| Deep learning-based networks for automated recognition and classification of awkward working postures in construction using wearable insole sensor data MF Antwi-Afari, Y Qarout, R Herzallah, S Anwer, W Umer, Y Zhang, ... Automation in construction 136, 104181, 2022 | 42 | 2022 |
| Probabilistic multiple model neural network based leak detection system: Experimental study MB Abdulla, R Herzallah Journal of Loss Prevention in the Process Industries 36, 30-38, 2015 | 38 | 2015 |
| Fully probabilistic control design in an adaptive critic framework R Herzallah, M Kárný Neural networks 24 (10), 1128-1135, 2011 | 34 | 2011 |
| A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems R Herzallah, D Lowe Engineering Applications of Artificial Intelligence 17 (2), 145-158, 2004 | 32 | 2004 |
| Pipeline leak detection using artificial neural network: Experimental study MB Abdulla, RO Herzallah, MA Hammad 2013 5th International Conference on Modelling, Identification and Control …, 2013 | 29 | 2013 |
| Probabilistic DHP adaptive critic for nonlinear stochastic control systems R Herzallah Neural Networks 42, 74-82, 2013 | 20 | 2013 |
| Adaptive critic methods for stochastic systems with input-dependent noise R Herzallah Automatica 43 (8), 1355-1362, 2007 | 20 | 2007 |
| Fully Probabilistic Control for Stochastic Nonlinear Control Systems with Input Dependent Noise. R Herzallah Neural Networks, 199-207, 2015 | 18 | 2015 |
| Generalised probabilistic control design for uncertain stochastic control systems R Herzallah Asian Journal of Control 20 (6), 2065-2074, 2018 | 17 | 2018 |
| Scalable harmonization of complex networks with local adaptive controllers M Kárný, R Herzallah IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (3), 394-404, 2015 | 17 | 2015 |
| A Bayesian perspective on stochastic neurocontrol R Herzallah, D Lowe IEEE Transactions on Neural Networks 19 (5), 914-924, 2008 | 16 | 2008 |
| Distribution modeling of nonlinear inverse controllers under a Bayesian framework R Herzallah, D Lowe IEEE transactions on neural networks 18 (1), 107-114, 2007 | 16 | 2007 |
| Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals R Herzallah, D Lowe Neural Computing & Applications 12, 98-108, 2003 | 16 | 2003 |
| Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty R Herzallah International Journal of Modelling, Identification and Control 12 (4), 311-327, 2011 | 15 | 2011 |
| Multi-valued control problems and mixture density network R Herzallah, D Lowe Australian Academic Press 2, 387-392, 2003 | 15 | 2003 |
| A novel approach to modelling and exploiting uncertainty in stochastic control systems R Herzallah, D Lowe International Conference on Artificial Neural Networks, 801-806, 2002 | 15 | 2002 |
| A novel approach to modeling and exploiting uncertainty in stochastic control systems RHD Lowe International Conference on Artificial Neural Networks, ICANN, 801–806, 2002 | 15* | 2002 |
| Bayesian adaptive control of nonlinear systems with functional uncertainty RHD Lowe Controlo, 2006, 2006 | 13* | 2006 |
| Optimal electricity trading strategy for a household microgrid Z Qin, H Hua, H Liang, R Herzallah, Y Zhou, J Cao 2020 IEEE 16th International Conference on Control & Automation (ICCA), 1308 …, 2020 | 12 | 2020 |
| ECG-derived respiration using a real-time QRS detector based on empirical mode decomposition C Kozia, R Herzallah, D Lowe 2018 12th International Conference on Signal Processing and Communication …, 2018 | 11 | 2018 |
Yuyang ZhouEdinburgh Napier UniversityDirección de correo verificada de napier.ac.uk
