| Nonlinear identification of a gasoline HCCI engine using neural networks coupled with principal component analysis VM Janakiraman, XL Nguyen, D Assanis Applied Soft Computing 13 (5), 2375-2389, 2013 | 103 | 2013 |
| Anomaly detection in aviation data using extreme learning machines VM Janakiraman, D Nielsen 2016 international joint conference on neural networks (IJCNN), 1993-2000, 2016 | 74 | 2016 |
| Explaining aviation safety incidents using deep temporal multiple instance learning VM Janakiraman Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 62 | 2018 |
| Stochastic gradient based extreme learning machines for stable online learning of advanced combustion engines VM Janakiraman, XL Nguyen, D Assanis Neurocomputing 177, 304-316, 2016 | 53 | 2016 |
| An ELM based predictive control method for HCCI engines VM Janakiraman, XL Nguyen, D Assanis Engineering Applications of Artificial Intelligence 48, 106-118, 2016 | 51 | 2016 |
| Identification of the dynamic operating envelope of HCCI engines using class imbalance learning VM Janakiraman, XL Nguyen, J Sterniak, D Assanis IEEE transactions on neural networks and learning systems 26 (1), 98-112, 2014 | 46 | 2014 |
| Comparative study of the performance and emission characteristics of biodiesels from different vegetable oils with diesel S Suryanarayanan, VM Janakiraman, GLN Rao, S Sampath SAE Technical Paper, 2008 | 37 | 2008 |
| Discovery of precursors to adverse events using time series data VM Janakiraman, B Matthews, N Oza Proceedings of the 2016 SIAM International Conference on Data Mining, 639-647, 2016 | 34 | 2016 |
| Finding precursors to anomalous drop in airspeed during a flight's takeoff VM Janakiraman, B Matthews, N Oza Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 22 | 2017 |
| Machine Learning for Identification and Optimal Control of Advanced Automotive Engines. VM Janakiraman | 22 | 2013 |
| A system identification framework for modeling complex combustion dynamics using support vector machines VM Janakiraman, XL Nguyen, J Sterniak, D Assanis Informatics in Control, Automation and Robotics: 9th International …, 2014 | 15 | 2014 |
| A Lyapunov based stable online learning algorithm for nonlinear dynamical systems using extreme learning machines VM Janakiraman, XL Nguyen, D Assanis The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 13 | 2013 |
| Nonlinear model predictive control of a gasoline HCCI engine using extreme learning machines VM Janakiraman, XL Nguyen, D Assanis arXiv preprint arXiv:1501.03969, 2015 | 12 | 2015 |
| Prediction of cetane number of a biodiesel based on physical properties and a study of their influence on cetane number S Suryanarayanan, VM Janakiraman, J Sekar, G Lakshmi, N Rao SAE Technical Paper, 2007 | 9 | 2007 |
| Using ADOPT algorithm and operational data to discover precursors to aviation adverse events VM Janakiraman, B Matthews, N Oza 2018 AIAA Information Systems-AIAA Infotech@ Aerospace, 1638, 2018 | 8 | 2018 |
| Explaining aviation safety incidents using deep learned precursors VM Janakiraman arXiv preprint arXiv:1710.04749, 2017 | 7 | 2017 |
| Lyapunov method based online identification of nonlinear systems using extreme learning machines VM Janakiraman, D Assanis arXiv preprint arXiv:1211.1441, 2012 | 7 | 2012 |
| Estimation of engine emissions based on physical and chemical properties of biodiesels using artificial neural networks VM Janakiraman, S Suryanarayanan, GLN Rao, S Sampath SAE Technical Paper, 2006 | 6 | 2006 |
| Variables influencing RNAV STAR adherence. IEEE/AIAA M Stewart, B Matthews, I Avrekh, V Janakiraman Proceedings of the 37th Digital Avionics Systems Conference (DASC). London, UK, 2018 | 5 | 2018 |
| Accept: Introduction of the adverse condition and critical event prediction toolbox RA Martin, D Santanu, VM Janakiraman, S Hosein | 5 | 2015 |
XuanLong NguyenUniversity of MichiganΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα umich.edu