Artificial Intelligence in Mechatronics and Civil Engineering
Springer Verlag, Singapore
978-981-19-8792-2 (ISBN)
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.
1. Optical resistance switch for optical sensing.- 2. Empirical, statistical, and machine learning techniques for predicting surface settlement induced by Tunnelling.- 3. A review on the feasibility of Artificial Intelligence in Mechatronics.- 4. Feasibility of artificial intelligence techniques in rock characterization.- 5. A review on the application of soft computing techniques in Foundation Engineering
Erscheinungsdatum | 17.02.2024 |
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Reihe/Serie | Emerging Trends in Mechatronics |
Zusatzinfo | 89 Illustrations, color; 23 Illustrations, black and white; XII, 247 p. 112 illus., 89 illus. in color. |
Verlagsort | Singapore |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Naturwissenschaften ► Geowissenschaften ► Meteorologie / Klimatologie | |
Technik ► Bauwesen | |
Schlagworte | Artificial Neural Networks (ANN) • Blast-induced back-break • Concrete Structures • foundation engineering • Meta-heuristic optimization algorithms • Nanostructure optical sensor • Piling capacity • Rock characterization • Smart mechatronic systems • Soft Computing Techniques |
ISBN-10 | 981-19-8792-0 / 9811987920 |
ISBN-13 | 978-981-19-8792-2 / 9789811987922 |
Zustand | Neuware |
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