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RESEARCH PAPER · Materials Today Communications · 2021

Deep learning method for predicting the mechanical properties of aluminum alloys with small data sets

Zhang Yu, Ye Sang, Yanli Sun, Hucheng Zhao, Xi‐Qiao Feng

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Deep learning method for predicting the mechanical properties of aluminum alloys with small data setsOriginalPredicting Strength of Selective Laser Melting 3D Printed A1Si10Mg Alloy Parts by Machine Learning Models10Machine learning reveals strain-rate-dependent predictability of discrete dislocation plasticity7Extracting the properties of constituent phases from the overall response of composites: A deep neural network method8Optimized XGBoost Model with Small Dataset for Predicting Relative Density of Ti-6Al-4V Parts Manufactured by Selective Laser Melting138Applying Fuzzy Inference and Machine Learning Methods for Prediction with a Small Dataset: A Case Study for Predicting the Consequences of Oil Spills on a Ground Environment10From Data to Wisdom: A Review of Applications and Data Value in the context of Small Data2Prediction of Drug Demand Based on Deep Learning Approach and Classification Model1A machine learning method for HTLCF life prediction of titanium aluminum alloys with consideration of manufacturing processes9Neural network-based ductile fracture model for 5182-O aluminum alloy considering electroplastic effect in electrically-assisted processing23Artificial Intelligence in Predicting Mechanical Properties of Composite Materials249Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks3Prediction model for the failure behavior of concrete under impact loading base on back propagation neural network27Research on composition-process-property prediction of die casting Al alloys via combining feature creation and attention mechanisms21Leveraging Deep Neural Networks for Estimating Vickers Hardness from Nanoindentation Hardness11Artificial Intelligence and Machine Learning for Material Characterizations and Mechanical Properties7Characterization and Modeling of Mechanical Properties of Additively Manufactured Coconut Fiber-Reinforced Polypropylene Composites5Fuzzy inference and machine learning-based prediction with a small dataset for oil spills in the geological environment0Optimization and prediction of mechanical properties of composite concrete with crumb rubber using RSM and hybrid DNN-HHO algorithm21PREDICTING ALUMINA COMPOSITES’ MECHANICAL CHARACTERISTICS USING A MACHINE LEARNING APPROACH0Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy13Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO 3 -type perovskite with doping modification8A FEM-guided data-driven machine learning model for residual stress characterization in ultrasonic surface rolling of lightweight alloys9NSGAN: a non-dominant sorting optimisation-based generative adversarial design framework for alloy discovery26Abrasive wear behavior of functionally graded Al3Ti reinforced aluminum matrix composite7Integrating machine learning and the finite element method for assessing stiffness degradation in photovoltaic modules3Finite element method-enabled machine learning for analysing residual stress and plastic deformation in surface mechanical attrition-treated alloys4Machine Learning-Based Analysis of Surface Hardening in Shot-Peened Superalloys3Taylor‐based smart flower optimization algorithm with the deep residual network to predict mechanical materials properties1Image-driven prediction of fatigue crack growth in metal materials via spatiotemporal neural network19Investigation of age-hardening behaviour of Al alloys via feature screening-assisted machine learning14Machine Learning‐Based Strength Prediction for Two‐Stage Aged 7050 Aluminum Alloy Forgings in Aircraft Main Support Joints2The role of artificial intelligence in materials science: a review0Local elasticity assessment of unidirectional fiber-reinforced polymer composites through impulse excitation and machine learning5A hybrid knowledge-guided and data-driven method for predicting low-alloy steels performance7Applications of Quantitative Read-Across Structure–Property Relationship (q-RASPR) Modeling in the Field of Materials Science2Predicting Yield Strength of Aluminum Alloys Based on Composition0Grain gradient refinement and corrosion mechanisms in metals through severe plastic deformation: insights from Surface Mechanical Attrition Treatment (SMAT)43Estimation of specific surface area and higher heating value of biochar and activated carbon produced by pyrolysis and physico-chemically assisted pyrolysis of biomass using an artificial neural network (ANN)14Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering4Implicit geometric descriptor-enabled ANN Framework for a unified structure-property relationship in architected nanofibrous materials6Data-driven dynamic friction models based on Recurrent Neural Networks3Co-design of geometry and thermal-elastic gradient alloy distribution with temperature-dependent material properties5Transformer based spatially resolved prediction of mechanical properties in wire arc additive manufacturing7Data-driven time series analysis for high-temperature deformation behavior prediction based on the deep learning approach: A case study on titanium alloy6Analysis of thermal conductivity of aluminum alloys by compositions and tempering process using machine learning11The Role of Artificial Intelligence in Biomaterials Science: A Review21Research on the Deformation Behavior at Elevated Temperature of Ti-6Al-4 V Titanium Based on the Recurrent Neural Network1A Comprehensive Study on Machine Learning Techniques for Prediction of Material Properties0Comparative analysis of machine learning models for predicting the mechanical properties of aerospace grade fiber composites1Utilizing hybrid BIGRU-LIGHTGBM model for mechanical characteristics prediction in aluminium alloys0Machine learning in additive manufacturing of aluminum alloys: a review of fundamentals, challenges, and evolution of intelligent pathways0Advancing Wire Arc Additive Manufacturing through Hybrid FEM-ML Modeling and Digital Twin-Driven Control0

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  2. Machine learning reveals strain-rate-dependent predictability of discrete dislocation plasticity

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  4. Optimized XGBoost Model with Small Dataset for Predicting Relative Density of Ti-6Al-4V Parts Manufactured by Selective Laser Melting

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  17. Fuzzy inference and machine learning-based prediction with a small dataset for oil spills in the geological environment

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  18. Optimization and prediction of mechanical properties of composite concrete with crumb rubber using RSM and hybrid DNN-HHO algorithm

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  19. PREDICTING ALUMINA COMPOSITES’ MECHANICAL CHARACTERISTICS USING A MACHINE LEARNING APPROACH

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  20. Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy

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  21. Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO 3 -type perovskite with doping modification

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  22. A FEM-guided data-driven machine learning model for residual stress characterization in ultrasonic surface rolling of lightweight alloys

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