| Application of two non-linear prediction tools to the estimation of tunnel boring machine performance S Yagiz, C Gokceoglu, E Sezer, S Iplikci Engineering Applications of Artificial Intelligence 22 (4-5), 808-814, 2009 | 311 | 2009 |
| An algorithm for fast convergence in training neural networks BM Wilamowski, S Iplikci, O Kaynak, MO Efe IJCNN'01. International Joint Conference on Neural Networks. Proceedings …, 2001 | 277 | 2001 |
| Parkinson’s Disease tremor classification–A comparison between Support Vector Machines and neural networks S Pan, S Iplikci, K Warwick, TZ Aziz Expert Systems with Applications 39 (12), 10764-10771, 2012 | 118 | 2012 |
| A micro-DC power distribution system for a residential application energized by photovoltaic–wind/fuel cell hybrid energy systems E Cetin, A Yilanci, HK Ozturk, M Colak, I Kasikci, S Iplikci Energy and Buildings 42 (8), 1344-1352, 2010 | 109 | 2010 |
| Support vector machines‐based generalized predictive control S Iplikci International Journal of Robust and Nonlinear Control: IFAC‐Affiliated …, 2006 | 90 | 2006 |
| A novel auto-tuning PID control mechanism for nonlinear systems M Cetin, S Iplikci ISA transactions 58, 292-308, 2015 | 85 | 2015 |
| A comparative study on a novel model‐based PID tuning and control mechanism for nonlinear systems S Iplikci International Journal of Robust and Nonlinear Control 20 (13), 1483-1501, 2010 | 59 | 2010 |
| A support vector machine based control application to the experimental three-tank system S Iplikci ISA transactions 49 (3), 376-386, 2010 | 58 | 2010 |
| Runge–Kutta model-based adaptive predictive control mechanism for non-linear processes S Iplikci Transactions of the Institute of Measurement and Control 35 (2), 166-180, 2013 | 43 | 2013 |
| Online trained support vector machines‐based generalized predictive control of non‐linear systems S Iplikci International Journal of Adaptive Control and Signal Processing 20 (10), 599-621, 2006 | 42 | 2006 |
| Dynamic reconstruction of chaotic systems from inter-spike intervals using least squares support vector machines S Iplikci Physica D: Nonlinear Phenomena 216 (2), 282-293, 2006 | 27 | 2006 |
| Support vector machines based neuro-fuzzy control of nonlinear systems S Iplikci Neurocomputing 73 (10-12), 2097-2107, 2010 | 26 | 2010 |
| A model‐based PID controller for Hammerstein systems using B‐spline neural networks X Hong, S Iplikci, S Chen, K Warwick International Journal of Adaptive Control and Signal Processing 28 (3-5 …, 2014 | 21 | 2014 |
| Control of chaotic systems using targeting by extended control regions method S Iplikci, Y Denizhan Physica D: Nonlinear Phenomena 150 (3-4), 163-176, 2001 | 19 | 2001 |
| Runge-Kutta model predictive speed control for permanent magnet synchronous motors A Akpunar, S Iplikci Energies 13 (5), 1216, 2020 | 16 | 2020 |
| An application of speech recognition with support vector machines O Eray, S Tokat, S Iplikci 2018 6th International Symposium on Digital Forensic and Security (ISDFS), 1-6, 2018 | 16 | 2018 |
| Veri kümeleme algoritmalarının performansları üzerine karşılaştırmalı bir çalışma MS Durmuş Pamukkale Üniversitesi Fen Bilimleri Enstitüsü, 2005 | 14 | 2005 |
| Predicting academically at-risk engineering students: A soft computing application N Güner, A Yaldır, G Gündüz, E Çomak, S Tokat, S İplikçi Acta Polytechnica Hungarica 11 (5), 199-216, 2014 | 13 | 2014 |
| River flow estimation from upstream flow records using support vector machines H Karahan, S Iplikci, M Yasar, G Gurarslan Journal of Applied Mathematics 2014 (1), 714213, 2014 | 13 | 2014 |
| Controlling the experimental three-tank system via support vector machines S Iplikci International Conference on Adaptive and Natural Computing Algorithms, 391-400, 2009 | 13 | 2009 |
