Publications
2023
Prantikos, K.; Chatzidakis, S.; Tsoukalas, L.H.; Heifetz, A. Physics-Informed Neural Network with Transfer Learning (TL-PINN) Based on Domain Similarity Measure for Prediction of Nuclear Reactor Transients. Scientific Reports 2023, 13, 16840.
Laitsos, V.; Vontzos, G.; Bargiotas, D.; Daskalopulu, A.; Tsoukalas, L.H. Enhanced Automated Deep Learning Application for Short-Term Load Forecasting. Mathematics 2023, 11, 2912.
Appiah, R.; Heifetz, A.; Kultgen, D.; Tsoukalas, L.H.; Vilim, R. Heat Transfer Model of Liquid Sodium Purification and Diagnostic System for Advanced Reactor Control Applications. In Proceedings of the 2023 American Nuclear Society Winter Meeting, Washington, D.C., USA, 12–15 Nov 2023.
Prantikos, K.; Lee, T.; Catalan, D.; Hua, T.; Tsoukalas, L.H.; Heifetz, A. Characterization of Noise in Optical Fiber Measurements for Machine Learning Data Set Development. In Proceedings of the 2023 American Nuclear Society Winter Meeting, Washington, D.C., USA, 12–15 Nov 2023.
Pantopoulou, M.; Kultgen, D.; Tsoukalas, L.H.; Heifetz, A. Comparison of Exponential Smoothing and GRU-Based Monitoring of Liquid Sodium Heater Zones. In Proceedings of the 2023 American Nuclear Society Winter Meeting, Washington, D.C., USA, 12–15 Nov 2023.
Pantopoulou, S.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Efficient Compression of Reactor Vessel Monitoring Sensor Data Using Machine Learning. In Proceedings of the 2023 American Nuclear Society Winter Meeting, Washington, D.C., USA, 12–15 Nov 2023.
Appiah, R.; Heifetz, A.; Kultgen, D.; Vilim, R.; Tsoukalas, L. Preliminary Development of Heat Transfer Model-Based Control Algorithms of Liquid Sodium Purification System: Advanced Sensors and Instrumentation Advanced Controls; 2023; p. ANL/NSE-23/87, 2212452, 185322.
Prantikos, K.; Lee, T.; Heifetz, A. Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging Using Synthetic Data; 2023; p. ANL/NSE-23/86, 2205614, 186205.
Appiah, R.; Heifetz, A.; Nguyen, T.; Ponciroli, R.; Ley, H.; Kultgen, D.; Vilim, R. Advanced Monitoring and Control in the ANL METL Facility Using an Engineering Digital Twin; 2023; p. ANL/NSE-23/80, 2204284, 185807.
Prantikos, K.; Lee, T.; Heifetz, A. Conceptual Machine Learning Strategy for Maintenance of Molten Salt Heat Exchanger; 2023; p. ANL/NSE--23/44, 1995454, 183742.
Walker, C.; Appiah, R.; Agarwal, V. Development of a Scalable, Risk-informed, Predictive Maintenance Cloud based Strategy at Nuclear Power Plants. In Proceedings of the 2023 American Nuclear Society 13th Nuclear Plant Instrumentation, Control, & Human-Machine Interface Technologies, Knoxville, TN, USA, 15-20 July 2023.
Pantopoulou, M.; Kultgen, D.; Tsoukalas, L.H.; Heifetz, A. Comparison of ARIMA and LSTM Performance in Monitoring of Piping Heater Zones of a Liquid Sodium Loop. In Proceedings of the 2023 American Nuclear Society Annual Meeting, Indianapolis, IN, USA, 11–14 June 2023.
Prantikos, K.; Lee, T.; Tsoukalas, L.H.; Heifetz, A. Conceptual Machine Learning-Based Strategy for Molten Salt Heat Exchanger Channel Plugging Detection and Localization. In Proceedings of the 2023 American Nuclear Society Annual Meeting, Indianapolis, IN, USA, 11–14 June 2023.
Pantopoulou, S.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Comparison of SVM and LSTM Performance in Monitoring of Thermal Hydraulic Sensors. In Proceedings of the 2023 American Nuclear Society Annual Meeting, Indianapolis, IN, USA, 11–14 June 2023.
2022
Prantikos, K.; Tsoukalas, L.H.; Heifetz, A. Physics-Informed Neural Network Solution of Point Kinetics Equations for a Nuclear Reactor Digital Twin. Energies 2022, 15, 7697.
Pantopoulou, S.; Ankel, V.; Weathered, M.T.; Lisowski, D.D.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Monitoring of Temperature Measurements for Different Flow Regimes in Water and Galinstan with Long Short-Term Memory Networks and Transfer Learning of Sensors. Computation 2022, 10, 108.
Kontogiannis, D.; Bargiotas, D.; Daskalopulu, A.; Arvanitidis, A.I.; Tsoukalas, L.H. (2022). Structural Ensemble Regression for Cluster-Based Aggregate Electricity Demand Forecasting. Electricity 2022, 3, 480-504.
Kontogiannis, D.; Bargiotas, D.; Daskalopulu, A.; Arvanitidis, A.I.; Tsoukalas, L.H. (2022). Error Compensation Enhanced Day-Ahead Electricity Price Forecasting. Energies 2022, 15, 1466.
Arvanitidis, A.I.; Bargiotas, D.; Daskalopulu, A.; Kontogiannis, D.; Panapakidis, I.P.; Tsoukalas L.H. (2022). Clustering Informed MLP Models for Fast and Accurate Short-Term Load Forecasting. Energies 2022, 15, 1295.
Daskalopulu, A.; Tsoukalas, L.H.; Bargiotas, D. Normative and Fuzzy Components of Medical AI Applications. In Handbook on Artificial Intelligence-Empowered Applied Software Engineering; Virvou, M., Tsihrintzis, G.A., Bourbakis, N.G., Jain, L.C., Eds.; Springer International Publishing: Cham, 2022; Vol. 3, pp. 167–184 ISBN 9783031076497.
Sgourou, E.N.; Daskalopulu, A.; Tsoukalas, L.H.; Stamoulis, G.; Vovk, R.V.; Chroneos, A. Seventy-Five Years since the Point-Contact Transistor: Germanium Revisited. Appl. Sci. 2022, 12, 11993.
Appiah, R.; Walker, C.; Agarwal, V.; Nistor, J.; Gruenwald, T.; Muhlheim, M.; Ramuhalli, P. Development of a Cloud-Based Application to Enable a Scalable Risk-Informed Predictive Maintenance Strategy at Nuclear Power Plants; 2022; p. INL/RPT-22-70543-Rev000, 1906501.
Appiah, R.; Oktavian, M.R.; Tsoukalas, L.H.. Neuro-Fuzzy Predictive Power Controller for a Nuclear Research Reactor. In Proceedings of the 2022 American Nuclear Society Winter Meeting, Phoenix, AZ, USA, 13–17 Nov 2022.
Prantikos, K.; Tsoukalas, L.H.; Heifetz, A. Forecasting of Nuclear Reactor Outages using Machine Learning. In Proceedings of the 2022 American Nuclear Society Winter Meeting, Phoenix, AZ, USA, 13–17 Nov 2022.
Pantopoulou, M.; Kultgen, D.; Tsoukalas, L.H.; Heifetz, A. Machine Learning-Based Monitoring of Liquid Sodium Vessel Heater Zones. In Proceedings of the 2022 American Nuclear Society Winter Meeting, Phoenix, AZ, USA, 13–17 Nov 2022.
Pantopoulou, S.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Transfer Learning Long Short-Term Memory (TL-LSTM) Network for Molten Salt Reactor Sensor Monitoring. In Proceedings of the 2022 American Nuclear Society Winter Meeting, Phoenix, AZ, USA, 13–17 Nov 2022.
Prantikos, K.; Tsoukalas, L.H.; Heifetz, A. Physics-Informed Neural Network Solution of Point Kinetics Equations for Development of Small Modular Reactor Digital Twin. In Proceedings of the 2022 American Nuclear Society Annual Meeting, Anaheim, CA, USA, 12–16 June 2022.
Roberts, M; Pantopoulou, M.; Tsoukalas, L.H.; Heifetz, A. Wireless Quantum Key Distribution for Small Modular Reactor Secure Communications. In Proceedings of the 2022 American Nuclear Society Annual Meeting, Anaheim, CA, USA, 12–16 June 2022.
Pantopoulou, S.; Lisowski, D.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Augmented Data Generation for Thermocouple Sensors Time Series with Generative Adversarial Network. In Proceedings of the 2022 American Nuclear Society Annual Meeting, Anaheim, CA, USA, 12–16 June 2022.
Oktavian Muhammad Rizki, Appiah Rita, Lastres Oscar, Miller True, Chapman Alec, Tsoukalas Lefteri H.” Fuzzy Power Controller Design for Purdue University Research Reactor-1”, International Journal of Nuclear and Quantum Engineering, Vol:16, No:5, 2022.
2021
Pantopoulou, S.; Lisowski, D.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. LSTM Validation of Fiber Optics Distributed Temperature Sensing. In Proceedings of the 2021 American Nuclear Society Winter Meeting, Washington, DC, USA, 1–3 Dec 2021.
Lagari, P-L., Alamaniotis, M., Pantopoulou, S., Tsoukalas, L.H., “A Library of Radionuclide Gamma Profiles for the Identification of Unknown Sources,” Nuclear Technology, 2021.
Pantopoulou, S., Pantopoulou, M., & Tsoukalas, L. H. (2021, July). Secure Decision Making and Inference in Critical Systems. In 2021 12th International Conference on Information, Intelligence, Systems and Applications (IISA) IEEE.
Lagari, P-L., & Tsoukalas, L. H. (2021, July). Neural Network Solution of Partial Differential Equations in Non-Rectangular Domains via Unconstrained Training. In 2021 12th International Conference on Information, Intelligence, Systems and Applications (IISA) IEEE.
2020
Lagari, P-L., Tsoukalas, L.H., Lagaris, I.E., “Variance Counterbalancing for Stochastic Large-Scale Learning,” International Journal on Artificial Intelligence Tools, World Scientific, 2020
Lagari, P-L., Tsoukalas, Safarkhani, S., L.H., Lagaris, I.E., “Systematic Construction of Neural Forms for Solving Partial Differential Equations inside Rectangular Domains, Subject to Initial, Boundary and Interface Conditions,” International Journal on Artificial Intelligence Tools, World Scientific, 2020
Pantopoulou, S., Lagari, P. L., Townsend, C. H., & Tsoukalas, L. H. (2020, July). Critical Systems under Cyber Threats. In 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA (pp. 1-4). IEEE.
Pantopoulou, S., Lagari, P. L., Townsend, C. H., & Tsoukalas, L. H. (2020, October). Data-Based Defense-in-Depth of Critical Systems. In International Conference on Dynamic Data Driven Application Systems (pp. 283-290). Springer, Cham.
2019
Townsend, C., Bean R., PUR-1: A fully digital I&C installation driving innovation, Nuclear News, ANS, February 2019, pp. 37-39
Kuganathan, N., Tsoukalas, L.H., Chroneos, A., “Defects, Dopants and Li-ion diffusion in Li2SiO3,” Journal of Solid States Ionics, Elsevier, July 2019.
2018
Mathew, J., Griffin, J., Alamaniotis, M., Kanarachos, S., Fitzpatrick, M., Prediction of welding residual stresses using machine learning: Comparison between neural networks and neuro-fuzzy systems, Applied Soft Computing Journal, Elsevier, vol. 70, September 2018, pp. 131-146.
Alamaniotis, M., Data Interpretation and Algorithms, Active Interrogation in Nuclear Security-Science, Technology, and Systems, Book edited by I. Jovanovic and A. Erickson, Springer Nature, 2018, pp. 249-278.
Alamaniotis, M., Karagiannis, G., "Genetic Driven Multi-Relevance Vector Regression Forecasting of Hourly Wind Speed in Smart Power Systems", IEEE PES Innovative Smart Grid Technologies – North America, 2018, pp. 1-5.
Lagari, P., Weidenbenner, S., Alamaniotis, M., Choi, C., Tsoukalas, L.H., "Testing the sensitivity of a neural based identification algorithm to shielding levels", American Nuclear Society Annual Meeting, Philadelphia, PA, USA, June 2018, pp. 779-782.
Fainti, R., Karasimou, M., Tsionas, I., Tsoukalas, L.H. Alamaniotis, M., "Load Management of Electric Vehicles Charging in New Generation Power Markets based on Fuzzy Logic and the Concept of Virtual Budget", 9th International Conference on Information, Systems and Applications (IISA), Zakynthos, Greece, July 2018, pp. 1-7. Invited
Alamaniotis, M., Tsoukalas, L.H., "Peak Locating in Gamma-Ray Spectra Using Wavelet Processing and Support Vector Regression with Applications to Nuclear Nonproliferation", Advances in Nuclear Nonproliferation and Policy Conference, Orlando, FL, USA, November 11-15, 2018, pp. 1-4. Accepted
Verney-Provatas, A., Alamaniotis, M., Choi C.K., Tsoukalas, L.H., "A Simulation Platform for Data Generation in Analysis of Detection Algorithms in Radioactive Source Search", American Nuclear Society Winter Meeting, Orlando, FL, USA, November 11-15, 2018, pp. 1-3. Accepted
Alamaniotis, M., Mathew, J., Chroneos, A., Fitzpatrick, M., Tsoukalas, L.H., Probabilistic Kernel Machines for Predictive Monitoring of Weld Residual Stress in Energy Systems, Engineering Applications of Artificial Intelligence, Elsevier, 2018, pp. 1-28
Alamaniotis, M., Gatsis, N., Tsoukalas, L.H., Virtual Budget: Integration of Electricity Load and Price Anticipation for Load Morphing in Price-Directed Energy Utilization, Electric Power Systems Research, Elsevier, vol. 158, 2018, pp. 284-296.
Mathew, J., Parfitt, D., Wilford, K., Riddle, N., Alamaniotis, M., Chroneos, A., Fitzpatrick, M., Reactor Pressure Vessel Embrittlement: Insights from Neural Network Modelling, Journal of Nuclear Materials, Elsevier, 2018, pp. 1-15.
Alamaniotis, M., Cappelli, M., Intelligent Identification of Boiling Water Reactor State Utilizing Relevance Vector Machines, ASME Journal of Nuclear Engineering and Radiation Science, American Society of Mechanical Engineers, vol. 4, April 2018, pp. [020904]1-9.
2017
Alamaniotis, M., Tsoukalas, L.H., Assessment of Gamma-Ray Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures, Critical Developments and Applications of Swarm Intelligence, Book edited by Yuhui Shi, IGI-Global, 2017. Accepted
Alamaniotis, M., Cappelli, M., Intelligent Identification of Boiling Water Reactor State Utilizing Relevance Vector Machines, ASME Journal of Nuclear Engineering and Radiation Science, American Society of Mechanical Engineers, 2017, pp. 1-15. Accepted
Alamaniotis, M., Tsoukalas, L.H., Multi-Kernel Assimilation for Predictive Intervals in Nodal Short Term Load Forecasting, IEEE International Conference on Intelligent System Application to Power Systems (ISAP 2017), San Antonio, TX, USA, September 2017, pp. 1-6. Accepted
Fainti, R., Alamaniotis, M., Tsoukalas, L.H., Three-Phase Line Overloading Predictive Monitoring utilizing Artificial Neural Networks, IEEE International Conference on Intelligent System Application to Power Systems (ISAP 2017), San Antonio, TX, USA, September 2017, pp. 1-6.
Alamaniotis, M., Tsoukalas, L.H., Utilization of Virtual Buffer in Local Area Grids for Electricity Storage in Smart Power Systems, 49th North American Power Symposium, Morgantwon, WV, USA, September 2017, pp. 1-6. Accepted
Agarwal, V., Raymond, A., Tsoukalas, L.H., Modeling Energy Consumption and Lifetime of a Wireless Sensor Node Operating on a Contention-Based MAC Protocol, IEEE Sensors Journal, vol. 17(16), 2017, pp. 5153-5168.
Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., Karagiannis, G., A Three-Stage Scheme for Consumers' Partitioning Using Hierarchical Clustering Algorithm, 8th International Conference on Information, Systems and Applications (IISA), Larnaca, Cyprus, August 2017, pp. 1-6. Accepted
Fainti, R., Alamaniotis, M., Tsoukalas, L.H., Karasimou, M., Tsionas, I., Ampacity Level Monitoring Utilizing Fuzzy Logic Theory in Deregulated Power Markets, 8th International Conference on Information, Systems and Applications (IISA), Larnaca, Cyprus, August 2017, pp. 1-6. Accepted
Nasiakou, A., Bean, R., Alamaniotis, M., "Development of Human Machine Interface (HMI) for Digital Control Rooms in Nuclear Power Plants", 10th International Topical Meeting on Nuclear Power Plant Instrumentation, Control and Human Machine Interface Technologies (NPIC & HMIT 2017), San Fracncisco, CA, June 11-15, 2017, pp. 1-10. Accepted
Alamaniotis, M., Bourbakis, N., Tsoukalas, L.H., Anticipatory Driven Nodal Electricity Load Morphing in Smart Cities Enhancing Consumption Privacy, IEEE PES PowerTech Conference, Manchester, UK, June 18-22, 2017, pp.1-6. Accepted
Bourbakis, N., Alamaniotis, M., Tsoukalas, L.H., A Smart Car Model based on Autonomous Agents for Reducing Accidents, IEEE Transportation Electrification Conference & Expo, Chicago, Il, USA, June 22-24, 2017, pp.1-6. accepted
Alamaniotis, M., Tsoukalas, L.H., Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbances of Cyber-Attacks in Smart Power Systems using Gaussian Processes and Fuzzy Inference, Data Analytics and Decision Support for Cybersecurity – Trends, Methodologies and Applications, Book edited by Ivan Palomares, Springer, 2017. in press
2016
Lagari, P.L., Sobes, V., Alamaniotis, M., Tsoukalas, L.H., Application of Artificial Neural Networks for Reliable Nuclear Data for Nonproliferation Modeling and Simulation, International Journal of Monitoring and Surveillance Technologies Research, (IJMSTR), December 2016
Fainti, R., Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., 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 (IJMSTR), December 2016
Chatzidakis, S., Choi, C. K., Tsoukalas, L.H., Analysis of Spent Nuclear Fuel Imaging Using Multiple Coulomb Scattering of Cosmic Muons, IEEE Transactions on Nuclear Science, vol. 63(6), pp. 2866-2874, December. 2016.
Alamaniotis, M., Tsoukalas, L.H., Anticipatory system for detection of hidden facilities utilizing nodal load consumption information in smart grids, IEEE Global Conference on Signal and Information Processing (GlobalSip), Washington D.C., USA, December 2016, pp. 1-5. Accepted.
Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., Extending the k-means Clustering Algorithm to Improve the Compactness of the Clusters, Journal of Pattern Recognition Research, November 2016. Accepted
Nasiakou, A., Vavalis M., Zimeris, D., Smart energy for smart irrigation, Computers and Electronics in Agriculture, vol. 129, November 2016, pp. 74-83.
Alamaniotis, M., Tsoukalas, L.H., Buckner, M., Privacy-Driven Electricity Group Demand Response in Smart Cities Using Particle Swarm Optimization, IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2016), San Jose, CA, USA, November 2016, pp. 1-8. Accepted
Belligianni, F., Alamaniotis, M., Fevgas, A., Tsompanopoulou, Bozanis, P., Tsoukalas, L.H., An Internet of Things Architecture for Preserving Privacy of Energy Consumption, 10th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (Med Power 2016), Belgrade, Serbia, November 6-9, 2016. Accepted
Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., Power Distribution Network Partitioning In Big Data Environment using k-means and Fuzzy Logic, The 10th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, November 2016. Accepted.
Fainti, R., Alamaniotis, M., Tsoukalas, L.H., Distribution Congestion Prediction Using Artificial Neural Networks for Big Data, The 10th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, November 2016. Accepted.
Alamaniotis, M., Tsoukalas, L.H., Implementing Smart Energy Systems: Integrating Load and Price Forecasting for Single Parameter based Demand Response, IEEE PES Innovative Smart Grid Technologies, Europe, (ISGT 2016), Ljubljana, Slovenia, October 9-12, 2016. Accepted.
Alamaniotis, M., Nasiakou, A., Fainti, R., Tsoukalas, L.H., Leaky Bucket Approach Implementing Anticipatory Control for Nodal Power Flow Management in Smart Energy Systems, IEEE PES Innovative Smart Grid Technologies, Europe (ISGT 2016), Ljubljana, Slovenia, October 9-12, 2016. Accepted.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., "Developing Intelligent Non-proliferation Enabling Capabilities: Very-Short-Term Prediction of Background Radiation in Radioactive Source Search Using Relevance Vector Regression", Advances in Nuclear Nonproliferation Technology and Policy Conference (ANTPC), Santa Fe, NM, USA, September 25-30, 2016. Accepted.
Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., Vavalis, M., "Dynamic Data Driven Partitioning of Smart Grid Using Learning Methods", 1st Conference in Dynamic Data Driven Application Systems, Hartford, Connecticut, August 2016. Accepted
Fainti, R., Alamaniotis, M., Tsoukalas, L.H., Backpropagation Neural Network for Interval Prediction of Three-Phase Ampacity Level in Power Systems, International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), August 2016, Accepted.
Lagari, P. L., Nasiakou, A., Alamaniotis, M., Evaluation of Human Machine Interface (HMI) on a Digital and Analog Control Room in Nuclear Power Plants Using a Fuzzy Logic Approach, Accepted in International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), August 2016.
Alamaniotis, M., Tsoukalas, L.H., Fusion of Gaussian Process Kernel Regressors for Fault Prediction in Intelligent Energy Systems, International Journal on Artificial Intelligence Tools, World Scientific Publishing Company, August 2016.
Chatzidakis, S., Choi, Tsoukalas L.H., Interaction of cosmic ray muons with spent nuclear fuel dry casks and determination of lower detection limit, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 828:37–45, August 2016.
Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H., MatGridGUI - A Toolbox for GridLAB-D Simulation Platform, The 7th International Conference on Information, Intelligence, Systems and Applications, July 2016.
Fainti, V., Alamaniotis, M., Tsoukalas, L.H., Three Phase Congestion Prediction Utilizing Artificial Neural Networks, The 7th International Conference on Information, Intelligence, Systems and Applications, July 2016.
Lagari, P. L., Nasiakou, A., Fainti, R., Mao, K., Tsoukalas, L.H., Bean, R., Alamaniotis, M., Evaluation of Human Machine Interface (HMI) in Nuclear Power Plants with Fuzzy Logic Method, 7th International Conference on Information, Intelligence, Systems and Applications, July 2016.
Mattingly, J., Hutchinson, J., Sullivan, C., Stinnett, J., Kamuda, M., Alamaniotis, M., Sims, B., Mueller, J., Newby, J., Linkous, J., Pozzi, S., Polack, K., Hamel, M., He, Z., Goodman, D., Streicher, M., "CNEC and CVT Subcritical Experiments with Category I Special Nuclear Material at the Nevada National Security Site Device Assembly Facility", Institute of Nuclear Materials Annual Conference, July 2016. Accepted.
Alamaniotis, M., Tsoukalas, L.H., Multi-Kernel Anticipatory Approach to Intelligent Control with Application to Load Management of Electrical Appliances, 16th Mediterranean Conference on Control and Automation, Athens, Greece, June 21-25, 2016. Accepted.
Alamaniotis, M., Cappelli, M., Real-Time State Identification of Boiling Water Reactors Using Relevance Vector Machines, 24th American Society of Mechanical Engineers International Conference on Nuclear Engineering (ICONE), Charlotte, NC, USA, June 2016, pp. 1-8. Accepted
Chatzidakis, S., Choi, C., Tsoukalas, L.H., "Theoretical Investigation of Spent Nuclear Fuel Monitoring using Cosmic Ray Muons", International Congress on Advances in Nuclear Power Plants. April 2016.
Lagari, P. L., Mao, K., Tsoukalas, L.H., Alamaniotis M., "Fuzzy Logic Method for Joint Human Machine Interface Evaluation in Nuclear Power Plants", ANS Student Conference, March 2016.
Alamaniotis, M., Bargiotas, D., Tsoukalas, L.H., Towards Smart Energy Systems: Application of Kernel Machine Regression for Medium Term Electricity Load Forecasting, SpringerPlus – Engineering, Springer, vol. 5(1), January 2016, pp. 1-15.
M.W.D. Cooper, M.E. Fitzpatrick, L.H. Tsoukalas, A. Chroneos., Oxygen self-diffusion in ThO2 under pressure: connecting point defect parameters with bulk properties, Materials Research Express, vol. 3(6), 2016.
Alamaniotis, M., Chatzidakis, S., Tsoukalas, L., Data Driven Monitoring of Complex Energy Systems: Gaussian Process Kernel Machines for Fault Identification with Application to Boiling Water Reactors, Intelligent Computing Systems, Book edited by G. Tsihrintzis, and M. Virvou, Studies in Computational Intelligence, vol. 627, Springer: Berlin, Chapter 8, pp. 177-188.
2015
Alamaniotis, M., Bourbakis, N., Tsoukalas, L.H., Very-Short Term Forecasting of Electricity Price Signals Using a Pareto Composition of Kernel Machines in Smart Power Systems, 3rd IEEE Global Conference on Signal and Information Processing, Orlando, FL, December 2015, pp. 780-784.
Alamaniotis, M., Bargiotas, D., Bourbakis, N., Tsoukalas, L.H., Genetic Optimal Regression of Relevance Vector Machines for Electricity Price Forecasting in Smart Grids, IEEE Transactions on Smart Grid, Institute of Electrical and Electronic Engineers, vol. 6(6), November 2015, pp. 2997-3005.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., Short-Term Gamma Background Anticipation Using Learning Gaussian Processes, IEEE Nuclear Science Symposium & Medical Imaging Conference, San Diego, CA, November 2015, pp. 1-2. Accepted
Alamaniotis, M., Tsoukalas, L.H., Developing Intelligent Radiation Analysis Systems: A Hybrid Wave-Fuzzy Methodology for Analysis of Radiation Spectra, 27th International Conference on Tools with Artificial Intelligence, Vietri Sul Mare, Italy, November 2015, pp. 1114-1121.
Alamaniotis, M., Tsoukalas, L.H., Fevgas, A., Tsompanopoulou, P., Bozanis, P., Multiobjective Unfolding of Shared Power Consumption Pattern using Genetic Algorithm for Estimating Individual Usage in Smart Cities, 27th International Conference on Tools with Artificial Intelligence, Vietri Sul Mare, Italy, November 2015, pp. 398-404.
Chatzidakis, S., Forsberg, P., Tsoukalas, L.H., Artificial neural networks and chaos dynamics for signal encryption, Nucl. Technol., vol. 192(1), October 2015, pp. 61-73.
Chrysikou, V., Alamaniotis, M., Tsoukalas, L.H., A Review of Incentive based Demand Response Methods in Smart Electricity Grids, International Journal of Monitoring and Surveillance Technologies Research, IGI Global Publications, vol. 3(4), October 2015, pp. 61-72.
Chatzidakis, S., Chrysikopoulou, S., Tsoukalas, L.H., Developing a cosmic ray muon sampling capability for muon tomography and monitoring applications, Nuclear Instruments and Methods in Physics Research Section A, vol. 804, December 2015, pp. 33-42,
Bourbakis, N., Ktistakis-Papadakis, I., Tsoukalas, L.H., Alamaniotis, M., An Autonomous Intelligent Wheelchair mounted with Robotic Arms for Smart Homes, International Conference on Information, Intelligence, Systems and Applications, Corfu, Greece, July 2015, pp. 1-7.
Alamaniotis, M., Tsoukalas, L.H., Anticipation of Minutes-Ahead Household Active Power Consumption Using Gaussian Processes, International Conference on Information, Intelligence, Systems and Applications, Corfu, Greece, July 2015, pp. 1-6.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., Anomaly Detection in Radiation Signals Using Kernel Machine Intelligence, Workshop on Advances in Machine Learning – International Conference on Information, Intelligence, Systems and Applications, Corfu, Greece, July 2015, pp. 1-6.
Alamaniotis, M., Lee, S., Jevremovic, T., Intelligent Analysis of Low Count Scintillation Spectra using Support Vector Regression and Fuzzy Logic, Nuclear Technology, American Nuclear Society, vol. 191(1), July 2015, pp. 41-57.
Chatzidakis, S., Forsberg, P.T., Sims, B.T., Tsoukalas, L.H., Monte Carlo simulations of cosmic ray muons for dry cask monitoring, Transactions of the American Nuclear Society, June 2015, vol. 112, pp. 534-536.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., A New Approach in Gamma Ray Spectra Analysis: Automated Integration of Peak Detection and Spectrum Fitting using Fuzzy Logic and Multiple Linear Regression, Transactions of the American Nuclear Society Annual Meeting, San Antonio, TX, USA, June 7-11, 2015, pp. 260-263.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., Data Driven Modeling of Radiation Background using an Ensemble of Learning Methods: Initial Concepts and Preliminary Results, Transactions of the American Nuclear Society Annual Meeting, San Antonio, TX, USA, June 7-11, 2015, pp. 249-252.
Alamaniotis, M., Jevremovic, T., Hybrid Fuzzy-Genetic Approach Integrating Peak Identification and Spectrum Fitting for Complex Gamma-Ray Spectra Analysis, IEEE Transactions on Nuclear Science, Institute of Electrical and Electronic Engineers, vol. 62(3), June 2015, pp. 1262-1277.
Alamaniotis, M., Tsoukalas, L.H., Agarwal, V., Predictive based Monitoring of Nuclear Plant Component Degradation Using Support Vector Regression, 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human Machine Interface Technologies (NPIC&HMIT 2015), American Nuclear Society, Charlotte, NC, USA, February 2015, pp. 1199-1207.
Chatzidakis, S., Alamaniotis, M., Tsoukalas, L.H., An Operator's Support System for Reactor Transients using Fuzzy Logic, 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human Machine Interface Technologies (NPIC&HMIT 2015), American Nuclear Society, Charlotte, NC, USA, February 2015, pp. 2148-2154.
Alamaniotis, M., Jin. X., Ray, A., n-line Condition Monitoring of Boiling Water Reactors Using Symbolic Dynamic Analysis, 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human Machine Interface Technologies (NPIC&HMIT 2015), American Nuclear Society, Charlotte, NC, USA, February 2015, pp. 722-732.
Chroneos, A., Fitzpatrick, M.E., Tsoukalas, L.H., Describing oxygen self-diffusion in PuO2 by connecting point defect parameters with bulk properties, Journal of Materials Science: Materials in Electronics, vol. 26(5), 2015, pp. 3287–3290.
2014
Bourbakis, N., Tsoukalas, L.H., Alamaniotis, M., Gao, R., Kerkman, K., DEMOS: A distributed Model based on Autonomous, Intelligent Agents with Monitoring and Anticipatory Responses for Energy Management in Smart Cities, International Journal of Monitoring and Surveillance Technologies Research, IGI Global Publications. vol. 2(4), October-December 2014, pp. 80-97.
Alamaniotis, M., Chatzidakis, S., Tsoukalas, L.H., Monthly Load Forecasting Using Gaussian Process Regression, 9th Mediterranean Conference on Power Generation, Transmission, Distribution, and Energy Conversion: MEDPOWER 2014, November 2014, Athens, Greece, pp. 1-7.
Alamaniotis, M., Tsoukalas, L.H., Integration of Price Anticipation and Self-Elasticity for Hour-Ahead Electricity Bidding and Purchasing, 9th Mediterranean Conference on Power Generation, Transmission, Distribution, and Energy Conversion: MEDPOWER 2014, November 2014, Athens, Greece, pp. 1-6.
Chatzidakis, S., Alamaniotis, M., Tsoukalas, L.H., A Bayesian Approach to Monitoring Spent Fuel Using Cosmic Ray Muons, American Nuclear Society Winter Meeting and Nuclear Technology Expo, November 2014, Anaheim, CA, USA, pp. 369-370.
Hainoun, A., Doval, A., Umbehaun, P., Chatzidakis, S., Ghazi, N., Park, S., Mladin, M., Shokr, A., International benchmark study of advanced thermal hydraulic safety analysis codes against measurements on IEA-R1 research reactor, Nuc. Eng. Des., Vol. 280, October 2014, pp. 233-250.
Alamaniotis, M., Grelle, A., Tsoukalas, L.H., Regression to Fuzziness Method for Estimation of Remaining Useful Life in Power Plant Components, Mechanical Systems and Signal Processing, Elsevier, vol. 48 (1-2), October 2014, pp. 188-198.
Alamaniotis, M., Tsoukalas, L.H., Bourbakis, N., Virtual Cost Approach: Electricity Consumption Scheduling in Smart Grids for Price Directed Electricity Markets, in Proceedings of the 5th International Conference on Information, Intelligence, Systems and Applications, July 2014, Chania, Greece, pp. 38-43.
Chatzidakis, S., Forsberg, P., Tsoukalas, L.H., Chaotic neural networks for intelligent signal encryption, pages 100–105, July 2014.
Chatzidakis, S., Alamaniotis, M., Tsoukalas, L.H., Creep Rupture Forecasting: A Machine Learning Approach to Useful Life Estimation, International Journal of Monitoring and Surveillance Technologies Research, IGI Global Publications, vol. 2(2), April-June 2014, pp. 1-25.
Alamaniotis, M, Agarwal, V., Fuzzy Integration of Support Vector Regressor Models for Anticipatory Control of Complex Energy Systems, International Journal of Monitoring and Surveillance Technologies Research, IGI Global Publications, vol. 2(2), April-June 2014, pp. 26-40.
Alamaniotis, M., Choi, C., Tsoukalas, L.H., Application of Fireworks Algorithm in Gamma-Ray Spectrum Fitting for Radioisotope Identification, International Journal of Swarm Intelligence Research – Special Issue on Developments and Applications of Fireworks Algorithm, IGI Global Publications, vol. 6 (2), April-June 2014, pp. 99-122.
Savva, P., Chatzidakis, S., et al., Optimized flux trap dimensions in a research reactor core, Nucl. Technol., Vol, 188, pp. 322-335.
Chatzidakis, S., Hainoun, A., et al., A comparative assessment of independent thermal-hydraulic models for research reactors: the RSG-GAS case, Nuc. Eng. Des., vol. 268, pp. 77-86.
2013
Chroneos, A., Rushton, M.J.D., Jiang, C., Tsoukalas, L.H., Nuclear wasteform materials: Atomistic simulation case studies, Journal of Nuclear Materials, vol. 441(1-3), May 2013, pp. 29–39.
Ikonomopoulos, A., Alamaniotis, M., Chatzidakis, S., Tsoukalas L.H., Gaussian processes for state identification in pressurized water reactors, Nucl. Technol., vol. 182, April 2013, pp. 1-12.
Chatzidakis, S., Forsberg, P.T., Tsoukalas, L.H., Data encryption of radiation signals using chaotic artificial neural networks, American Nuclear Society (ANS) Student Conference, Boston, MA, April 2013.
Knowles, J., Chatzidakis, S., Defect diffusion simulation through zirconium lattice structure, American Nuclear Society (ANS) Student Conference, Boston, MA, April 2013.
2012
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Swarm Intelligence Optimization: Applications of Particle Swarms in Industrial Engineering and Nuclear Power Plants, in Computational Intelligence Systems in Industrial Engineering, Book edited by Cengiz Kahraman, Springer & Atlantis Press, Chapter 9, November 2012, pp. 181-202.
Young, J., MacKe, C.J., Tsoukalas, L.H., Short-term acoustic forecasting via artificial neural networks for neonatal intensive care units, Journal of the Acoustical Society of America, vol. 132(5), November 2012, pp. 3234–3239.
Alamaniotis, M., Ikonomopoulos, A., Alamaniotis, A., Bargiotas, D., Tsoukalas, L.H., Day-ahead Electricity Price Forecasting using Optimized Multiple-Regression of Relevance Vector Machines, in Proceedings of the 8th Mediterranean Conference on Power Generation, Transmission, Distribution, and Energy Conversion: MEDPOWER 2012, Cagliari, Italy, October 2012, pp. 1-8.
Chatzidakis, S, Ikonomopoulos, A., Alamaniotis. M., An algorithmic approach for RELAP5/MOD3 reactivity insertion analysis in research reactors, Nucl. Technol., Vol. 179, September 2012, pp. 392-406.
Alamaniotis, M., Heifetz, A., Raptis, A., Tsoukalas, L.H., Fuzzy Logic Radio Isotope Identifier for Gamma Spectra Analysis in Source Search Applications, inProceedings of the American Nuclear Society Annual Meeting, Chicago, IL, USA, June 2012, pp. 211-212.
Alamaniotis, M., Heifetz, A., Raptis, A., Tsoukalas, L.H., Background Spectrum Estimation for Low Count Spectra Using Kernel-Modeled Gaussian Processes, inProceedings of the American Nuclear Society Annual Meeting, Chicago, IL, USA, June 2012, pp. 273-274.
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Evolutionary Multiobjective Optimization of Kernel-based Very Short-Term Load Forecasting, IEEE Transactions on Power Systems, Institute of Electrical and Electronic Engineers, vol. 27(3), August 2012, pp. 1477-1484.
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Optimal assembly of support vector regressors with application to system monitoring, International Journal on Artificial Intelligence Tools, 21(6), April 2012.
Young, J., Alamaniotis, M., Tsoukalas, L.H., Fuzzy Logic Detection of Special Nuclear Materials in Aqueous Environments, in Proceedings of the American Nuclear Society Student Conference, Las Vegas, NV, April 2012, pp. 1-2.
Grelle, A., Young, J., Gao, R., Tsoukalas, L.H., Neuro-fuzzy methodology for geospatial and time interpolation on gamma ray spectroscopy data, vol. 106, 2012, pp. 209–210.
Young, J., Alamaniotis, M., Gao, R., Tsoukalas, L.H., Development of path search toolkit for nuclear non-proliferation applications, vol. 106, 2012, pp. 205–206.
2011
Alamaniotis, M., Ikonomopoulos, A., Gao, R., Tsoukalas, L.H., Lessons learned in Accidents: An Intelligent Systems Perspective for Nuclear Power Plant Safety, in Proceedings of the American Nuclear Society Winter Meeting, Washington D.C., November 2011, pp. 305.
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., A Pareto Optimization Approach of a Gaussian Process Ensemble for Short-Term Load Forecasting, in Proceedings of the International Conference on Intelligent System Applications on Power Systems 2011 (ISAP 2011), Crete, Greece, September 2011, pp. 48(1-6).
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Online Surveillance of Nuclear Power Plant Peripheral Components using Support Vector Regression, in Proceedings of the International Symposium on Future I&C for Nuclear Power Plants, Cognitive Systems Engineering on Process Control, and International Symposium on Symbiotic Nuclear Power Systems (ICI 2011), Daejeon, Korea, August 2011, pp. 1230(1-6).
Alamaniotis, M., Ikonomopoulos, A., Jevremovic, T., Tsoukalas, L.H., Intelligent Recognition of Signature Patterns in NRF Spectra, Nuclear Technology, American Nuclear Society, vol. 175 (2), August 2011, pp. 480-497.
Agarwal, V., Tsoukalas, L.H., Smart grids: Importance of power quality, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 54, 2011, pp. 136–143.
2010
Alamaniotis, M., Xiao, S., Young, J., Gao, R., Tsoukalas, L.H., Choe, D., Jevremovic T., Using iMASS to simulate the Tracking/Movement of Special Nuclear Materials, in Proceedings of the American Institute of Chemical Engineers Annual Conference 2010 (AIChE 2010), Salt Lake City, UT, November 2010, pp. 1-6.
Alamaniotis, M., Gao, R., Tsoukalas, L.H., Towards an Energy Internet: A Game-Theoretic Approach to Price-Directed Energy Utilization, in Proceedings of the 1st International ICST Conference on E-Energy, Athens, Greece, October 2010, pp. 3-10.
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Distributed System for Operator Support in Nuclear Power Plants, in Proceedings of the 1st International Conference for Undergraduate and Postgraduate Students in Computer Engineering, Informatics, related Technologies and Applications: EUREKA 2010, Patras, Greece, October 2010, pp. 1-9.
Alamaniotis, M., Ikonomopoulos, A., Tsoukalas, L.H., Gaussian Processes for Failure Prediction of Slow Degradation Components in Nuclear Power Plants, in Proceedings of the European Safety and Reliability Conference 2010 (ESREL 2010), Rhodes, Greece, September 2010, pp. 2096-2102.
Alamaniotis, M., Tsoukalas, L.H., Ikonomopoulos, A., Automated System for Plan Realization in Nuclear Power Plants, in Proceedings of the European Safety and Reliability Conference 2010 (ESREL 2010), Rhodes, Greece, September 2010, pp. 2103-2109.
Alamaniotis, M., Young, J., Tsoukalas, L.H., Jevremovic, T., Assessment of Wavelet Processing in Removing Background Peaks from NRF Spectra, in Proceedings of the American Nuclear Society (ANS) Student Conference, Ann Arbor, MI, April 2010, pp. 1-2.
Alamaniotis, M., Young, J., Tsoukalas, L.H., Jevremovic, T., An Insight in Wavelet Denoising of Nuclear Resonance Spectra for Identification of Hazardous Materials, in Proceedings of the 1st National Conference on Advanced Tools and Solutions for Nuclear Material Detection, Salt Lake City, UT, March 2010, pp. 1-6.
Agarwal, V., Uthaichana, K., Decarlo, R.A. Tsoukalas, L.H., Development and validation of a battery model useful for discharging and charging power control and lifetime estimation, IEEE Transactions on Energy Conversion, 25(3):821–835, 2010.
2009
Pantelopoulos, A., Alamaniotis, M., Jevremovic, T., Park, M.S., Chung, M.S., Bourbakis N., LG-Graph based Detection of NRF Signatures: Initial Results and Comparison, Invited Contribution in Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence, Newark, NJ, November 2009, pp. 683-686.
Alamaniotis, M., Young, J., Perry, J., Xiao, S., Agarwal, V., Forsberg, P., Gao, R., Choi, C., Tsoukalas, L.H., Jevremovic, T., Engineering Solution to Nuclear Material Detection at Ports: Introducing the Novel iMASS Paradigm, Invited Contribution in Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence, Newark, NJ, November 2009, pp. 679-682.
Alamaniotis, M., Gao, R., Tsoukalas, L.H., Jevremovic, T., Intelligent Order-based Method for Synthesis of NRF Spectra and Detection of Hazardous Materials, Invited Contribution in Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence, Newark, NJ, November 2009, pp. 658-665.
Alamaniotis, M., Gao, R., Tsoukalas, L.H., Jevremovic, T., Expert System for Decision Making and Instructing Nuclear Resonance Fluorescence Cargo Interrogation, Invited Contribution in Proceedings of the 21st IEEE International Conference on Tools with Artificial Intelligence, Newark, NJ, November 2009, pp. 666-673.
Alamaniotis, M., Youtsos, M., Gao, R., Tsoukalas L.H., Pseudo Neural Network based Diagnostic System for Two Phase Annular Flow in Nuclear Power Plants, in Proceedings of the International Conference on Optimization Using Exergy-based Methods and Computational Fluid Dynamics, Berlin, Germany, October 2009, pp. 203-208.
Alamaniotis, M., Gao, R., Tsoukalas, L.H., Distributed Intelligence System for Online Action Taking in Non-Anticipated Situations in Nuclear Power Plants, in Proceedings of the ICAPS-2009 Scheduling and Planning Applications Workshop, Thessaloniki, Greece, September 2009, pp. 7-13.
Alamaniotis, M., Gao, R., Jevremovic, T., Tsoukalas, L.H., Intelligent Detection of SNM in Liquid Containers, in Proceedings of the 16th International Conference on Systems, Signals and Image Processing, Chalkida, Greece, June 2009, pp. 1-4.
Pantelopoulos, A., Alamaniotis, M., Bourbakis, N., Jevremovic, T., Heuristic Identification of Nuclear Materials from NRF Spectra, in Proceedings of the American Nuclear Society (ANS) Student Conference, Gainesville, Florida, April 2009, pp. 1-2.
Alamaniotis, M., Terrill, S., Perry, J., Gao, R., Tsoukalas, L.H., Jevremovic, T., A Multisignal Detection of Hazardous Materials for Homeland Security, Journal of Nuclear Technology and Radiation Protection, Vinca Institute, vol. 24 (1), April 2009, pp. 46-55.
Alamaniotis, M., Terrill, S., Gao, R., Jevremovic, T., Automated Multisignal Detection of Special Nuclear Material in Cargo Containers, in Proceedings of the American Nuclear Society (ANS) Student Conference, Gainesville, Florida, April 2009, CD-ROM, pp. 1-2. Best Paper Award.
Forsberg, P., Agarwal, V., Perry, J., Gao, R., Tsoukalas, L.H., Jevremovic, T., Peakseek: A statistical processing algorithm for radiation spectrum peak identification, 2009, pp. 674–678.
2008
Tsoukalas, L.H., Gao, R., Inventing an energy internet: The role of anticipation in human-centered energy distribution and utilization, August 2008, pp. 399–403.
Tsoukalas, L.H., Gao, R., From smart grids to an energy internet: Assumptions, architectures and requirements, April 2008, pp.94–98.
Uhrig, R.E., Tsoukalas, L.H., Gao, R., Multi-intelligent agents: Potential applications to next generation nuclear plants, vol.98, 2008, pp. 87–88.
2007
Junguo, B., Gao, R., Tsoukalas, L.H., Hazardous material identification using a neurofuzzy methodology, International Journal on Artificial Intelligence Tools, vol. 16(5), October 2007, pp. 901-906.
Agarwal, V., Tsoukalas, L.H., Denoising electrical signal via empirical mode decomposition, August 2007.
Gao, R., Tsoukalas, L.H., Implementing virtual buffer for electric power grids, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4487 LNCS:1083–1089, 2007.
Hoffmann, C., Swain, E., Xu, Y., Downar, T., Tsoukalas, L.H., Top, P., Senel, M., Bell, M., Coyle, E., Loop, B., Aliprantis, D., Wasynczuk, O., Meliopoulos, S., Dddas for autonomic interconnected systems: The national energy infrastructure, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4487 LNCS:1074–1082, 2007.
Bougaev, A., Urmanov, A., Tsoukalas, L.H., Gross, K., Method of Key Extraction using R-cloud Classifiers, New Mathematics and Natural Computation, vol. 3(3), pp. 419-426.
2006
Clikeman, F., Bertodano, M., Jevremovic, T., Walter, J., Bougaev, A., Merritt, E., Tritium measurements in neutron-induced cavitation of deuterated acetone, Nuclear Technology, vol. 155(2), April 2006, pp. 248–251.
Agarwal, V., Bougaev, A., Tsoukalas, L.H., Kernel regression based short-term load forecasting, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4132 LNCS - II:701–708, September 2006.
Meliopoulos, A.P.S., Cokkinides, G.J., Wasynczuk, O., Coyle, E., Bell, M., Hoffmann, C., Nita-Rotaru, C., Downar, T., Tsoukalas, L.H, Gao. R., Pmu data characterization and application to stability monitoring, November 2006, pp. 151–158.
Bougaev, A., Urmanov, A., Gross, K.C., Tsoukalas, L.H., Method of key vectors extraction using r-cloud classifiers, 2006, pp. 97–100.
Swain, E.T., Xu, Y., Gao, R., Downar, T.J., Tsoukalas, L.H., The application of neural networks to electric power grid simulation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4132 LNCS - II:736–745, 2006.
2005
Clarke, S., Gao, R., Xu, Y., Tsoukalas, L.H., Downar, T.J., Artificial networks for nuclear source characterization, vol. 93, 2005, pp. 327–328.
Walter, J., Gert, G., Bougaev, A., Hounshel, D., Satvat, N., Tsoukalas, L.H., Bertodano, M., Jevremovic, T., Experimental measurements and mcnp5 modeling of tritium production in deuterated acetone exposed to isotopic neutron source, 2005, pp.1607–1612.
Won, I.-H., Gao, R., Tsoukalas, L.H., Eryurek, E., Kavaklioglu, K., Diagnostic methodology for pump health in nuclear power plant using fuzzy logic, vol. 92, 2005, pp. 391–392.
Won, I.-H., Gao, R., Tsoukalas, L.H., Eryurek, E., Kavaklioglu, K., Incipient cavitatiqn detection methodology using current sensor based on a neural wavelet approach, vol. 6, 2005, pp. 3243–3249.
2004
Hursin, M., Shanjie, X., Burns, A., Hopkins, J., Satvat, N., Gert, G., Tsoukalas, L.H., and Jevremovic, T. Innovations and enhancements in neutronic analysis of the big-10 university research and training reactors based on the agent code system. vol. 2006, 2006.
Liu, Y., Jevremovic, T., Tsoukalas, L.H., Monte Carlo simulation of particle microbeams probing cellular radiation response, vol. 90, 2004, pp. 447–448.
Wang, X., Sideratos, G., Hatziargyriou, N., and Tsoukalas, L.H., Wind speed forecasting for power system operational planning. 2004, pp.470– 474.
Wang X., and Tsoukalas, L.H., Application of an adaptive neurofuzzy system in transient detection. volume 90, pages 411–412, 2004.
Uhrig, R.E., Gao, R., and Tsoukalas, L.H., Use of multi-agents to improve efficiency and safety of nuclear power plants. pages 241–250, 2004.
2003
Uhrig R.E., Tsoukalas, L.H., Multi-agent-based anticipatory control for enhancing the safety and performance of generation-iv nuclear power plants during long-term semi-autonomous operation. Progress in Nuclear Energy, vol. 43(1-4 SPEC), 2003, pp. 113–120.
Gao, R., Basseas, S., Bargiotas, D.T., Tsoukalas, L.H., Next-generation hearing prosthetics, IEEE Robotics and Automation Magazine, vol. 10(1), March 2003, pp.21-25.
2002
Wang, X., Hatziargyriou, N., Tsoukalas, L.H., A new methodology for nodal load forecasting in deregulated power systems, IEEE Power Engineering Review, vol. 22(5), May 2002, pp. 48-51.
El-Hawary, M.E., Wang, X., Hatziargyriou, N., Tsoukalas, L.H., Power engineering letters. IEEE Power Engineering Review, vol. 22(5), 2002, pp. 48–51.
2001
Gao, R., Tsoukalas, L.H., Neural-wavelet methodology for load forecasting, Journal of Intelligent and Robotic Systems: Theory and Applications, vol 31(1-3), May-July 2001, pp.149-57.
Gao, R., Eryurek, E., Tsoukalas, L.H., A novel neural-wavelet diagnostics approach: application to magnetic flowmeter, International Journal on Artificial Intelligence Tools (Architectures, Languages, Algorithms), vol. 10(3), September 2001, pp.421-429.
Tolias, Y.A., Panas, S.M., Tsoukalas, L.H., Generalized fuzzy indices for similarity matching, Fuzzy Sets and Systems, vol. 120(2), June 2001, pp. 255-70.
Wang, X., Tsoukalas, L.H., Wei, T.Y.C., Reifman, J., An innovative fuzzy-logic-based methodology for trend identification, Nuclear Technology, vol. 135(1), July 2001, pp.67-84.
Mi, Y., Ishii, M., Tsoukalas, L.H., Flow regime identification methodology with neural networks and two-phase flow models, Nuclear Engineering and Design, vol. 204(1-3), February 2001, pp. 87-100.
Mi, Y., Ishii, M., Tsoukalas, L.H., Investigation of vertical slug flow with advanced two-phase flow instrumentation, Nuclear Engineering and Design, vol. 204(1-3), 2001, pp. 69–85.
Tsoukalas, L.H., Modeling the grid as a customer-driven system: Emerging challenges and opportunities for self-healing infrastructures, vol.1, 2001, pp. 158.
Uluyol, O., Ragheb, M., Tsoukalas, L.H., Neural network with local memory for nuclear reactor power level control, Nuclear Technology, vol. 133(2), 2001, pp. 213–228.
2000
Radhakrishnan, A., Viswanathan, V., Gao, R., Tsoukalas L.H., Bassens, S., New generation intelligent hearing prosthetics, 2000, pp. 270– 274.
1999
Uhrig, R.E., Tsoukalas, L.H., Soft computing technologies in nuclear engineering applications, Progress in Nuclear Energy, vol. 34(1), 1999, pp. 13-75.
Gao, R., Liu, Y., Basseas, S. and Tsoukalas, L.H., Neurofuzzy approaches for advanced hearing devices. 1999, pp. 327–331.
Wang, X., Wei, T.Y.C., Reifman, J., Tsoukalas, L.H., Signal trend identification with fuzzy methods. 1999, pp. 332–335.
1998
Pantazopoulos, K.N., Tsoukalas, L.H., Bourbakis, N.G., Brun, M.J, Houstis, E.N., Financial prediction and trading strategies using neurofuzzy approaches, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol. 28(4), August 1998, pp.520-531.
Tsoukalas, L.H., Neurofuzzy approaches to anticipation: a new paradigm for intelligent systems, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol. 28(4), August 1998, pp. 573-82.
Mi, Y., Ishii, M., Tsoukalas, L.H., Vertical two-phase flow identification using advanced instrumentation and neural networks, Nuclear Engineering and Design, vol. 184(2-3), August 1998, pp. 409-420.
Uhrig, R.E., Tsoukalas, L.H., Neurofuzzy approaches and their application to nuclear power systems. Computers and Artificial Intelligence, vol. 17(2-3), 1998, pp. 169–188.
1997
Tsoukalas, L.H., Neurofuzzy anticipatory systems: a new approach to intelligent control, International Journal on Artificial Intelligence Tools (Architectures, Languages, Algorithms), vol. 6(3), September 1997, pp.365-395.
Tsoukalas, L.H., Uhrig, R.E., Hypermedia integration of information resources for nuclear plant operations, Nuclear Technology, vol. 119(1), July 1997, pp. 48-62.
Mi, Y., Ishii, M., Tsoukalas, L.H., A neurofuzzy methodology for impedance-based multiphase flow identification, Engineering Applications of Artificial Intelligence, vol. 10(6), December 1997, pp. 545-55.
Pantazopoulos, K.N., Tsoukalas, L.H., Houstis, E.N., Neurofuzzy characterization of financial time series in an anticipatory framework, 1997, pp. 50–56.
Tsoukalas, L.H., Houstis, E.N., Jones, G.V., Neurofuzzy motion planners for intelligent robots, Journal of Intelligent and Robotic Systems: Theory and Applications, vol. 19(3), 1997, pp. 339–356.
Mi, Y., Tsoukalas, L.H., Ishii, M., Li, M., Xiao, Z., Hybrid fuzzyneural flow identification methodology, vol. 2, 1996, pp. 1332–1338.
1996
Xinqing, L., Tsoukalas, L.H., Uhrig, R.E., Neurofuzzy approach for the anticipatory control of complex systems, vol. 1, 1996, pp. 587–593.
Tsoukalas, L.H. and Bargiotas, D.T., Modeling instructible robots for waste disposal applications, 1996, pp. 202–207.
Mi, Y., Tsoukalas, L.H., Ishii, M., Li, M. and Xiao, Z. Hybrid fuzzyneural flow identification methodology, vol.2, 1996, pp. 1332–1338.
Tsoukalas, L.H., Uhrig, R.E., Fuzzy and Neural Approaches in Engineering, John Wiley & Sons, New York, NY, 1996 (in press).
Tsoukalas, L.H., Jones, G.V., Neurofuzzy Motion Planners for Intelligent Robots, International Journal of Intelligent Systems and Robotics, 1996.
Uhrig, R.E., Tsoukalas, L.H., Applications of Neural and Fuzzy Technologies in Soft Computing, Invited Contribution to Appear in Proc. of IEEE International Workshop in Soft Computing, Muroran, Japan, April 22-26, 1996.
1995
Tsoukalas, L.H., Ikonomopoulos, A., Uhrig, R.E., Neuro-Fuzzy Approaches to Anticipatory Control, Chapter 13 of the Book Artificial Intelligent in Industrial Decision Making, Control and Automation, S. Tzafestas, H. Verbrugen, Eds, Kluwer Academic Publishers, Amsterdam, 1995, pp. 405-419.
Pantopoulou, S.; Cilliers, A.; Tsoukalas, L.H.; Heifetz, A. Comparison of SVM and LSTM Performance in Monitoring of Thermal Hydraulic Sensors. In Proceedings of the 2023 American Nuclear Society Annual Meeting, Indianapolis, IN, USA, 11–14 June 2023.
