Interpretable Machine Learning Algorithms to Predict the Axial Capacity of FRP-Reinforced Concrete Columns

Interpretable Machine Learning Algorithms to Predict the Axial Capacity of FRP-Reinforced Concrete Columns

Fiber-reinforced polymer (FRP) rebars are increasingly being used as an alternative to steel rebars in reinforced concrete (RC) members due to their excellent corrosion resistance capability and enhanced mechanical properties. Extensive research works have been performed in the last two decades to d...

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Bibliographic Details
Main Authors: Bekdaş, G. (Author), Cakiroglu, C. (Author), Geem, Z.W (Author), Islam, K. (Author), Kim, S. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Adaptive boosting
axial capacity
Axial capacity
Concrete construction
Corrosion resistance
Decision trees
ensemble learning
Ensemble learning
Fiber reinforced plastics
fiber-reinforced polymer (FRP) rebar
Fiber-reinforced polymer rebar
Fiber-reinforced polymers
Fibre reinforced polymers
Forecasting
Gradient boosting
harmony search optimization
Harmony search optimizations
Load limits
Loads (forces)
machine learning
Machine learning models
Polymer rebars
Regression analysis
Reinforced concrete
Reinforced concrete column
reinforced concrete columns
Steel corrosion
Steel fibers
Support vector machines
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