Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Research Progress on Structural Damage Identification in Civil Engineering
Structural damage identification has been a focus of civil engineering research in recent years. Therefore, this paper focuses on the advantages and disadvantages of various damage identification methods, including model updates, genetic algorithms, neural networks, support vector machines, dynamic fingerprints, wavelet transformations, and the Hilbert-Huang transform. This paper also discusses the latest research on damage identification combined with building information modeling (BIM) and deep learning. Finally, it is demonstrated that comparing the accuracy of different machine learning algorithms for damage identification and obtaining the optimal algorithm will become an important research direction in the future.
Research Progress on Structural Damage Identification in Civil Engineering
Structural damage identification has been a focus of civil engineering research in recent years. Therefore, this paper focuses on the advantages and disadvantages of various damage identification methods, including model updates, genetic algorithms, neural networks, support vector machines, dynamic fingerprints, wavelet transformations, and the Hilbert-Huang transform. This paper also discusses the latest research on damage identification combined with building information modeling (BIM) and deep learning. Finally, it is demonstrated that comparing the accuracy of different machine learning algorithms for damage identification and obtaining the optimal algorithm will become an important research direction in the future.
Research Progress on Structural Damage Identification in Civil Engineering
Song, Laijian (Autor:in) / Li, Shuai (Autor:in) / Wang, Jingquan (Autor:in) / Wang, Zhen (Autor:in) / Zhao, Guotang (Autor:in)
01.01.2020
372575 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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