E.H. Shiguemori, H.F. de Campos Velho, J.D.S. da Silva (2002): Estimation of Initial Condition in Heat Conduction by Neural Network, 4th International Conference on Inverse Problems in Engineering: Theory and Practice ( ICIPE-2002), May 26-31, Angra dos Reis (RJ), Brazil. (submitted).

Abstract: Neural network have emerged as a new technique to solve inverse problems. This approch was used to identify boundary conditions in inverse heat conduction problem [1]. In this paper the neural network technique is used to determine the initial condition in heat conduction. The results are compared with those obtained with standard regularization schemes [2, 3].

[1] J. Krejsa, K.A. Woodbury, J.D. Ratliff, M. Raudensky (1999): Assessment of strategies and potential for neural networks in the inverse heat conduction problem, Inverse Problems in Engineering, 7 (3), 197-213.

[2] W.B. Muniz, F.M. Ramos, H.F. Campos Velho (2000): Entropy- and Tikhonov-based regularization techniques applied to the backwards heat equation, Computers & Mathematics with Applications, 40 (8/9), 1071-1084.

[3] W.B. Muniz, H.F. Campos Velho, F.M. Ramos (1999): A comparison of some inverse methods for estimating the initial condition of the heat equation, Journal of Computational and Applied Mathematics, 103 (1), 145-163.