Abstract
The problem of solving systems of interval linear equations with use of AI based approaches is studied in this paper. First, this problem is viewed in terms of an optimization task. A cost function with interval variables is defined. Next, for a given system of equations, instead of the exact algebraic solution its approximation is determined by minimizing the cost function. This is done by use of two different approaches: the NN based approach and the GA based one. A number of numerical evaluations are provided in order to verify the proposed techniques. The results are compared, discussed and some final conclusions are drawn.
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Viet, N.H., Kleiber, M. (2006). AI Methods in Solving Systems of Interval Linear Equations. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_17
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DOI: https://doi.org/10.1007/11785231_17
Publisher Name: Springer, Berlin, Heidelberg
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