A comprehensive review of robust methods based on genetic algorithms (GA), this book presents readers with the background and recent developments required to conduct research and apply GA-based methods for parameter identification, model updating, and damage detection of structural dynamic systems. It demonstrates a novel strategy that focuses on structural identification problems with limited and noise-contaminated measurements. This book also presents parameter estimation of non-linear structural systems to illustrate the power and versatility of the GA-based identification strategy.
A comprehensive review of robust methods based on genetic algorithms (GA), this book presents readers with the background and recent developments required to conduct research and apply GA-based methods for parameter identification, model updating, and damage detection of structural dynamic systems. It demonstrates a novel strategy that focuses on structural identification problems with limited and noise-contaminated measurements. This book also presents parameter estimation of non-linear structural systems to illustrate the power and versatility of the GA-based identification strategy.
1. Introduction 2. A Primer to Genetic Algorithms 3. An Improved GA Strategy 4. Structural Identification by GA 5. Output-Only Structural Identification 6. Structural Damage Detection 7. Experimental Verification Study 8. Substructure Methods of Identification References, Appendix, Index.
1. Introduction 2. A Primer to Genetic Algorithms 3. An Improved GA Strategy 4. Structural Identification by GA 5. Output-Only Structural Identification 6. Structural Damage Detection 7. Experimental Verification Study 8. Substructure Methods of Identification References, Appendix, Index.
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