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Artificial Intelligence for Science and Engineering Applications

Shahab D. Mohaghegh
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artificial intelligence in scientific modelling
Author_Shahab D. Mohaghegh
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Category1=Non-Fiction
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Category=TBD
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computational modelling
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engineering optimisation
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physical systems analysis
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research methodology
scientific computing
softlaunch
statistical inference methods

Product details

  • ISBN 9781032439044
  • Weight: 360g
  • Dimensions: 156 x 234mm
  • Publication Date: 01 Apr 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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Description

Artificial Intelligence (AI) is defined as the simulation of human intelligence through the mimicking of the human brain for analysis, modeling, and decision‑making. Science and engineering problem solving requires modeling of physical phenomena, and humans approach the solution of scientific and engineering problems differently from other problems. Artificial Intelligence for Science and Engineering Applications addresses the unique differences in how AI should be developed and used in science and engineering. Through the inclusion of definitions and detailed examples, this book describes the actual and realistic requirements as well as what characteristics must be avoided for correct and successful science and engineering applications of AI.

This book:

  • Offers a brief history of AI and covers science and engineering applications
  • Explores the modeling of physical phenomena using AI
  • Discusses explainable AI (XAI) applications
  • Covers the ethics of AI in science and engineering
  • Features real‑world case studies

Offering a probing view into the unique nature of scientific and engineering exploration, this book will be of interest to generalists and experts looking to expand their understanding of how AI can better tackle and advance technology and developments in scientific and engineering disciplines.
About Shahab D. Mohaghegh

Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Machine Learning in the Exploration and Production industry, is a Professor of Petroleum and Natural Gas Engineering at West Virginia University, USA, and the president and CEO of Intelligent Solutions, Inc. (ISI). He is the director of WVU-LEADS (Laboratory for Engineering Application of Data Science).

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