Parameter identification for fractional-fractal model of filtration-consolidation dynamics using artificial neural networks

Fìz.-mat. model. ìnf. tehnol. 2021, 32:52-57

Abstract

Artificial neural networks are applied to solve parameters identification problem for one-dimensional fractional-fractal model of filtration consolidation processes in geo-porous media in the conditions of salt transfer. Based on the indicators of the state of the process in a fixed number of observation points, the values of the orders of fractional derivatives with respect to time and space variables were restored. Testing results based on data sets obtained from noised solutions of the direct problem show the adequacy of fractional derivatives orders restoration with at least 25 observation points and noise levels less than 10%.

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