Development of data-driven prediction model for CFRP-steel bond strength by implementing ensemble learning algorithms-Reference-Cited by-同舟云学术

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Development of data-driven prediction model for CFRP-steel bond strength by implementing ensemble learning algorithms

Published:2021-10 Issue: Volume:303 Page:124470
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Chen Shi-Zhi,Feng De-Cheng,Han Wan-Shui,Wu Gang

Funder

Chang'an University

Natural Science Foundation of Shaanxi Province

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference46 articles.

1. Damage Detection of Highway Bridges Based on Long-Gauge Strain Response under Stochastic Traffic Flow;Chen;Mech Syst Signal Pr,2019

2. Multi-Cross-Reference Method for Highway-Bridge Damage Identification Based on Long-Gauge Fiber Bragg-Grating Sensors;Chen;J Bridge Eng,2020

3. The bond behaviour of CFRP-to-steel bonded joints with varying bond properties at elevated temperatures;Zhou;Eng Struct,2019

4. Experimental study on the carbon-fiber-reinforced polymer–steel interfaces based on carbon-fiber-reinforced polymer delamination failures and hybrid failures;Pang;Adv Struct Eng,2020

5. Analytical and experimental evaluation of flexural behavior of FRP pultruded composite profiles for bridge deck structural design;Xin;Constr Build Mater,2017

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