Intelligent Computational Paradigms in Earthquake Engineering

Nikos D. Lagaros is an Assistant Professor of Civil Engineering at the Faculty of Civil Engineering, University of Thessaly and Research Associate of the National Technical University of Athens. His research activity is focused in the area of the optimum design of structures under static and seismic loading conditions using evolutionary and hybrid optimization methods. The optimum design problem of real world problems with multiple objective functions has also been a subject of research using specially tailored genetic algorithms and evolution strategies. He has more than 120 publications including 37 refereed international journal papers 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.

The enormous advances in computational hardware and software resources over the last fifteen years resulted in the development of non-conventional data processing and simulation methods. Among these methods artificial intelligence (AI) has been mentioned as one of the most eminent approaches to the so-called intelligent methods of information processing that present a great potential for engineering applications.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.