Enhancing computational fluid dynamics with machine learning
https://doi.org/10.1038/s43588-022-00264-7
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https://doi.org/10.1038/s43588-022-00264-7
We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding ...
https://doi.org/10.1142/s0218271810017160
https://doi.org/10.1007/s11837-020-04155-y
https://doi.org/10.1007/978-1-4615-7566-5
10.3389/fphy.2022.1072691
Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...
https://doi.org/10.1038/s41467-019-09103-2
PMC: 6403242
https://doi.org/10.1016/j.apenergy.2021.116452
https://doi.org/10.1038/s41578-021-00340-w
Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that ...
https://doi.org/10.58248/pn633
The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means av...
https://doi.org/10.1080/21693277.2016.1192517
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering...
https://doi.org/10.1017/9781009089517.019
https://doi.org/10.1557/mrc.2019.32
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
https://doi.org/10.1016/j.gsf.2015.07.003
With the growth and wide variety of available data, advanced processing, and affordable data storage, machine learning is witnessing great attention in finding optimized solutions in various fields. Machine learning techniques are currently...
https://doi.org/10.1109/hpcs48598.2019.9188224
During the past few years, research in applying machine learning (ML) to design efficient, effective, and robust metaheuristics has become increasingly popular. Many of those machine learning-supported metaheuristics have generated high-qua...
https://doi.org/10.1145/3459664
https://doi.org/10.1016/j.inffus.2019.12.001
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...
https://doi.org/10.1021/acssensors.0c01424
Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicle...
https://doi.org/10.1016/j.egyai.2021.100128
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...
https://doi.org/10.1146/annurev-fluid-010719-060214
We argue that Artificial Intelligence (AI) will, in the very near future, have a profound impact on the conduct of strategy and will be disruptive of existing power balances. To do so, we review the psychological foundations of strategy and...
https://doi.org/10.1080/01402390.2015.1088838