Intelligent Computational Paradigms in Earthquake Engineering contains contributions that cover a wide spectrum of very important real-world engineering problems, and explore the implementation of neural networks for the representation of structural responses in earthquake engineering. This book assesses the efficiency of seismic design procedures and describes the latest findings in intelligent optimal control systems and their applications in structural engineering. Intelligent Computational Paradigms in Earthquake Engineering presents the application of learning machines, artificial neural networks and support vector machines as highly-efficient pattern recognition tools for structural damage detection. It includes an AI-based evaluation of bridge structures using life-cycle cost principles that considers seismic risk, and emphasizes the use of AI methodologies in a geotechnical earthquake engineering application.
Yiannis Tsompanakis has received his M.Sc. and Ph.D. in Civil Engineering from the Department of Civil Engineering, National Technical University of Athens, Greece. He is currently an Assistant Professor of structural earthquake engineering at the Department of Applied Sciences, Technical University of Crete, Greece. He teaches undergraduate and postgraduate courses in structural mechanics and earthquake engineering and he is a supervisor of diploma, master and doctoral theses. He is a reviewer for archival journals and he has participated in the organization of several international congresses. He has published over 60 research papers in international journals, book chapters and conference proceedings. He has been involved in many research and practical projects in the field of earthquake engineering and computational mechanics. His main research interests include: structural and geotechnical earthquake engineering, structural optimization, probabilistic mechanics, structural assessment, applications of artificial intelligence methods in engineering. [Editor]