Papers citing Deep learning method for predicting the mechanical properties of aluminum alloys with small data sets
Predicting Strength of Selective Laser Melting 3D Printed A1Si10Mg Alloy Parts by Machine Learning Models
International Conference on Signal Processing and Integrated Networks (SPIN) · 2021
Pritish Shubham, Ajay Sharma, Prem Narayan Vishwakarma, Rakesh Kumar Phanden
Read original paper ↗ ·Machine learning reveals strain-rate-dependent predictability of discrete dislocation plasticity
Physical Review Materials · 2022
Marcin Mińkowski, David Kurunczi-Papp, Lasse Laurson
Read original paper ↗ ·Extracting the properties of constituent phases from the overall response of composites: A deep neural network method
Composite Structures · 2022
Ye Sang, Min Li, Kaixuan Zhang, Hongping Zhao, Xi‐Qiao Feng
Read original paper ↗ ·Optimized XGBoost Model with Small Dataset for Predicting Relative Density of Ti-6Al-4V Parts Manufactured by Selective Laser Melting
Materials · 2022
Miao Zou, Wugui Jiang, Qing‐Hua Qin, Yucheng Liu, Maolin Li
Read original paper ↗ ·Applying 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 Environment
Applied Sciences · 2022
Бурмакова Анастасия Владимировна, Diana Kalibatienė
Read original paper ↗ ·From Data to Wisdom: A Review of Applications and Data Value in the context of Small Data
Procedia Computer Science · 2023
Jonas Werner, Philipp Beisswanger, Christoph Schuerger, Marco Klaiber, Andreas Theissler
Read original paper ↗ ·Prediction of Drug Demand Based on Deep Learning Approach and Classification Model
International Journal on Advanced Science Engineering and Information Technology · 2023
Musli Yanto, Syafri Arlis, Muhammad Reza Putra, Hadi Syahputra, Vicky Ariandi
Read original paper ↗ ·A machine learning method for HTLCF life prediction of titanium aluminum alloys with consideration of manufacturing processes
Engineering Fracture Mechanics · 2023
Haojin Yang, Jianxiong Gao, Pengnian Zhu, Qin Cheng, Fei Heng, Yuanyuan Liu
Read original paper ↗ ·Neural network-based ductile fracture model for 5182-O aluminum alloy considering electroplastic effect in electrically-assisted processing
Engineering Fracture Mechanics · 2023
Hongchun Shang, Songchen Wang, Liucheng Zhou, Yanshan Lou
Read original paper ↗ ·Artificial Intelligence in Predicting Mechanical Properties of Composite Materials
Journal of Composites Science · 2023
Fasikaw Kibrete, Tomasz Trzepieciński, Hailu Shimels Gebremedhen, Dereje Engida Woldemichael
Read original paper ↗ ·Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks
Materials Research Express · 2023
M C Gowrishankar, Srinivas Doddapaneni, Sathyashankara Sharma, Ananda Hegde, Manjunath Shettar, B. M. Karthik
Read original paper ↗ ·Prediction model for the failure behavior of concrete under impact loading base on back propagation neural network
Construction and Building Materials · 2023
Jianguo Ning, Yuanbao Feng, Huilan Ren, Xiangzhao Xu
Read original paper ↗ ·Research on composition-process-property prediction of die casting Al alloys via combining feature creation and attention mechanisms
Journal of Materials Research and Technology · 2023
Jian Lin Yang, Bo Liu, Haiyou Huang
Read original paper ↗ ·Leveraging Deep Neural Networks for Estimating Vickers Hardness from Nanoindentation Hardness
Materials · 2023
Junbo Niu, Bin Miao, Jiaxu Guo, Zhifeng Ding, Yin He, Zhiyu Chi, Feilong Wang, Xinxin Ma
Read original paper ↗ ·Artificial Intelligence and Machine Learning for Material Characterizations and Mechanical Properties
Tissue repair and reconstruction · 2024
Nura Brimo, Dilek Çökeli̇ler Serdaroğlu, Halit Muhittin
Read original paper ↗ ·Characterization and Modeling of Mechanical Properties of Additively Manufactured Coconut Fiber-Reinforced Polypropylene Composites
Advances in Materials Physics and Chemistry · 2024
George Mosi, Bernard W. Ikua, Samuel Kabini Karanja, James Wamai Mwangi
Read original paper ↗ ·Fuzzy inference and machine learning-based prediction with a small dataset for oil spills in the geological environment
Venue not supplied by source · 2024
Бурмакова Анастасия Владимировна
Read original paper ↗ ·Optimization and prediction of mechanical properties of composite concrete with crumb rubber using RSM and hybrid DNN-HHO algorithm
Journal of Building Engineering · 2024
R. Anjali, G. Venkatesan
Read original paper ↗ ·PREDICTING ALUMINA COMPOSITES’ MECHANICAL CHARACTERISTICS USING A MACHINE LEARNING APPROACH
Proceedings on Engineering Sciences · 2024
Ashwini Kumar, Arunkumar Devalapura Thimmappa, Ritesh Kumar, Manali Gupta
Read original paper ↗ ·Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy
Engineering Applications of Artificial Intelligence · 2024
Jian Lin Yang, Bo Liu, Yunbo Zeng, Yiben Zhang, Haiyou Huang, Jichao Hong
Read original paper ↗ ·Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO 3 -type perovskite with doping modification
Royal Society Open Science · 2024
Quan Luo, Hua Hao, Hanxing Liu
Read original paper ↗ ·A FEM-guided data-driven machine learning model for residual stress characterization in ultrasonic surface rolling of lightweight alloys
Applied Physics A · 2024
Rahul Pradhan, Farag M. A. Altalbawy, Ahmed Raza Khan, Carlos Rodriguez‐Benites, Mukesh Kumar Sharma, Renas Rajab Asaad
Read original paper ↗ ·NSGAN: a non-dominant sorting optimisation-based generative adversarial design framework for alloy discovery
npj Computational Materials · 2024
Ziyuan Li, N. Birbilis
Read original paper ↗ ·Abrasive wear behavior of functionally graded Al3Ti reinforced aluminum matrix composite
China Foundry · 2024
Eylül Tuğçe Yaman Yildiz, Ömer Savaş, Muhammed Soner Başer, Engin Kocaman
Read original paper ↗ ·Integrating machine learning and the finite element method for assessing stiffness degradation in photovoltaic modules
Journal of Physics Condensed Matter · 2024
Weiqing Li
Read original paper ↗ ·Finite element method-enabled machine learning for analysing residual stress and plastic deformation in surface mechanical attrition-treated alloys
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering · 2024
Biju Theruvil Sayed, Arif Sari, Wade Ghribi, Ahmed A. H. Alkurdi, Shavan K. Askar, Shavan Askar, Karrar Hatif Mohmmed
Read original paper ↗ ·Machine Learning-Based Analysis of Surface Hardening in Shot-Peened Superalloys
Journal of Materials Engineering and Performance · 2024
Paul Rodrigues, Mokhtar Massoud Kerwad, Shavan K. Askar, Harikumar Pallathadka, Dilsora Abduvalieva, Sajad Ali Zearah
Read original paper ↗ ·Taylor‐based smart flower optimization algorithm with the deep residual network to predict mechanical materials properties
Optimal Control Applications and Methods · 2024
Oshin Sharma, Deepak Sharma
Read original paper ↗ ·Image-driven prediction of fatigue crack growth in metal materials via spatiotemporal neural network
Engineering Fracture Mechanics · 2024
J.M. Liang, Yin Yu, Yile Hu, C.H. Wan, X.Z. Feng
Read original paper ↗ ·Investigation of age-hardening behaviour of Al alloys via feature screening-assisted machine learning
Materials Science and Engineering A · 2024
Mingwei Hu, Qiyang Tan, Ruth Knibbe, Bin Jiang, Xue Li, Mingxing Zhang
Read original paper ↗ ·Machine Learning‐Based Strength Prediction for Two‐Stage Aged 7050 Aluminum Alloy Forgings in Aircraft Main Support Joints
Advanced Engineering Materials · 2024
Yongjie Liu, Yuanzhi Qian, Weijiu Huang, Xiaofei Zhu, Xusheng Yang, Lingfei Cao, Yanzheng Guo, Mofan Liu, Wenya Xiao, Ke Gan
Read original paper ↗ ·The role of artificial intelligence in materials science: a review
Elsevier eBooks · 2024
Dhanya Lakshmi, Rithuraj Nambiar, Parveen Kumar
Read original paper ↗ ·Local elasticity assessment of unidirectional fiber-reinforced polymer composites through impulse excitation and machine learning
Journal of Reinforced Plastics and Composites · 2024
Ying Liu, Hamzah Ali Alkhazaleh, Mohammad Ahmar Khan, Majid Samavatian, Vahid Samavatian
Read original paper ↗ ·A hybrid knowledge-guided and data-driven method for predicting low-alloy steels performance
Computational Materials Science · 2024
Conghua Qi, Chengmeng Wang, Dongmei Fu, Lizhen Shao, Ke Zhou, Zhiyi Zhao
Read original paper ↗ ·Applications of Quantitative Read-Across Structure–Property Relationship (q-RASPR) Modeling in the Field of Materials Science
Challenges and advances in computational chemistry and physics · 2025
Shubham Kr. Pandey, Souvik Pore, Arkaprava Banerjee, Kunal Roy
Read original paper ↗ ·Predicting Yield Strength of Aluminum Alloys Based on Composition
The minerals, metals & materials series · 2025
Clinton Kade Waite, Eric R. Homer, Luca Montanelli, Elsa Olivetti
Read original paper ↗ ·Grain gradient refinement and corrosion mechanisms in metals through severe plastic deformation: insights from Surface Mechanical Attrition Treatment (SMAT)
Advanced Composites and Hybrid Materials · 2025
Xi-wen Yue, Huayun Du, L.J. Zhang, Lifeng Hou, Qian Wang, Huan Wei, Xiaoda Liu, Yinghui Wei
Read original paper ↗ ·Estimation 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)
Biomass Conversion and Biorefinery · 2025
Mamadou Saliou Balde, Rukiye Karakış, Ayten Ateş
Read original paper ↗ ·Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering
Materials Today Physics · 2025
Xiaobin Liu, Qiuxia Huang, Chang Su, Ning Shao, Lei Zhang, Yapeng Tian, Huanfu Zhou
Read original paper ↗ ·Implicit geometric descriptor-enabled ANN Framework for a unified structure-property relationship in architected nanofibrous materials
Extreme Mechanics Letters · 2025
Bhanugoban Maheswaran, Komal Chawla, Abhishek Gupta, Ramathasan Thevamaran
Read original paper ↗ ·Data-driven dynamic friction models based on Recurrent Neural Networks
Applied Computing and Geosciences · 2025
Gaëtan Cortes, Joaquin Garcia‐Suarez
Read original paper ↗ ·Co-design of geometry and thermal-elastic gradient alloy distribution with temperature-dependent material properties
Structural and Multidisciplinary Optimization · 2025
Stefan Knapik, Shiguang Deng, Liwei Wang, Aaditya Chandrasekhar, Wing Kam Liu, Jian Feng Cao, Wei Chen
Read original paper ↗ ·Transformer based spatially resolved prediction of mechanical properties in wire arc additive manufacturing
Scientific Reports · 2025
Mohammad Keshmiri, Shirin Dehgahi, Abdullah Mohiuddin, Ahmed Jawad Qureshi
Read original paper ↗ ·Data-driven time series analysis for high-temperature deformation behavior prediction based on the deep learning approach: A case study on titanium alloy
Journal of Alloys and Compounds · 2025
Taowen Wu, Zhanping Gao, Minghe Chen, Hongrui Dong
Read original paper ↗ ·Analysis of thermal conductivity of aluminum alloys by compositions and tempering process using machine learning
Scientific Reports · 2025
Adnan Roshid Shawon, Rittika Ghosh, Md Ashraful Islam
Read original paper ↗ ·The Role of Artificial Intelligence in Biomaterials Science: A Review
Polymers · 2025
Andrea Martelli, Devis Bellucci, Valeria Cannillo
Read original paper ↗ ·Research on the Deformation Behavior at Elevated Temperature of Ti-6Al-4 V Titanium Based on the Recurrent Neural Network
Journal of Materials Engineering and Performance · 2025
Taowen Wu, Minghe Chen, Hongrui Dong, Xiangwei Wen, Qianlong Sui
Read original paper ↗ ·A Comprehensive Study on Machine Learning Techniques for Prediction of Material Properties
Macromolecular Symposia · 2026
Shalini Zanzote Ninoria, Diptonil Banerjee
Read original paper ↗ ·Comparative analysis of machine learning models for predicting the mechanical properties of aerospace grade fiber composites
Machine learning for computational science and engineering · 2026
Md Shafinur Murad, Abdulhammed K. Hamzat, Naime A. Unlu, Özkan Altay, Ersin Bahçeci, Eylem Asmatulu, Mete Bakır, Ramazan Asmatulu
Read original paper ↗ ·Utilizing hybrid BIGRU-LIGHTGBM model for mechanical characteristics prediction in aluminium alloys
International Journal of Material Forming · 2026
Lakshmi Rajan P., Sujatha I., Arun M. S.
Read original paper ↗ ·