Abstract Computational Fluid Dynamics (CFD) and Machine Learning (ML) approaches are
implemented and compared in an industrial Chemical Vapor Deposition process for the …

In this research article, we introduce a numerical investigation through artificial neural
networks (ANN) integrated with evolutionary algorithm especially Archimedean optimization …

A data-driven framework is presented, that enables the prediction of quantities, either
observations or parameters, given sufficient partial data. The framework is illustrated via a …

This study introduces a machine learning framework tailored to large-scale industrial
processes characterized by a plethora of numerical and categorical inputs. The framework …

High indium-content group-III nitrides are of interest to further expand upon our ability to
produce highly efficient optical emitters at longer visible/IR wavelengths or to broaden …

This review explores the oxidation behavior of titanium carbide (TiC) and titanium nitride
(TiN) coatings deposited by chemical vapor deposition, with a focus ontheirindustrial …

This work introduces a comprehensive approach utilizing data-driven methods to elucidate
the deposition process regimes in Chemical Vapor Deposition (CVD) reactors and the …

This work introduces a comprehensive approach utilizing data-driven methods to elucidate
the deposition process regimes in Chemical Vapor Deposition (CVD) reactors and the …

Highly indium-rich group-III nitrides are attracting attention for advancing our capacity to
create highly effective optical emitters at extended visible/IR wavelengths or for enhancing …

Important variables of processes are, in many occasions, categorical, ie names or labels
representing, eg categories of inputs, or types of reactors or a sequence of steps. In this …