Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system K Sabahi, M Teshnehlab Energy Conversion and Management 50 (4), 938-946, 2009 | 85 | 2009 |
Load frequency control in interconnected power system using modified dynamic neural networks K Sabahi, MA Nekoui, M Teshnehlab, M Aliyari, M Mansouri 2007 Mediterranean conference on control & automation, 1-5, 2007 | 76 | 2007 |
Application of type-2 fuzzy logic system for load frequency control using feedback error learning approaches K Sabahi, S Ghaemi, S Pezeshki Applied Soft Computing 21, 1-11, 2014 | 70 | 2014 |
Load Frequency Control in Interconnected Power System Using Multi-Objective PID Controller MTMA K. Sabahi, A. Sharifi, M. Aliyari Sh. Journal of Applied Sciences 8 (20), 3676-3682, 2008 | 51 | 2008 |
Load frequency control in interconnected power system using multi-objective PID controller A Sharifi, K Sabahi, MA Shoorehdeli, MA Nekoui, M Teshnehlab Soft Computing in Industrial Applications, 2008. SMCia'08. IEEE Conference …, 2008 | 47 | 2008 |
Designing an adaptive type-2 fuzzy logic system load frequency control for a nonlinear time-delay power system K Sabahi, S Ghaemi, M Badamchizadeh Applied Soft Computing 43, 97-106, 2016 | 44 | 2016 |
Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input-delay systems K Sabahi, S Ghaemi, J Liu, MA Badamchizadeh ISA transactions 71, 185-195, 2017 | 20 | 2017 |
Recurrent fuzzy neural network for DC-motor control A Faramarzi, K Sabahi 2011 Fifth International Conference on Genetic and Evolutionary Computing, 93-96, 2011 | 19 | 2011 |
Adaptive robust control of autonomous underwater vehicle S Pezeshki, AR Ghiasi, MA Badamchizadeh, K Sabahi Journal of Control, Automation and Electrical Systems 27, 250-262, 2016 | 17 | 2016 |
Adaptive type-2 fuzzy PID controller for LFC in AC microgrid K Sabahi, M Tavan, A Hajizadeh Soft Computing 25, 7423-7434, 2021 | 16 | 2021 |
Gain Scheduling Technique using MIMO Type-2 Fuzzy Logic System for LFC in Restructure Power System K Sabahi, S Ghaemi, S Pezeshki International Journal of Fuzzy Systems, 1-15, 2016 | 16 | 2016 |
Recognition COVID-19 cases using deep type-2 fuzzy neural networks based on chest X-ray image K Sabahi, S Sheykhivand, Z Mousavi, M Rajabioun Computational Intelligence in Electrical Engineering 14 (1), 75-92, 2023 | 15 | 2023 |
Overcoming the detectability obstacle in adaptive output feedback control of DC–DC boost converter with unknown load M Tavan, K Sabahi, A Hajizadeh, MN Soltani, K Jessen IEEE Transactions on Control Systems Technology 29 (6), 2678-2686, 2020 | 14 | 2020 |
Feedback error learning-based type-2 fuzzy neural network predictive controller for a class of nonlinear input delay systems K Sabahi, S Ghaemi, MA Badamchizadeh Transactions of the Institute of Measurement and Control 41 (13), 3651-3665, 2019 | 14 | 2019 |
Self-tuning fuzzy PID controller for load frequency control in AC micro-grid with considering of input delay روح الله شاهدی, کامل صباحی, مهدی توان, امین حاجی زاده روشهای هوشمند در صنعت برق 9 (35), 19-26, 2018 | 14* | 2018 |
Lyapunov–Krasovskii stable T2FNN controller for a class of nonlinear time-delay systems S Ghaemi, K Sabahi, MA Badamchizadeh Soft Computing 23 (4), 1407-1419, 2019 | 13 | 2019 |
A modified DNA-computing algorithm to solve TSP K Mehdizadeh, MA Nekoui, K Sabahi, A Akbarimajd 2006 IEEE International Conference on Mechatronics, 65-68, 2006 | 11 | 2006 |
Adaptive fuzzy gain scheduling PID controller for frequency regulation in modern power system P Razmi, T Rahimi, K Sabahi, M Gheisarnejad, MH Khooban IET Renewable Power Generation, 2022 | 8 | 2022 |
Adaptive type-2 fuzzy PID LFC for an interconnected power system considering input time-delay K Sabahi, A Hajizadeh, M Tavan, A Feliachi International Journal of Fuzzy Systems 23 (4), 1042-1054, 2021 | 8 | 2021 |
Dynamic neural network for AGC in restructure power system K Sabahi, E Narimani, A Faramarzi 2010 IEEE International Conference on Power and Energy, 594-599, 2010 | 7 | 2010 |