[HTML][HTML] Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer
The use of data-driven methods in fluid mechanics has surged dramatically in recent years
due to their capacity to adapt to the complex and multi-scale nature of turbulent flows, as …
due to their capacity to adapt to the complex and multi-scale nature of turbulent flows, as …
Flow regime classification using various dimensionality reduction methods and AutoML
Accurate identification of flow regimes is paramount in several industries, especially in
chemical and hydrocarbon sectors. This paper describes a comprehensive data-driven …
chemical and hydrocarbon sectors. This paper describes a comprehensive data-driven …
[HTML][HTML] Teaching classical machine learning as a graduate-level course in chemical engineering: An algorithmic approach
KE Pilario - Digital Chemical Engineering, 2024 - Elsevier
The demand for engineering graduates with technical skills in data science, machine
learning (ML), and artificial intelligence (AI) is now growing. Chemical engineering (ChemE) …
learning (ML), and artificial intelligence (AI) is now growing. Chemical engineering (ChemE) …
[PDF][PDF] Digital Chemical Engineering
KE Pilario - 2000 - researchgate.net
The demand for engineering graduates with technical skills in data science, machine
learning (ML), and artificial intelligence (AI) is now growing. Chemical engineering (ChemE) …
learning (ML), and artificial intelligence (AI) is now growing. Chemical engineering (ChemE) …