Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering will be highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.
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Dr. Ehsan Momeni currently works as Assistant Professor in the Faculty of Engineering, Lorestan University, Iran. He received his postdoc from University of Tehran, Iran, and his Ph.D. degree, in Civil-Geotechnics, from Universiti Teknologi Malaysia, Malaysia. His areas of research are foundation engineering, reliability analysis, rock mechanics, and applied artificial intelligence.
Dr. Danial Jahed Armaghani is currently working as Research Associate at the School of Civil and Environmental Engineering, University of Technology Sydney (UTS), Australia. He received his postdoc from Amirkabir University of Technology, Tehran, Iran, and his Ph.D. degree, in Civil Geotechnics, from Universiti Teknologi Malaysia, Malaysia. His areas of research are tunneling, rock mechanics, piling technology, blasting environmental issues, applying artificial intelligence, and optimization algorithms in different areas of civil engineering.Dr. Aydin Azizi holds a Ph.D. degreein Mechanical Engineering-Mechatronics, an M.Sc. in Mechatronics, a B.Sc. in Mechanical Engineering-Heat & Fluids and certified as Official Instructor for the Siemens Mechatronic Certification Program (SMSCP). He currently serves as Senior Lecturer at the Oxford Brookes University. His current research focuses on investigating and developing novel techniques to model, control, and optimize complex systems. Dr. Azizi's areas of expertise include control & automation, artificial intelligence, and simulation techniques. Dr. Azizi is Recipient of the National Research Award of Oman for his AI-focused research, DELL EMC's "Envision the Future" competition award in IoT for "Automated Irrigation System", and "Exceptional Talent" recognition by the British Royal Academy of Engineering.
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Etat : Hervorragend. Zustand: Hervorragend | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book. N° de réf. du vendeur 40859957/1
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book. 260 pp. Englisch. N° de réf. du vendeur 9789811987892
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Buch. Etat : Neu. Artificial Intelligence in Mechatronics and Civil Engineering | Bridging the Gap | Ehsan Momeni (u. a.) | Buch | Emerging Trends in Mechatronics | xii | Englisch | 2023 | Springer | EAN 9789811987892 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 125796908
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