Nagi Gebraeel

Georgia Power Early Career Professor

Publications

Journal Publications:

  1. Si, G., Xia, T., Wang, D., Gebraeel, N., Pan, E. and Xi, L., “Maintenance scheduling and vessel routing for offshore wind farms with multiple ports considering day-ahead wind-wave predictions”, Applied Energy, vol. 379, 2025.
  2. Si, G., Xia, T., Gebraeel, N., Wang, D., Pan, E. and Xi, L., “Holistic opportunistic maintenance scheduling and routing for offshore wind farms”, Renewable and Sustainable Energy Reviews, 207, p.114991, 2025.
  3. Rozas H., Xie W., and Gebraeel N., “Condition-based Maintenance for Wind Farms using a Distributionally Robust Chance Constrained Program”, Accepted IEEE Transactions on Power Systems, 2024.
    * INFORMS ENRE Best Student Paper Award, 2023.
  4. Basciftci, B., Ahmed, S. and Gebraeel, N., “Adaptive two-stage stochastic programming with an application to capacity expansion planning”, Accepted Manufacturing and Service Operations Management, 2024, arXiv preprint arXiv:1906.03513.
  5. Karakaya, Ş., Yildirim, M., Gebraeel, N. and Xia, T., “A sensor-driven operations and maintenance planning approach for large-scale leased manufacturing systems”, International Journal of Production Research, pp.1-18, 2024.
  6. Zhang, K., Xia, T., Xu, Y., Ding, Y., Zhao, Y., Gebraeel, N., & Xi, L., “A hybrid prognostic & health management framework across multi-level engineering systems with scalable convolution neural networks and adjustable functional regression models”, Advanced Engineering Informatics, vol. 61, 102566, 2024.
  7. Jiao R., Gong X., and Gebraeel N., “Task Derivation and Decomposition in Crowdsourced Manufacturing by Bilevel Coordinated Optimization of Product Family Planning and Manufacturer Load Balancing”, Computers and Industrial Engineering, vol. 190, p.110101, 2024.
  8. Ibrahim M., Rozas H., and Gebraeel N., “An Integrated Detection-Prognostics Methodology for Components with Intermittent Faults”, ASME Journal of Computing and Information Science in Engineering, vol. 24, no. 6, 2024
  9. Rozas H., Basciftci B., and Gebraeel N., “Data-driven Joint Optimization of Maintenance and Spare Parts Provisioning for Deep Space Habitats: A Stochastic Programming Approach”, Acta astronautica, vol. 214 p.167-181, 2024. 
  10. Zhang K., Xia T., Si G., Gebraeel N., Wang D., Pan E., Xi L., “A Collaborative Scheduling Algorithm for Real-Time Production and Opportunistic Maintenance Under Cloud Manufacturing Paradigm”, IEEE Transactions on Reliability, 2023.
  11. Gebraeel, N., Lei, Y., Li, N., Si, X. and Zio, E., “Prognostics and Remaining Useful Life Prediction of Machinery: Advances, Opportunities and Challenges”, Journal of Dynamics, Monitoring and Diagnostics, vol. 2, no. 1, pp.1-12, 2023.
  12. Gong, X., Wang, S., Jiao, R.J. and Gebraeel, N., “Collaborative contracting for Manufacturing-as-a-Service (MaaS) by information content measurement and decision tree learning”, Advanced Engineering Informatics, 56, p.101911, 2023.
  13. Shi J., Yildirim M., Rozas H., and Gebraeel N., “A Stochastic Programming Model for Jointly Optimizing Maintenance and Spare Parts Inventory for Industrial IoT Applications”, IISE Transactions, vol. 55, no.4 , p. 419 – 431, 2023.
  14. Ramanan P., Yildirim M., and Gebraeel N., “Differentially Private Decentralized Generator Maintenance and Operations for Power Networks”, IEEE Transactions on Control of Network Systems, 2022.
  15. DeShong E., Peters B., Berdanier R. A., Thole K. A., Paynabar K., and Gebraeel N., “Applying Infrared Thermography as a Method for On-Line Monitoring of Turbine Blade Coolant Flow”, Journal of Turbomachinery, 144 (11), p.111009, 2022.
  16. Li D., Gebraeel N., Paynabar K., and Meliopoulos A.P.S., “An Online Approach to Cyberattack Detection and Localization in Smart Grid”,  IEEE Transactions on Power Systems, 38 (1), 267-277, 2022.
    * 2021 IISE Annual Meeting Data Analytics and Information Systems, Best Student Paper Award 
    * 2021 IISE Annual Meeting QCRE Best Student Paper Award (Finalist).
  17. G. Si, Xia T., Gebraeel N., Wang D., Pan E., and Xi L.. “A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems.” Reliability Engineering & System Safety (2022): 108652.
  18. DeShong E., Peters B., Berdanier R. A., Thole K. A., Paynabar K., and Gebraeel N., “Correlating Time-Resolved Pressure Measurements with Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring”, Journal of Turbomachinery, vol. 144, no. 6, p. 061004, 2022
  19. Ramanan P., Li D. and Gebraeel N. “A Decentralized Blockchain based Cyber Threat Detection for Power Systems”, Accepted IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021.
  20. Ramanan P, Yildirim M, Gebraeel N, Chow E. “Large-Scale Maintenance and Unit Commitment: A Decentralized Subgradient Approach”, IEEE Transactions on Power Systems, vol. 37, no. 1, p. 237-248, 2021.
  21. Peters B., Rock N., Emerson B., Gebraeel N., and Paynabar K., “Data Analytics Method for Detecting Extinction Precursors to Lean Blowout in Spray Flames”, published online, Combustion Science and Technology, 2021.
  22. Ashok K., Li D., Divan D., and Gebraeel N., “Online Detection of Inter-turn Winding Faults in Single-Phase Distribution Transformers Using Smart Meter Data”, IEEE Transactions on Smart Grid, vol. 12, no. 6,  p. 5073-5083, 2021.
  23. Li N., Gebraeel N., Lei Y., Fang X., Cai X., and Yan T., “Remaining Useful Life Prediction based on Multi-sensor Data Fusion Model”, Reliability Engineering and Systems Safety, vol. 208, p. 107249, 2021
  24. Li D., Gebraeel N., and Paynabar K., “A Degradation-Based Detection Framework Against Covert Cyberattacks on SCADA Systems”, IISE Transactions, vol. 53, no. 7, p. 812-829, 2021
    * Best Application Paper Award in the 2022 IISE Transactions Transactions Focus Issue on Data Science, Quality and Reliability
    * 2020 Georgia Tech IISP Cybersecurity Summit Best Student Poster Award (Second Prize)
  25. Fang X., Hao Y., Gebraeel N., and Paynabar K., “Multi-Sensor Prognostic Modeling for Applications with Highly Incomplete Signals”, IISE Transactions, vol. 53, no. 5, p. 597-613, 2021.
    * Paper featured in the June 2021 issue of ISE Magazine.
  26. Li N., Lei Y., Gebraeel N., Wang Z., Cai X., Xu P., and Wang B., “Multi-Sensor Data-Driven Remaining Useful Life Prediction of Semi-Observable Systems”, IEEE Transactions on Industrial Electronics, 2020, doi: 10.1109/TIE.2020.3038069.
  27. Li D., Gebraeel N., and Paynabar K., “Detection and Differentiation of Replay Attack and Equipment Faults in SCADA Systems”, Accepted, IEEE Transactions on Automation Science and Engineering, 2020.
    * 2019 IISE Annual Meeting Energy System Best Student Paper Award
    * 2019 IISE Annual Meeting Data Analytics and Information Systems, Best Student Paper Award (Runner-up).
  28. Jiao J., Zhoub F., Gebraeel N. and Duffy D., “Towards Augmenting Cyber-physical-human Collaborative Cognition for Human-Automation Interaction in Complex Manufacturing and Operational Environments”, International Journal of Production Research,  vol. 58, no. 16, p.5089-5111. 2020.
  29. Peters B., Yildirim M., Gebraeel N. and Paynabar K., “Severity-based Diagnostics for Vehicular Electric Systems with Multiple Interacting Fault Modes”, Reliability Engineering and System Safety, vol. 195, p. 106605, 2020.
  30. Fang X., Paynabar K., and Gebraeel N., “Image-Based Prognostics Using Penalized Tensor Regression”, Technometrics, vol. 61, no. 3, p. 369-384, 2019.
    * SAS Data Mining Best Paper Award, INFORMS, 2016
  31. Xia T., Fang X., Gebraeel N., Xi L., and Pan E., “Online Analytics Framework of Sensor-Driven Prognosis and Opportunistic Maintenance for Mass Customization”, Journal of Manufacturing Science and Engineering, 141.5, 2019
  32. Ramanan P., Yildirim M., Chow E., and Gebraeel N., “An Asynchronous, Decentralized Solution Framework for the Large Scale Unit Commitment Problem”, IEEE Transactions on Power Systems, vol. 34, no. 5, p.3677-3686, 2019.
  33. Yildirim M., Gebraeel N., and Xu A., “Leveraging Predictive Analytics to Control and Coordinate Operations, Asset Loading and Maintenance”, IEEE Transactions on Power Systems, vol. 34, no. 6, p.4279-4290, 2019.
  34. Li N., Gebraeel N., Lei Y., and Bian L., “Remaining Useful Life Prediction of Machinery Under Time-Varying Operating Conditions Based on a Two-Factor State-Space Model”, Reliability Engineering and Systems Safety, vol. 186, p. 88-10034, 2019.
  35. Basciftci B., Ahmed S., and Gebraeel N.. “Data-Driven Maintenance and Operations Scheduling under Decision-Dependent Uncertainty”, IISE Transactions, p. 1-14, 2019.
    *2021 Best Paper Award, IIE Transactions in Quality and Reliability Engineering.
  36. Ejaz, I., Alvarado, M., Gautam, N., Gebraeel, N., & Lawley, M., “Condition-Based Maintenance for Queues with Degrading Servers”, IEEE Transactions on Automation Science and Engineering, vol. 16, no. 4, p. 1750-1762, 2019.
  37. Basciftci B., Ahmed S., Gebraeel N., Yildirim M., “Stochastic Optimization of Generator Maintenance and Operations Schedules under Uncertain Failures”, IEEE Transactions on Power Systems, vol. 33, no. 6, p. 6755-6765, 2018.
    * INFORMS ENRE Best Student Paper Award, 2018.
  38. Yang C., Xie Y., and Gebraeel N., “Multi-Sensor Slope Change Detection”, Annals of Operations Research, p. 1-27, 2018.
  39. Fang X., Gebraeel N., and Paynabar K., “Scalable Prognostic Models for Large Scale Condition Monitoring Applications”, IISE Transactions, vol. 49, no.7, p. 698-710, 2017.
    * Paper featured in the June 2017 issue of ISE Magazine.
  40. Fang X., Paynabar K., and Gebraeel N., “Multi-sensor Fusion Based Prognostics Model for Systems with Single Failure Modes”, Reliability Engineering and Systems Safety, vol. 159, p. 322-331, 2017.
  41. Hao L., Liu K., Gebraeel N., and Shi J., “Controlling the Residual Life Distribution of Parallel Multi-Component Systems through Workload Adjustment”, IEEE Transactions on Automation Science and Engineering, vol. 14, no. 2, p. 1042-1052, 2017.
  42. Yildirim M., Gebraeel N., and Xu A., “Integrated Predictive Analytics and Optimization for Opportunistic Maintenance and Operations in Wind Farms”,  IEEE Transactions on Power Systems, vol. 32, no. 6, p. 4319-4328, 2017.
  43. Xia T., Xi L., Pan, E, Fang X., and Gebraeel N., “Lease-oriented Opportunistic Maintenance for Multi-Unit Leased Systems Under Product-Service Paradigm”, ASME Transactions, Journal of Manufacturing Science and Engineering, vol. 139, no. 7, p. 071005, 2017.
  44. Hao L., Bian L., Gebraeel N., and Shi J., “Residual Life Prediction of Multistage Processes with Interaction between Tool Wear and Product Quality Degradation”, IEEE Transactions on Automation Science and Engineering, vol. 14, no. 2, p. 1211-1224, 2016
  45. Yildirim M., Xu A. and Gebraeel N., “Sensor Driven Condition-Based Generator Maintenance Scheduling Part 2: Algorithms and Validation “, IEEE Transactions on Power Systems, vol. 31, no. 6, p. 4263-4271, 2016.
  46. Yildirim M., Xu A. and Gebraeel N., “Sensor Driven Condition-Based Generator Maintenance Scheduling Part 1: Maintenance Framework and Formulation”, IEEE Transactions on Power Systems, vol. 31, no. 6, p. 4253-4262, 2016.
  47. Bian L., Gebraeel N., and Kharoufeh J., “Degradation Modeling for Real-Time Estimation of Residual Lifetimes in Dynamic Environments”, IIE Transactions, vol. 47, no. 5, 2015.
    *2016 Best Paper Award, IIE Transactions in Quality and Reliability Engineering.
  48. Fang X., Zhou R., and Gebraeel N., “An Adaptive Functional Regression-based Prognostic Model for Applications with Missing Data”, Reliability Engineering and Systems Safety, vol. 133, p. 266-274, 2015.
  49. Hao L., Gebraeel N., and Shi J., “Simultaneous Signal Separation and Prognostics of Multi-Component Systems: The case of Identical Components”, IIE Transactions, vol. 47, no. 5, p. 487-504, 2015.
  50. Bian L., and Gebraeel N., “Stochastic Modeling and Real-Time Prognostics for Multi-Component Systems with Degradation-Rate-Interactions”, IIE Transactions, vol. 46, no. 5, p. 470-482, 2014.
  51. Bian L., and Gebraeel N., “Stochastic Framework for Partially Degradation Systems with Continuous Component Degradation-Rate-Interactions” Naval Research Logistics, vol. 61, no. 4, p. 286-303, 2014.
  52. Zhou R., Serban N., Gebraeel N. and Muller H., “A Functional Time Warping Approach to Modeling and Monitoring Truncated Degradation Signals”, Technometrics, vol. 56, no. 1, p. 67-77, 2014.
  53. Zhou R., Serban N., and Gebraeel N., “Degradation-based Residual Life Prediction Under Different Environments”, Annals of Applied Statistics , vol. 8, no.3, p. 1671-1689, 2014.
  54. Flory, J.A., Kharoufeh, J.P. and Gebraeel N., “A switching diffusion model for lifetime estimation in randomly-varying environments”, IIE Transactions, vol. 46, no. 11, p. 1227-1241, 2014.
  55. Bian L. and Gebraeel N., “Stochastic Methodology for Prognostics Under Continuously Varying Environmental Profiles”, Statistical Analysis and Data Mining, vol. 6, no. 3, p. 260-270, 2013.
  56. Liu K., Gebraeel N., and Shi J., “Health Index Development Based on Sensory Data Fusion for Degradation Modeling and Prognostic Analysis”, IEEE Transactions on Automation Science and Engineering, vol. 10, no. 3, p. 652-664, July 2013.
    * IIE Quality Control and Reliability Best Student Paper Award.
  57. Bian L. and Gebraeel N., “Computing and Updating First-Passage Time Distributions for Randomly Evolving Degradation Signals”, IIE Transactions, vol. 44, no. 11, p. 974-987, 2012.
  58. Zhou R., Gebraeel N., and Serban N., “Modeling of Thresholded Degradation Signals using Functional Principle Component Analysis”, IIE Transactions, vol. 44, no. 9, p. 793-803, 2012.
    * Paper featured in the August 2012 issue of IE Magazine, and finalist in the Best QSR Student Paper Competition at INFORMS 2010.
  59. Elwany A., Gebraeel N., and Maillart L., “Structured Replacement Policies for Systems with Complex Degradation Processes and Dedicated Sensors”, Operations Research, vol. 59, no. 3, p. 684-695, 2011.
  60. Zhou R., Serban N., and Gebraeel N., “Degradation Modeling Applied to Residual Lifetime Prediction Using Functional Data Analysis”, Annals of Applied Statistics, vol. 5, no. 2B, p. 1586-1610, 2011.
  61. Gebraeel N., “Prognostics-Based Identification of Top-k Units in a Fleet”, IEEE Transactions on Automation Science and Engineering, vol. 7, no. 1, p. 37-48, Jan. 2010.
  62. Chakraborty S., Gebraeel N., Lawley M., and Wan H., “Residual Life Estimation for Components with Non-symmetric Priors”, IIE Transactions, vol. 41, no. 4, p. 372-387, 2009.
  63. Gebraeel N. and Hernandez, L., “Advanced prognostics for aircraft electrical power systems”, SAE International Journal of Aerospace, vol. 1, no. 1, p. 1059-1063, 2009.
  64. Gebraeel N., Elwany A. H., and Pan J., “Residual Life Predictions in the Absence of Prior Degradation Knowledge: Prognostic Models with Fixed Intercepts”, IEEE Transactions on Reliability, vol. 8, no. 1, p. 106-117, March 2009.
  65. Kaiser K. and Gebraeel N., “Predictive Maintenance Management Using Sensor-Based Degradation Models”, IEEE Transactions on Systems, Man, and Cybernetics, Part A, vol. 8, no. 1, p. 106-117, March 2009.
  66. Elwany A. and Gebraeel N., “Sensor-Based Degradation Models for Computing Residual Life Distributions: A First Passage Time Approximation”, ASME Transactions on Manufacturing Science and Engineering, vol. 131, no. 5, Oct. 2009.
  67. Gebraeel N. and Pan J., “Prognostic Degradation Models for Computing and Updating Residual Life Distributions in a Time-Varying Environment”, IEEE Transactions on Reliability, vol. 57, no. 4, p. 539-550, December 2008.
  68. Elwany A. H. and Gebraeel N., “Sensory-Driven Prognostic Models for Spare Parts Logistics”, IIE Transactions Quality and Reliability Engineering, vol. 40, no. 7, p. 629-639, July 2008.
    * Paper featured in the July 2008 issue of IE Magazine, and was a finalist in the Best QSR Student Paper Competition at INFORMS 2007.
  69. Gebraeel N. and Lawley M., “A Neural Network Degradation Model for Computing and Updating Residual Life Distributions “, IEEE Transactions on Automation Science and Engineering, vol.5, no.1, p. 154-163, January 2008.
  70. Wu S., Gebraeel N., Lawley M., and Yih Y., “A Neural Network Integrated Decision Support System for Condition-Based Optimal Predictive Maintenance Policy”, IEEE Transactions on Systems, Man and Cybernetics Part A-Systems and Humans, vol. 37, no. 2, pp 226-236, March 2007.
  71. Gebraeel N., “Sensor-based degradation models for components with exponential degradation patterns”, IEEE Transactions on Automation Science and Engineering, vol. 3, no. 4, p. 382 393, October 2006.
  72. Gebraeel N., Lawley M., Li R., and Ryan J. K., “Life Distributions from Component Degradation Signals: A Bayesian Approach”, IIE Transactions on Quality and Reliability , vol.37, no. 6, p 543-557, June 2005.
  73. Gebraeel N., Lawley M., Liu R., and Parmeshwaran V., “Life Distributions from Component Degradation Signals: A Neural Net Approach”, IEEE Transactions on Industrial Electronics, vol. 51, no. 3, p. 694-700, June 2004.
  74. Gebraeel N. and Lawley M. “Deadlock Detection, Prevention, and Avoidance for Automated Tool Sharing Systems in Flexible Manufacturing”, IEEE Transactions on Robotics and Automation, vol. 17, no. 3, pp 342-356, 2001.

 Publications Submitted and Under Review:

  1. Fang X., Gebraeel N. and Paynabar K., “A Supervised Dimension Reduction-Based Prognostics Model for Applications with Incomplete Signals and Censored Failure Times”.
  2. Mohanty A., Dekarske J., Joshi, S., and Gebraeel N., “Operational Self Awareness of Robotic Manipulators Performing Tasks with Dynamic Severity Levels”.
  3. Peters B., Mohanty A., Fang X., and Gebraeel N., “Sensor-fusion based Prognostics Framework for Complex Engineering Systems Exhibiting Multiple Failure Modes”.
  4. Rozas H., Xie W., and Gebraeel N., “Data-driven Joint Optimization of Maintenance and Spare Parts Provisioning: A Distributionally Robust  Approach”.
  5. Ibrahim M., Rozas H., Gebraeel N., and Xie W., “A Federated Distributionally Robust Support Vector Machine with Mixture of Wasserstein Balls Ambiguity Set for Distributed Fault Diagnosis”.
  6. Rozas, H., Gebraeel N., and Xie W., “On the Computation of Contextual Distributionally Robust Preventive Maintenance Intervals”.

Conference Publications:

  1. Wang, S., Song, M., Fei, Y., Zhang, D., Zhou, F., Gebraeel, N. and Jiao, J., “Prospect-theoretic Modeling of Team Cognition for Task Allocation Towards Human-automation Symbiosis”, 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1158-1162).
  2. Wang, S., Song, M., Fei, Y.C., Zhang, D., Gebraeel, N.Z., and Jiao, R.J., “System Analysis and Design of Task Allocation for Human-Automation Symbiosis in Smart Manufacturing”, Proceedings of the 6th European Conference on Industrial Engineering and Operations Management, Lisbon, Portugal, July 18-20, 2023.
  3. Eshima, S., Nabity, J., Mohany, A., Rozas, H., & Gebraeel, N. (2022, July). “A Diagnostics Model for Detecting Leak Severity in a Regenerable CO2 Removal System”. 51st International Conference on Environmental Systems.
  4. D. Li, P. Ramanan, N. Gebraeel and K. Paynabar, “Deep Learning Based Covert Attack Identification for Industrial Control Systems,” 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020, p. 438-445, doi: 10.1109/ICMLA51294.2020.00075.
  5. Ashok K., Li D., Divan D., and Gebraeel N., “Distribution Transformer Health Monitoring using Smart Meter Data”, 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2020, p. 1-5, doi: 10.1109/ISGT45199.2020.9087641.
  6. DeShong E., Peters B., Berdanier R. A., Thole K. A., Paynabar K., and Gebraeel N.,”Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring” In Turbo Expo: Power for Land, Sea, and Air, vol. 84980, p. V05BT14A012. American Society of Mechanical Engineers, 2021.
  7. Kumar, R. M., Peters, B., Emerson, B., Paynabar, K., Gebraeel, N., Lieuwen, T., “Data driven fault detection of premixer centerbody degradation in a swirl combustor”, Turbomachinery Technical Conference and Exposition GT 2020, Proceedings of ASME Turbo Expo 2020
  8. Ramanan P., Yildirim M., Chow E., and Gebraeel N. “An Asynchronous, Decentralized Solution Framework for the Large Scale Unit Commitment Problem”,  International Conference on Computational Science, ICCS 2017, Procedia Computer Science, Vol 108, pages 665-674.
  9. Fang X., Paynabar K., and Gebraeel N.,  “Real-Time Predictive Analytics Using Degradation Image Data”, 2018 Annual Reliability and Maintainability Symposium (RAMS), 1-6, 2018.
  10. Jain, Paras, Chirag Tailor, Sam Ford, Liexiao Ding, Michael Phillips, Fang Liu, Nagi Gebraeel, and Duen Horng Chau. “Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets.” In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), p. 1078-1082. IEEE, 2017.
  11. Gebraeel, Nagi Z. “Degradation Models for Computing and Updating Residual Life Distributions in a Time-Varying Environment.” In IIE Annual Conference. Proceedings, p. 128. Institute of Industrial and Systems Engineers (IISE), 2008.
  12. Gebraeel, Nagi, and Luis Hernandez. “Advanced prognostics for aircraft electrical power systems.” SAE International Journal of Aerospace 1, no. 2008-01-2922 (2008): 1059-1063.
  13. Elwany A. and Gebraeel N., “Sensor-Driven Decision Models for Equipment Replacement and Spare Parts Logistics.” In IIE Annual Conference. Proceedings, p. 1488. Institute of Industrial and Systems Engineers (IISE), 2007.
  14. Gebraeel, N., M. Lawley, and R. Liu. “Vibration-based condition monitoring of thrust bearings for maintenance management.” Proc. ANNIE 2002 Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Artificial Life and Data Mining (2002): 543-551.