Digital twin paradigm: A systematic literature review

C Semeraro, M Lezoche, H Panetto, M Dassisti - Computers in Industry, 2021 - Elsevier
Manufacturing enterprises are facing the need to align themselves to the new information
technologies (IT) and respond to the new challenges of variable market demand. One of the …

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

R Yondo, E Andrés, E Valero - Progress in aerospace sciences, 2018 - Elsevier
Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …

One in two cancer patients is significantly distressed: prevalence and indicators of distress

A Mehnert, TJ Hartung, M Friedrich, S Vehling… - Psycho …, 2018 - Wiley Online Library
Objective Psychological distress is common in cancer patients, and awareness of its
indicators is essential. We aimed to assess the prevalence of psychological distress and to …

Prediction of the landslide susceptibility: Which algorithm, which precision?

HR Pourghasemi, O Rahmati - Catena, 2018 - Elsevier
Coupling machine learning algorithms with spatial analytical techniques for landslide
susceptibility modeling is a worth considering issue. So, the current research intend to …

[PDF][PDF] Applications of artificial intelligence in machine learning: review and prospect

S Das, A Dey, A Pal, N Roy - International Journal of Computer …, 2015 - Citeseer
Machine learning is one of the most exciting recent technologies in Artificial Intelligence.
Learning algorithms in many applications that's we make use of daily. Every time a web …

Machine learning models for predicting ship main engine Fuel Oil Consumption: A comparative study

C Gkerekos, I Lazakis, G Theotokatos - Ocean Engineering, 2019 - Elsevier
Abstract As Fuel Oil Consumption (FOC) constitutes over 25% of a vessel's overall operating
cost, its accurate forecasting, and the reliable prediction of the relevant ship operating …

[BOOK][B] Statistical learning from a regression perspective

RA Berk - 2008 - Springer
This chapter launches a more detailed examination of statistical learning within a regression
framework. Once again, the focus is on conditional distributions. How does the conditional …

[PDF][PDF] Shrink globally, act locally: Sparse Bayesian regularization and prediction

NG Polson, JG Scott - Bayesian statistics, 2010 - Citeseer
We use Lévy processes to generate joint prior distributions for a location parameter β=(β1,...,
βp) as p grows large. This approach, which generalizes normal scale-mixture priors to an …

An effective approach for software project effort and duration estimation with machine learning algorithms

P Pospieszny, B Czarnacka-Chrobot… - Journal of Systems and …, 2018 - Elsevier
During the last two decades, there has been substantial research performed in the field of
software estimation using machine learning algorithms that aimed to tackle deficiencies of …

Machine learning in catalysis, from proposal to practicing

W Yang, TT Fidelis, WH Sun - ACS omega, 2019 - ACS Publications
Recently, machine learning (ML) methods have gained popularity and have performed as
powerfully predictive tools in various areas of academic and industrious activities. In …