Structural health monitoring of harbor caissons using support vector machine and principal component analysis

• Published in: Structures (Oxford) Vol. 33; pp. 4501 - 4513
• Main Authors: Bolourani, Anahita, Bitaraf, Maryam, Nekouvaght Tak, Ala
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2021
• Subjects: Autoregressive (AR) model; Finite element (FE) modeling; Harbor caissons; Machine learning; Principal component analysis (PCA); Structural health monitoring; Support vector machine (SVM); Harbor caissons; Support vector machine (SVM); Autoregressive (AR) model; Machine learning; Structural health monitoring; Finite element (FE) modeling; Principal component analysis (PCA)

Harbor caissons are regarded as one of the most critical infrastructures, and any disruption in their operation would have dramatic economic consequences. The need for a health monitoring system for these structures is thus evident. The primary aim of this study is to develop a structural health mon...