics, 2007;199(2):310–316. URL http://dx.doi.org/10.1016/j.cam.2005.08.048.
  • [16] Popova E, Krämer W. Visualizing parametric solution sets. BIT Numerical Mathematics, 2008;48(1):95–115. doi:10.1007/s10543-007-0159-3.
  • [17] Hladík M. Enclosures for the solution set of parametric interval linear systems. International Journal of Applied Mathematics and Computer Science, 2012;22(3):561–574. doi:10.2478/v10006-012-0043-4.
  • [18] Dehghan M, Hashemi B, Ghatee M. Computational methods for solving fully fuzzy linear systems. Applied Mathematics and Computation, 2006;179(1):328–343. URL http://dx.doi.org/10.1016/j.amc.2005.11.124.
  • [19] Dubois D, Prade H. Fuzzy Sets and Systems: Theory and Applications, volume 144. Academic Press, 1980. ISBN:0122227506, 9780122227509.
  • [20] Behera D, Chakraverty S. New approach to solve fully fuzzy system of linear equations using single and double parametric form of fuzzy numbers. Sadhana, 2015;40(1):35–49. doi:10.1007/s12046-014-0295-9.
  • [21] Shary SP. A new technique in systems analysis under interval uncertainty and ambiguity. Reliab. Comput., 2002;8(5):321–418. doi:10.1023/A:1020505620702.
  • [22] Lakeyev AV. On the computational complexity of the solution of linear systems with moduli. Reliab. Comput., 1996;2(2):125–131. doi:10.1007/BF02425914.
  • [23] Allahviranloo T, Ghanbari M. A New Approach to Obtain Algebraic Solution of Interval Linear Systems. Soft Comput., 2012;16(1):121–133. doi:10.1007/s00500-011-0739-7.
  • [24] Behera D, Chakraverty S, Hladík M. Algebraic solution of an interval system of linear equations with an application in static responses of structures with interval forces, 2015. Submitted.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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