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Prediction of mechanical behaviors of L-DED fabricated SS 316L parts via machine learning

Israt Zarin Era, Manikanta Grandhi, Zhichao Liu

2022The International Journal of Advanced Manufacturing Technology42 citationsDOIOpen Access PDF

Topics & Concepts

Random forestUltimate tensile strengthMean squared errorGradient boostingElastic net regularizationExtreme learning machineRidgeRapid prototypingMaterials scienceBoosting (machine learning)Laser power scalingRegressionAerospaceAlgorithmComputer scienceMachine learningComposite materialPower (physics)Feature selectionMathematicsEngineeringArtificial neural networkStatisticsAerospace engineeringBiologyPaleontologyQuantum mechanicsPhysicsAdditive Manufacturing Materials and ProcessesAdditive Manufacturing and 3D Printing TechnologiesWelding Techniques and Residual Stresses
Prediction of mechanical behaviors of L-DED fabricated SS 316L parts via machine learning | Litcius