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Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

Structural Identification and Damage Detection using Genetic Algorithms
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簡體網頁||繁體網頁
Chan Ghee Koh 作者
CRC Press
譯者
2010-1-28 出版日期
140 頁數
USD 69.95 價格
Hardcover
叢書系列
9780415461023 圖書編碼

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Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


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Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 著者簡介

Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 著者簡介

Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Structural Identification and Damage Detection using Genetic Algorithms 在線電子書 圖書描述

Rapid advances in computational methods and computer capabilities have led to a new generation of structural identification strategies. Robust and efficient methods have successfully been developed on the basis of genetic algorithms (GA). This volume presents the development of a novel GA-based identification strategy that contains several advantageous features compared to previous methods. Focusing on structural identification problems with limited and noise contaminated measurements, it provides insights into the effects of various identification parameters on the identification accuracy for systems with known mass. It then proposes a generalization for systems with unknown mass, stiffness and damping properties. The GA identification strategy is subsequently extended for structural damage detection. The findings of the output-only strategy and substructural identification represent a great leap forward from the practical point of view. This book is intended for researchers, engineers and graduate students in structural and mechanical engineering, particularly for those interested in model calibration, parameter estimation and damage detection of structural and mechanical systems using the state-of-the-art GA methodology.

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