2 citations · 3 across the 3 of their papers we have counts for
3 papers
Hierarchical Higher-Order Dynamic Mode Decomposition for Clustering and Feature Selection
Adrián Corrochano, Giuseppe D'Alessio, Alessandro Parente +1
In this work, a new algorithm based on the application of higher-order dynamic mode decomposition (HODMD) is proposed for feature selection and variables clustering in reacting flo…
Advancing Reacting Flow Simulations with Data-Driven Models
Kamila Zdybał, Giuseppe D'Alessio, Gianmarco Aversano +4
The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems,…
Higher order dynamic mode decomposition to model reacting flows
Adrián Corrochano, Giuseppe D'Alessio, Alessandro Parente +1
In this work, the application of the multi-dimensional higher order dynamic mode decomposition (HODMD) is proposed for the first time to analyse combustion databases. In particular…