Intelligent Computational Paradigms in Earthquake Engineering, 1st Edition

  • Published By:
  • ISBN-10: 1599041014
  • ISBN-13: 9781599041018
  • Grade Level Range: College Freshman - College Senior
  • 444 Pages | eBook
  • Original Copyright 2007 | Published/Released December 2007
  • This publication's content originally published in print form: 2007

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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

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Intelligent Computational Paradigms in Earthquake Engineering: Table of Contents.
1: Structural Optimization Applications.
2: Improved Seismic Design Procedures and Evolutionary Tools.
3: Applying Neural Networks for Performance-Based Design in Earthquake Engineering.
4: Evolutionary Seismic Design for Optimal Performance.
5: Optimal Reliability-Based Design Using Support Vector Machines and Artificial Life Algorithms.
6: Optimum Design of Structures for Earthquake Induced Loading by Wavelet Neural Network.
7: Developments in Structural Optimization and Applications to Intelligent Structural Vibration Control.
8: Structural Assessment Applications.
9: Neuro-Fuzzy Assessment of Building Damage and Safety After an Earthquake.
10: Learning Machines for Structural Damage Detection.
11: Structural Assessment of RC Constructions and Fuzzy Expert Systems.
12: Life-Cycle Cost Evaluation of Bridge Structures Considering Seismic Risk.
13: Soft Computing Techniques in Probabilistic Seismic Analysis of Structures.
14: Structural Identification Applications.
15: Inverse Analysis of Weak and Strong Motion Downhole Array Data: A Hybrid Optimization Algorithm.
16: Genetic Algorithms in Structural Identification and Damage Detection.
17: Neural Network-Based Identification of Structural Parameters in Multistory Buildings.
18: Application of Neurocomputing to Parametric Identification Using Dynamic Responses.
19: Neural Networks for the Simulation and Identification Analysis of Buildings Subjected to Paraseismic Excitations.
About the Authors.