January 05, 2013 conference-paper Characterization of Shape Memory Alloys Using Artificial Neural Networks AIAA Aerospace Sciences Meeting DOI: 10.2514/6.2013-129 OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 6 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Feedforward neural network-assisted parameter identification and tuning for uniaxial superelastic shape memory alloy models under dynamic loads 2024 Journal of Vibration and Control article Materials Science Shape Memory Alloy Transformations Open access 5 citations Machine Learning Enhanced Dynamic Response Modelling of Superelastic Shape Memory Alloy Wires 2022 Materials article Materials Science Shape Memory Alloy Transformations Open access 27 citations 2 results References 0