Concepedia

Predicting the compressive strength of CFRP-confined concrete using deep learning

Ali Benzaamia, Mohamed Ghrici, Redouane Rebouh, Kypros Pilakoutas, Panagiotis G. Asteris

Engineering Structures · 2024 · 46 citations · 90 references

Concepts

EngineeringCivil EngineeringMaterials EngineeringBuilding MaterialsConstruction EngineeringMachine LearningCompressive PropertiesConcrete ConstructionConcrete MaterialsConcrete TechnologyDeep LearningReinforced Concrete StructuresCompressive StrengthCompressive Strength DevelopmentConcrete Compressive StrengthConcrete Constitutive ModelsConcrete StrengthDeep Learning In ConstructionMachine Learning In Construction

References

90

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky et al. · 2014 · 34.3K citations

Computing, Computer Science, Artificial Intelligence +12

Takuya Akiba, Shotaro Sano, Toshihiko Yanase et al. · 2019 · 7.4K citations

Computing, Computer Engineering, Computer Science +11

Algorithms for hyper-parameter optimization

James Bergstra, Yoshua Bengio · 2011 · 3.2K citations · Full text

Computing, Computer Science, Algorithms +15

Design-oriented stress–strain model for FRP-confined concrete

L. Lam, J.G. Teng · Construction and Building Materials · 2003 · 1.6K citations

Engineering, Civil Engineering, Materials Engineering +12

Compressive Behavior of Concrete Confined by Carbon Fiber Composite Jackets

Yan Xiao, Haomin Wu · Journal of Materials in Civil Engineering · 2000 · 760 citations

Natural Sciences, Materials Engineering, Materials Science +17