Lefteri H. Tsoukalas
Affiliations: | Nuclear Engineering | Purdue University, West Lafayette, IN, United States |
Area:
Nuclear Engineering, Artificial IntelligenceWebsite:
https://engineering.purdue.edu/~tsoukala/Google:
"Lefteris H. Tsoukalas"Bio:
https://www.proquest.com/openview/8c438b561decd3867f9132787cfb1e8d/1
Parents
Sign in to add mentor| Magdi M. H. Ragheb | grad student | 1989 | UIUC | |
| (Anticipatory systems using a probabilistic-possibilistic formalism) | ||||
Children
Sign in to add trainee| Thomas E. Fieno | grad student | 2000 | Purdue |
| In-ho Won | grad student | 2005 | Purdue |
| Anton A. Bougaev | grad student | 2006 | Purdue |
| Jack E. Fulton | grad student | 2007 | Purdue |
| Nader Satvat | grad student | 2010 | Purdue |
| Vivek Agarwal | grad student | 2011 | Purdue |
| Miltiadis Alamaniotis | grad student | 2012 | Purdue |
| Demir Akin | research scientist | 2000-2002 | Purdue (Physics Tree) |
BETA: Related publications
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Publications
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| Alamaniotis M, Bourbakis N, Tsoukalas LH. (2019) Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithms Sustainable Cities and Society. 46: 101426 |
| Alamaniotis M, Gatsis N, Tsoukalas LH. (2018) Virtual Budget: Integration of electricity load and price anticipation for load morphing in price-directed energy utilization Electric Power Systems Research. 158: 284-296 |
| Alamaniotis M, Mathew J, Chroneos A, et al. (2018) Probabilistic kernel machines for predictive monitoring of weld residual stress in energy systems Engineering Applications of Artificial Intelligence. 71: 138-154 |
| Agarwal V, DeCarlo RA, Tsoukalas LH. (2017) Modeling Energy Consumption and Lifetime of a Wireless Sensor Node Operating on a Contention-Based MAC Protocol Ieee Sensors Journal. 17: 5153-5168 |
| Alamaniotis M, Bargiotas D, Tsoukalas LH. (2016) Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting. Springerplus. 5: 58 |
| Lagari PL, Sobes V, Alamaniotis M, et al. (2016) Application of Artificial Neural Networks to Reliable Nuclear Data for Nonproliferation Modeling and Simulation International Journal of Monitoring and Surveillance Technologies Research. 4: 54-64 |
| Fainti R, Nasiakou A, Alamaniotis M, et al. (2016) Hierarchical Method Based on Artificial Neural Networks for Power Output Prediction of a Combined Cycle Power Plant International Journal of Monitoring and Surveillance Technologies Research. 4: 20-32 |
| Fainti R, Alamaniotis M, Tsoukalas LH. (2016) Backpropagation Neural Network for Interval Prediction of Three-Phase Ampacity Level in Power Systems International Journal of Monitoring and Surveillance Technologies Research. 4: 1-20 |
| Nasiakou A, Alamaniotis M, Tsoukalas L. (2016) Extending the K-Means Clustering Algorithm to Improve the Compactness of the Clusters Journal of Pattern Recognition Research. 11: 61-73 |
| Alamaniotis M, Tsoukalas LH. (2016) Fusion of Gaussian Process Kernel Regressors for Fault Prediction in Intelligent Energy Systems International Journal On Artificial Intelligence Tools. 25: 1650023 |