Concrete dam deformation prediction model for health monitoring based on extreme learning machine

• Published in: Structural control and health monitoring Vol. 24; no. 10; pp. e1997 - n/a
• Main Authors: Kang, Fei, Liu, Jia, Li, Junjie, Li, Shouju
• Format: Journal Article
• Language: English
• Published: Pavia John Wiley & Sons, Inc 01.10.2017
• Subjects: Artificial neural networks; Back propagation; Back propagation networks; Concrete dams; dam health monitoring; Dams; Detention dams; extreme learning machine; Feedforward control; Gravity dams; Learning algorithms; Mathematical models; Monitoring; multiple linear regression; Neural networks; Nodes; Prediction models; Regression analysis; Seepage; Space shuttle; Statistical models; stepwise regression

Summary Structural health monitoring via quantities that can reflect behaviors of concrete dams, like horizontal and vertical displacements, rotations, stresses and strains, seepage, and so forth, is an important method to evaluate operational states of concrete dams correctly and predict the future...