no code implementations • 18 Dec 2017 • Farshad Harirchi, Doohyun Kim, Omar A. Khalil, Sijia Liu, Paolo Elvati, Angela Violi, Alfred O. Hero
In this paper, we introduce a novel approach for the identification of the influential reactions in chemical reaction networks for combustion applications, using a data-driven sparse-learning technique.
no code implementations • 12 Dec 2017 • Farshad Harirchi, Omar A. Khalil, Sijia Liu, Paolo Elvati, Angela Violi, Alfred O. Hero
In this paper, we propose an optimization-based sparse learning approach to identify the set of most influential reactions in a chemical reaction network.