| Minimum complexity echo state network A Rodan, P Tino IEEE transactions on neural networks 22 (1), 131-144, 2010 | 771 | 2010 |
| Learning in the model space for cognitive fault diagnosis H Chen, P Tino, A Rodan, X Yao IEEE Transactions on Neural Networks and Learning Systems, 1-1, 2013 | 172* | 2013 |
| Simple Deterministically Constructed Cycle Reservoirs with Regular Jumps A Rodan, P Tiňo Neural Computation, MIT Press , 2012, 2012 | 142 | 2012 |
| An efficient hybrid filter and evolutionary wrapper approach for sentiment analysis of various topics on Twitter MA Hassonah, R Al-Sayyed, A Rodan, AZ Ala’M, I Aljarah, H Faris Knowledge-Based Systems 192, 105353, 2020 | 103 | 2020 |
| A Support Vector Machine Approach for Churn Prediction in Telecom Industry A Rodan, H Faris, J Alsakran, O Al-Kadi INFORMATION 17 (8), 3961-3970, 2014 | 51 | 2014 |
| Artificial Neural Networks for Surface Ozone Prediction: Models and Analysis. H Faris, M Alkasassbeh, A Rodan Polish Journal of Environmental Studies 23 (2), 2014 | 39 | 2014 |
| Bidirectional Reservoir Networks Trained using SVM+ Privileged Information for Manufacturing Process Modeling A Rodan, A Sheta, H Faris Soft Computing, 2016 | 38 | 2016 |
| Optimizing Feedforward Neural Networks Using Biogeography Based Optimization for E-Mail Spam Identification A Rodan, H Faris, J Alqatawna Int. J. Communications, Network and System Sciences 9, 19-28, 2016 | 35 | 2016 |
| Negative Correlation Learning for Customer Churn Prediction: A Comparison Study A Rodan, A Fayyoumi, H Faris, J Alsakran, O Al-Kadi The Scientific World Journal 2014 (Article ID 473283), 1-7, 2014 | 35 | 2014 |
| Churn prediction: A comparative study using knn and decision trees MA Hassonah, A Rodan, AK Al-Tamimi, J Alsakran 2019 Sixth HCT Information Technology Trends (ITT), 182-186, 2019 | 32 | 2019 |
| Short term memory in input-driven linear dynamical systems P Tiňo, A Rodan Neurocomputing 112, 58-63, 2013 | 31 | 2013 |
| Simple deterministically constructed recurrent neural networks A Rodan, P Tiňo Intelligent Data Engineering and Automated Learning–IDEAL 2010: 11th …, 2010 | 30 | 2010 |
| Cycle reservoir with regular jumps for forecasting ozone concentrations: Two real cases from the east of Croatia: CRJ for forecasting ozone concentrations A Sheta, H Faris, A Rodan, E Kovač-Andrić, AM Al-Zoubi Air Quality, Atmosphere & Health 11, 559-569, 2018 | 27 | 2018 |
| Echo state network with SVM-readout for customer churn prediction A Rodan, H Faris 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing …, 2015 | 24 | 2015 |
| Online news popularity prediction F Namous, A Rodan, Y Javed 2018 Fifth HCT Information Technology Trends (ITT), 180-184, 2018 | 22 | 2018 |
| Polar particle swarm algorithm for solving cloud data migration optimization problem RM Al-Sayyed, HN Fakhouri, A Rodan, C Pattinson Modern Applied Science 11 (8), 98, 2017 | 19 | 2017 |
| A Survey of Concepts Location Enhancement for Program Comprehension and Maintenance N Alhindawi, J Alsakran, A Rodan, H Faris Journal of Software Engineering and Applications 7 (5), 413-421, 2014 | 16 | 2014 |
| Pattern Recognition of Thermal Images for Monitoring of Breathing Function F Al-Obaisi, J Alqatawna, H Faris, A Rodan, O AlKadi International Journal of Control and Automation 8 (6), 381-392, 2015 | 13 | 2015 |
| Security approach for in-vehicle networking using blockchain technology M Salem, M Mohammed, A Rodan Advances in Internet, Data and Web Technologies: The 7th International …, 2019 | 12 | 2019 |
| Credit Risk Evaluation Using Cycle Reservoir Neural Networks with Support Vector Machines Readout A Rodan, H Faris Lecture Notes on Computer Science lNCS/LNAI, 595-604, 2016 | 12 | 2016 |
Hossam FarisProfessor, The University of Jordanبريد إلكتروني تم التحقق منه على ju.edu.jo
