DOI QR코드

DOI QR Code

APPROXIMATE SOLUTIONS TO ONE-DIMENSIONAL BACKWARD HEAT CONDUCTION PROBLEM USING LEAST SQUARES SUPPORT VECTOR MACHINES

  • Wu, Ziku (Department of Mathematics Qingdao Agricultural University) ;
  • Li, Fule (Department of Mathematics Qingdao Agricultural University) ;
  • Kwak, Do Young (Department of Mathematical Sciences Korea Advanced Institute of Science and Technology)
  • 투고 : 2016.01.13
  • 심사 : 2016.10.13
  • 발행 : 2016.11.15

초록

This article deals with one-dimension backward heat conduction problem (BHCP). A new approach based on least squares support vector machines (LS-SVM) is proposed for obtaining their approximate solutions. The approximate solution is presented in closed form by means of LS-SVM, whose parameters are adjusted to minimize an appropriate error function. The approximate solution consists of two parts. The first part is a known function that satisfies initial and boundary conditions. The other is a product of two terms. One term is known function which has zero boundary and initial conditions, another term is unknown which is related to kernel functions. This method has been successfully tested on practical examples and has yielded higher accuracy and stable solutions.

키워드

참고문헌

  1. O. M. Alifanov, Inverse Hear Transfer Problems. International series in heat and mass transfer, Spingger-Verlag, 1994.
  2. Ghosh, D. K. Pratihar, B. Maiti, and P. K. Das, Inverse estimation of location of internal heat source in conduction, Inverse problem in science and engineering 19 (2011), no. 3, 337-361. https://doi.org/10.1080/17415977.2011.551876
  3. X. T. Xiong, X. H. Liu, Y. M. Yan, and H. B. Guo, A numerical method for identifying heat transfer coefficient, Applied Mathematical Modelling 34 (2010), 1930-1938. https://doi.org/10.1016/j.apm.2009.10.010
  4. C. W. Chang and C. S. Liu, A backward group preserving scheme for multi-dimensional backward heat conduction problems, CMES, Tech Science Press 59 (2010), no. 3, 239-274.
  5. D. Colton, The approximation of solutions to the backwards heat equation in a nonhomogeneous medium. J. Math. Anal. Appl. 72 (1979), 419-429.
  6. N. S. Mera, L. Elliott, D. B. Ingham, and D. Lesnic, An iterative boundary element for solving one-dimensional backward heat conduction problem, Int. J. Heat Mass Transfer. 44 (2001), 1937-1946. https://doi.org/10.1016/S0017-9310(00)00235-0
  7. I. E. Lagaris, A. Likas, and D. I. Fotiadis, Artificial neural networks for solving ordinary and partial differential equations, IEEE Trans. Neural Networks 9 (1998), no. 5, 987-1000. https://doi.org/10.1109/72.712178
  8. I. E. Lagaris, A. Likas, and D. G. Papageorgio, Neural-network methods for boundary value problems with irregular boundaries, IEEE Trans. Neural Networks 11 no. 5 (2000), 1041-1049. https://doi.org/10.1109/72.870037
  9. M. Baymani, A. Kerayechian, and S. Effati, Artificial neural networks approach for solving Stokes problem, Applied Mathematics 2010, no. 1, 288-292.
  10. H. Alli, A. Ucar, and Y. Demir, The solutions of vibration control problems using artificial neural networks, Journal of the Franklin Institute 340 (2003), 307-325. https://doi.org/10.1016/S0016-0032(03)00036-X
  11. V. N. Vapnik, The nature of statistical learning theory, New York, Springer-Verlag, 1995.
  12. J. A. K. Suykens and J. Vandewalle, Least squares support vector machine classifiers, Neural Process Letter 9 (1999), no. 3, 293-300. https://doi.org/10.1023/A:1018628609742
  13. J. A. K. Suykens, T. V. Gestel, J. De Brabanter, B. De Moor, and J. Vandewalle, Least squares support vector machines, Singapore, World Scientific, 2002.
  14. S. Mehrkanoon and J. A. K. Suykens, LS-SVM approximate solution to linear time varying descriptor systems, Automatica 48 (2012), no. 10, 2502-2511. https://doi.org/10.1016/j.automatica.2012.06.095
  15. S. Mehrkanoon, T. Falck, and J. A. K. Suykens, Approximate solution to ordinary differential equations using least squares support vector machines, IEEE Transactions on Neural Networks and Learning Systems 23 (2012), no. 9, 1356-1367. https://doi.org/10.1109/TNNLS.2012.2202126
  16. S. Mehrkanoon, S. Mehrkanoon, and J. A. K. Suykens, Parameter estimation of delay differential equations: An integration-free LS-SVM approach, Commun. Nonlinear Sci. Numer. Simulat. 19 (2014), 830-841. https://doi.org/10.1016/j.cnsns.2013.07.024