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Solving initial-boundary value problems for systems of partial differential equations using neural networks and optimization techniques. (English) Zbl 1298.65155
Summary: A general system of the time-dependent partial differential equations containing several arbitrary initial and boundary conditions is considered. A hybrid method based on artificial neural networks, minimization techniques and collocation methods is proposed to determine a related approximate solution in a closed analytical form. The optimal values for the corresponding adjustable parameters are calculated. An accurate approximate solution is obtained, that works well for interior and exterior points of the original domain. Numerical efficiency and accuracy of the hybrid method are investigated by two-test problems including an initial value and a boundary value problem for the two-dimensional biharmonic equation.

MSC:
65M99 Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems
65K10 Numerical optimization and variational techniques
92B20 Neural networks for/in biological studies, artificial life and related topics
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