Prediction of shear strength of RC deep beams using XGBoost regression with Bayesian optimization-Reference-Cited by-同舟云学术

Prediction of shear strength of RC deep beams using XGBoost regression with Bayesian optimization

Published:2023-01-23 Issue:14 Volume:27 Page:4046-4066
ISSN:1964-8189
Container-title:European Journal of Environmental and Civil Engineering
language:en
Short-container-title:European Journal of Environmental and Civil Engineering

Author:

Truong Gia Toai¹,Choi Kyoung-Kyu²^ORCID,Nguyen Tri-Hai³,Kim Chang-Soo¹

Affiliation:

1. School of Architecture, Seoul National University of Science and Technology, Seoul, South Korea

2. School of Architecture, Soongsil University, Seoul, South Korea

3. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, South Korea

Funder

Seoul National University of Science and Technology

Ministry of Land, Infrastructure and Transport of Korean government

Publisher

Informa UK Limited

Subject

Civil and Structural Engineering,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/19648189.2023.2169357

Reference75 articles.

1. Prediction of elastic modulus of normal and high strength concrete using ANFIS and optimal nonlinear regression models

2. Machine learning for wildfire classification: Exploring blackbox, eXplainable, symbolic, and SMOTE methods

3. Machine Learning Algorithm for Shear Strength Prediction of Short Links for Steel Buildings

4. American Concrete Institute (ACI). (2019). ACI 318-19: Building code requirements for structural concrete and commentary. American Concrete Institute.

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