New Book "Smart Proxy Modeling: Artificial Intelligence & Machine Learning in Numerical Simulation" was just published.
Numerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. Smart Proxy Models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes, thereby simplifying the use of complex numerical simulations, which can otherwise take tens of hours. This book focuses on Smart Proxy Modeling and provides readers with all the essential details on how to develop Smart Proxy Models using Artificial Intelligence and Machine Learning, as well as how they may be used in real-world cases.
Smart Proxy Modeling is ideal for petroleum, chemical, environmental, and mechanical engineers, as well as statisticians and others working with applications of data-driven analytics.
Smart Proxy Modeling | Artificial Intelligence and Machine Learning in
| Taylor & Francis |
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| Smart Proxy Modeling | Artificial Intelligence and Machine Learning in |
| Numerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. Smart Proxy Models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes, thereby simplifying the use of complex numerical simulations, which can otherwise take tens of hours. |
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Shahab D. Mohaghegh
Professor; Petroleum & Natural Gas Engineering
Director of (WVU-LEADS)
West Virginia University Laboratory for Engineering Application of Data Science
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