Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM): Recent submissions
Now showing items 295-301 of 1234
-
Article dans une revue avec comité de lecture; ; ;
CHINESTA SORIA, Francisco (Elsevier Masson, 2020)
The present work aims at analyzing issues related to the data manifold dimensionality. The interest of the study is twofold: (i) first, when too many measurable variables are considered, manifold learning is expected to ... -
Article dans une revue avec comité de lecture; ; ; ;GHNATIOS, Chady; CHINESTA SORIA, Francisco (MDPI AG, 2021)
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric solutions for electromagnetic fields in synchronous machines. Specifically, the intrusive version of the Proper Generalized ...
-
Article dans une revue avec comité de lecture; ; ;CHINESTA SORIA, Francisco (Hindawi Limited, 2019)
no abstract
-
Article dans une revue avec comité de lectureCHINESTA SORIA, Francisco (Springer Science and Business Media LLC, 2021)
No abstract
-
Article dans une revue avec comité de lecture; ; ; ; ;CHINESTA SORIA, Francisco (Wiley-VCH Verlag, 2020)
The purpose of this paper is to combine a classical 1D twin-screw extrusion model with machine learning techniques to obtain accurate predictions of a complex system despite few data. Systems involving reactive polyethylene ...
-
Article dans une revue avec comité de lecture; ; ;GHNATIOS, Chady; CHINESTA SORIA, Francisco (Springer Science and Business Media LLC, 2020)
Non-intrusive approaches for the construction of computational vademecums face different challenges, especially when a parameter variation affects the physics of the problem considerably. In these situations, classical ...
-
Article dans une revue avec comité de lecture; ; ; ; ; ; ;CHINESTA SORIA, Francisco (MDPI, 2021)
We are interested in evaluating the state of drivers to determine whether they are attentive to the road or not by using motion sensor data collected from car driving experiments. That is, our goal is to design a predictive ...
