Data-driven aerospace engineering: reframing the industry with machine learning
Data science, and machine learning in particular, is rapidly transforming the scientific and
industrial landscapes. The aerospace industry is poised to capitalize on big data and …
industrial landscapes. The aerospace industry is poised to capitalize on big data and …
[BOOK][B] Data-driven science and engineering: Machine learning, dynamical systems, and control
SL Brunton, JN Kutz - 2022 - books.google.com
Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …
A tutorial-based survey on feature selection: Recent advancements on feature selection
A Moslemi - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …
computer vison and machine learning in recent years. Feature selection and feature …
Modal analysis of fluid flows: Applications and outlook
THE field of fluid mechanics involves a range of rich and vibrant problems with complex
dynamics stemming from instabilities, nonlinearities, and turbulence. The analysis of these …
dynamics stemming from instabilities, nonlinearities, and turbulence. The analysis of these …
Data-driven sparse sensor placement for reconstruction: Demonstrating the benefits of exploiting known patterns
Optimal sensor and actuator placement is an important unsolved problem in control theory.
Nearly every downstream control decision is affected by these sensor and actuator …
Nearly every downstream control decision is affected by these sensor and actuator …
Estimation of cavitation velocity fields based on limited pressure data through improved U-shaped neural network
Y Xu, Y Sha, C Wang, Y Wei - Physics of Fluids, 2023 - pubs.aip.org
In marine applications, estimating velocity fields or other states from limited data are
important as it provides a reference for active control. In this work, we propose PVNet …
important as it provides a reference for active control. In this work, we propose PVNet …
[BOOK][B] Data-driven fluid mechanics: combining first principles and machine learning
Data-driven methods have become an essential part of the methodological portfolio of fluid
dynamicists, motivating students and practitioners to gather practical knowledge from a …
dynamicists, motivating students and practitioners to gather practical knowledge from a …
Greedy sensor placement with cost constraints
The problem of optimally placing sensors under a cost constraint arises naturally in the
design of industrial and commercial products, as well as in scientific experiments. We …
design of industrial and commercial products, as well as in scientific experiments. We …
Dynamic mode decomposition for compressive system identification
Dynamic mode decomposition has emerged as a leading technique to identify
spatiotemporal coherent structures from high-dimensional data, benefiting from a strong …
spatiotemporal coherent structures from high-dimensional data, benefiting from a strong …
Bioinspired artificial hair sensors for flight-by-feel of unmanned aerial vehicles: a review
Flight-by-feel is an emerging approach to flight control that uses distributed arrays of
pressure, strain, and flow sensors to guide aircraft. Among these, hair-type flow sensors …
pressure, strain, and flow sensors to guide aircraft. Among these, hair-type flow sensors …