Smart proxy modeling: artificial intelligence and machine learning in numerical simulation
"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 wit…
Read More ↓Title Statements
- Full title :Smart proxy modeling : artificial intelligence and machine learning in numerical simulation / Shahab D. Mohaghegh.
Summary
"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 it may be used in real-world cases. Covers replication of highly accurate numerical simulations using artificial intelligence and machine learning. Details application in reservoir simulation and modeling, and computational fluid dynamics. Includes real case studies based on commercially available simulators. 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"--
Read More ↓Edition Statements
- Publication Date:2023.
- Edition:First edition
Publication Statements
- Publisher(s):CRC Press
- Place of Publication:Boca Raton, FL
- Language:eng
- Publication Date:2023.
The Physical Object
- Description:pages cm
Edition Identifiers
- ISBN:9781032151144, 1032151145, 9781032151151, 1032151153
- oclc:on1341399269
- LC Classification:TA342
- Dewey Decimal:620.001/1
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