Machine learning in structural engineering

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AMEZQUITA SANCHEZ J.P.; VALTIERRA RODRIGUEZ M.; ADELI H.

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Journal Paper

Paper Information

Journal: SCIENTIA IRANICA Year:2020 | Volume:27 | Issue:6 (Transactions A: Civil Engineering) Page(s): 2645-2656

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Information Journal Paper

Title

Machine learning in structural engineering

Author(s)

AMEZQUITA SANCHEZ J.P. | VALTIERRA RODRIGUEZ M. | ADELI H. | Issue Writer Certificate

Keywords

Civil structures

Machine learning

Deep learning

Structural engineering

System identification

Structural health monitoring

Vibration control

Structural design

Prediction

Abstract

This article presents a review of selected articles about Structural engineering applications of Machine learning (ML) in the past few years. It is divided into the following areas: structural System identification, Structural health monitoring, structural Vibration control, Structural design, and Prediction applications. Deep neural network algorithms have been the subject of a large number of articles in civil and Structural engineering. There are, however, other ML algorithms with great potential in civil and Structural engineering that are worth exploring. Four novel supervised ML algorithms developed recently by the senior author and his associates with potential applications in civil/Structural engineering are reviewed in this paper. They are the Enhanced Probabilistic Neural Network (EPNN), the Neural Dynamic Classification (NDC) algorithm, the Finite Element Machine (FEMa), and the Dynamic Ensemble Learning (DEL) algorithm.

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APA: Copy

ADELI, H.. (2020). Machine learning in structural engineering. SCIENTIA IRANICA, 27(6 (Transactions A: Civil Engineering)), 2645-2656. SID. https://sid.ir/paper/973878/en

Vancouver: Copy

ADELI H.. Machine learning in structural engineering. SCIENTIA IRANICA[Internet]. 2020;27(6 (Transactions A: Civil Engineering)):2645-2656. Available from: https://sid.ir/paper/973878/en

IEEE: Copy

H. ADELI, “Machine learning in structural engineering,” SCIENTIA IRANICA, vol. 27, no. 6 (Transactions A: Civil Engineering), pp. 2645–2656, 2020, [Online]. Available: https://sid.ir/paper/973878/en

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