| BA-PNN-based methods for power transformer fault diagnosis X Yang, W Chen, A Li, C Yang, Z Xie, H Dong Advanced engineering informatics 39, 178-185, 2019 | 108 | 2019 |
| Defect criticality analysis on fatigue life of L-PBF 17-4 PH stainless steel via machine learning A Li, S Baig, J Liu, S Shao, N Shamsaei International Journal of Fatigue 163, 107018, 2022 | 43 | 2022 |
| Machine learning-based sensor data modeling methods for power transformer PHM A Li, X Yang, H Dong, Z Xie, C Yang Sensors 18 (12), 4430, 2018 | 40 | 2018 |
| Nonparametric bayesian framework for material and process optimization with nanocomposite fused filament fabrication J Liu, J Ye, F Momin, X Zhang, A Li Additive Manufacturing 54, 102765, 2022 | 29 | 2022 |
| An inspired machine-learning algorithm with a hybrid whale optimization for power transformer PHM W Zhang, X Yang, Y Deng, A Li Energies 13 (12), 3143, 2020 | 27 | 2020 |
| A Hybrid machine‐learning method for oil‐immersed power transformer fault diagnosis X Yang, W Chen, A Li, C Yang IEEJ Transactions on Electrical and Electronic Engineering 15 (4), 501-507, 2020 | 25 | 2020 |
| Fault diagnosis in industrial chemical processes using optimal probabilistic neural network Z Xie, X Yang, A Li, Z Ji The Canadian Journal of Chemical Engineering 97 (9), 2453-2464, 2019 | 20 | 2019 |
| Bio-inspired PHM model for diagnostics of faults in power transformers using dissolved gas-in-oil data H Dong, X Yang, A Li, Z Xie, Y Zuo Sensors 19 (4), 845, 2019 | 19 | 2019 |
| An optimized GRNN‐enabled approach for power transformer fault diagnosis A Li, X Yang, Z Xie, C Yang IEEJ Transactions on Electrical and Electronic Engineering 14 (8), 1181-1188, 2019 | 15 | 2019 |
| A Novel Method for Power Transformer Fault Diagnosis Based on Bat-BP Algorithm H Dong, X Yang, A Li 2018 International Conference on Sensing, Diagnostics, Prognostics, and …, 2018 | 7 | 2018 |
| Cuckoo Search Optimized NN-Based Fault Diagnosis Approach for Power Transformer PHM A Li, X Yang, H Dong, C Yang 2018 International Conference on Sensing, Diagnostics, Prognostics, and …, 2018 | 5 | 2018 |
| A data-driven process-quality-property analytical framework for conductive composites in additive manufacturing T Gao, A Li, X Zhang, G Harris, J Liu Manufacturing Letters 35, 626-635, 2023 | 3 | 2023 |
| Nondestructive fatigue life prediction for additively manufactured metal parts through a multimodal transfer learning framework A Li, A Poudel, S Shao, N Shamsaei, J Liu IISE Transactions, 1-16, 2024 | 2 | 2024 |
| A Novel Visible Light Communication System Prototype Based on SiPM Receiver Z Deng, A Li arXiv preprint arXiv:1909.00641, 2019 | 1 | 2019 |
| Defects Classification via Hierarchical Graph Convolutional Network in L-PBF Additive Manufacturing A Li, J Liu, S Shao, N Shamsaei 2022 International Solid Freeform Fabrication Symposium, 2022 | | 2022 |
| Patent analysis of PET core components and development of enterprises, universities and research institutions Z DENG, S HE, A CHEN, Z LIU, A LI, Y DENG Science & Technology Review 38 (24), 129-137, 2020 | | 2020 |
| PET Quantification of Ultra Low Activity via Inhomogeneous Poisson Process Parameters Estimation Directly from Listmode Data Z Deng, X Zhao, A Li arXiv preprint arXiv:1909.02254, 2019 | | 2019 |
| A Fast algorithm of PET System Response Matrix based on Straight Line Truncation Z Deng, F Luo, A Li, L Ling, J Xiong, S Xu, H Deng, X Zhao arXiv preprint arXiv:1909.02263, 2019 | | 2019 |
Jia LiuAuburn UniversityBestätigte E-Mail-Adresse bei auburn.edu
