Prognosticating fabric-reinforced cementitious matrix-to-masonry bond and failure mechanisms using novel tabular variational autoencoder-augmented probabilistic model
Aman Kumar, Afshin Marani, Asim Abbas, Moncef L. Nehdi
Topics & Concepts
Computer scienceProbabilistic logicExtrapolationUncertainty quantificationArtificial intelligenceNormalization (sociology)MasonryPredictabilityMachine learningCategorical variableBayesian probabilitySupport vector machineNaive Bayes classifierGaussianDiscriminatorStatistical modelAutoencoderBoosting (machine learning)Artificial neural networkTest setPattern recognition (psychology)Robustness (evolution)Bayesian inferenceAlgorithmAutoregressive modelCompatibility (geochemistry)Bond strengthFailure mode and effects analysisTest dataData miningMaterial failure theoryBayes' theoremRange (aeronautics)Mixture modelSet (abstract data type)Synthetic dataMasonry and Concrete Structural AnalysisInnovative concrete reinforcement materialsCivil and Structural Engineering Research