| MATLAB supplement to fuzzy and neural approaches in engineering JW Hines, LH Tsoukalas, RE Uhrig John Wiley & Sons, Inc., 1997 | 435 | 1997 |
| Multilayer data-driven cyber-attack detection system for industrial control systems based on network, system, and process data F Zhang, HADE Kodituwakku, JW Hines, J Coble IEEE Transactions on Industrial Informatics 15 (7), 4362-4369, 2019 | 317 | 2019 |
| Anomaly-based intrusion detection for SCADA systems D Yang, A Usynin, JW Hines 5th intl. topical meeting on nuclear plant instrumentation, control and …, 2006 | 250 | 2006 |
| Identifying optimal prognostic parameters from data: a genetic algorithms approach J Coble, JW Hines Annual Conference of the PHM Society 1 (1), 2009 | 161 | 2009 |
| Use of autoassociative neural networks for signal validation JW Hines, RE Uhrig, DJ Wrest Journal of Intelligent and Robotic Systems 21, 143-154, 1998 | 147 | 1998 |
| Technical review of on-line monitoring techniques for performance assessment JW Hines, R Seibert, SA Arndt Volume 1, 20555-0001, 2006 | 146 | 2006 |
| A review of prognostics and health management applications in nuclear power plants J Coble, P Ramuhalli, L Bond, J Hines, B Ipadhyaya | 121 | 2015 |
| A hybrid fault diagnosis methodology with support vector machine and improved particle swarm optimization for nuclear power plants H Wang, M Peng, JW Hines, G Zheng, Y Liu, BR Upadhyaya ISA transactions 95, 358-371, 2019 | 115 | 2019 |
| Prognostic algorithm categorization with PHM challenge application JB Coble, JW Hines 2008 International Conference on Prognostics and Health Management, 1-11, 2008 | 103 | 2008 |
| Applying the general path model to estimation of remaining useful life J Coble, JW Hines International Journal of Prognostics and Health Management Volume 2 (color), 71, 2011 | 102 | 2011 |
| Optimization of fuzzy evapotranspiration model through neural training with input–output examples LO Odhiambo, RE Yoder, DC Yoder, JW Hines Transactions of the ASAE 44 (6), 1625, 2001 | 102 | 2001 |
| Prognostics and health management in nuclear power plants: a review of technologies and applications JB Coble, P Ramuhalli, LJ Bond, W Hines, B Upadhyaya Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 2012 | 81 | 2012 |
| Development and application of fault detectability performance metrics for instrument calibration verification and anomaly detection JW Hines, DR Garvey Journal of Pattern Recognition Research 1 (1), 2-15, 2006 | 80 | 2006 |
| Robust distance measures for on-line monitoring JW Hines US Patent 8,311,774, 2012 | 77 | 2012 |
| Signal validation using an adaptive neural fuzzy inference system JW Hines, DJ Wrest, RE Uhrig Nuclear technology 119 (2), 181-193, 1997 | 77 | 1997 |
| Current computational trends in equipment prognostics J Wesley Hines, A Usynin International Journal of Computational Intelligence Systems 1 (1), 94-102, 2008 | 73 | 2008 |
| Validation of on-line monitoring techniques to nuclear plant data J Garvey, D Garvey, R Seibert, JW Hines Nuclear Engineering and Technology 39 (2), 133, 2007 | 72 | 2007 |
| Lessons learned from the US nuclear power plant on-line monitoring programs JW Hines, E Davis Progress in Nuclear Energy 46 (3-4), 176-189, 2005 | 63 | 2005 |
| A model for predicting lung cancer response to therapy RM Seibert, CR Ramsey, JW Hines, PA Kupelian, KM Langen, SL Meeks, ... International Journal of Radiation Oncology* Biology* Physics 67 (2), 601-609, 2007 | 61 | 2007 |
| Method and system for automatically transitioning files among computer systems R Bowler, J Hines, K Mackin US Patent App. 09/793,334, 2002 | 61 | 2002 |
Jamie CobleUniversity of TennesseeDirección de correo verificada de utk.edu
