@misc{Lipnicka_Marta_Topological_2016,
 author={Lipnicka, Marta and Szulc, Katarzyna and Żochowski, Antoni},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2016},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={This paper considers a coupled model described by the domain bounded in R2 and decomposed into two sub-domains Ω and ω in such way that the interior sub-domain ω is surrounded by the exterior sub-domain Ω. In the interior sub-domain the physical phenomenon are described by the linear partial differential equation (PDE), and in the exterior domain the processes are governed by nonlinear PDEs subject to some external function. An example of such a system constitutes a gravity flow around an elastic obstacle. The goal of this paper is to propose the combination of neural network and information given by the topological derivative for solving such difficult problems or at least providing the initial approximation of the solutions. For a fixed number of holes, the differential equation was considered and solved.},
 title={Topological derivative and neural network for inverse problems of coupled models * Introduction},
 type={Text},
 URL={http://www.rcin.org.pl/Content/110600/PDF/RB-2016-38.pdf},
 keywords={Optymalizacja kształtu, Shape optimization, Topological derivative, Artificial neural networks, Pochodna topologiczna, Sztuczne sieci neuronowe},
}