| A hybrid model of self-organizing maps (SOM) and least square support vector machine (LSSVM) for time-series forecasting S Ismail, A Shabri, R Samsudin Expert Systems with Applications 38 (8), 10574-10578, 2011 | 167 | 2011 |
| River flow time series using least squares support vector machines R Samsudin, P Saad, A Shabri Hydrology and Earth System Sciences 15 (6), 1835-1852, 2011 | 116 | 2011 |
| A comparison of time series forecasting using support vector machine and artificial neural network model R Samsudin, A Shabri, P Saad Journal of applied sciences 10 (11), 950-958, 2010 | 116 | 2010 |
| Daily crude oil price forecasting using hybridizing wavelet and artificial neural network model A Shabri, R Samsudin Mathematical Problems in Engineering 2014 (1), 201402, 2014 | 67 | 2014 |
| A hybrid model of self organizing maps and least square support vector machine for river flow forecasting S Ismail, A Shabri, R Samsudin Hydrology and Earth system sciences 16 (11), 4417-4433, 2012 | 43 | 2012 |
| Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis A Shabri, R Samsudin The Scientific World Journal 2014 (1), 854520, 2014 | 30 | 2014 |
| A hybrid least squares support vector machines and GMDH approach for river flow forecasting R Samsudin, P Saad, A Shabri Hydrology and Earth System Sciences Discussions 7 (3), 3691-3731, 2010 | 24 | 2010 |
| A hybrid GMDH and least squares support vector machines in time series forecasting R Samsudin, P Saad, A Shabri Neural Network World 21 (3), 251, 2011 | 21 | 2011 |
| Tourism forecasting using hybrid modified empirical mode decomposition and neural network NA Yahya, R Samsudin, A Shabri Int. J. Advance Soft Compu. Appl 9 (1), 14-31, 2017 | 20 | 2017 |
| A hybrid GMDH and box-jenkins models in time series forecasting A Shabri, R Samsudin Applied mathematical sciences 8 (62), 3051-3062, 2014 | 20 | 2014 |
| Forecasting of the rice yields time series forecasting using artificial neural network and statistical model. A Shabri, R Samsudin, Z Ismail | 20 | 2009 |
| Hybridizing GMDH and least squares SVM support vector machine for forecasting tourism demand. S Ruhaidah, S Puteh, S Ani International Journal of Research and Reviews in Applied Sciences 3 (3), 274-279, 2010 | 19 | 2010 |
| Intelligent learning model based on significant weight of domain knowledge concept for adaptive e-learning N Idris, SZM Hashim, R Samsudin, NBH Ahmad Int. J. Adv. Sci. Eng. Inf. Technol 7 (4-2), 1486, 2017 | 17 | 2017 |
| River flow forecasting: a hybrid model of self organizing maps and least square support vector machine S Ismail, R Samsudin, A Shabri Hydrol Earth Syst Sci Discuss 7 (5), 8179-8212, 2010 | 15 | 2010 |
| Fishery Landing Forecasting Using Wavelet‐Based Autoregressive Integrated Moving Average Models A Shabri, R Samsudin Mathematical Problems in Engineering 2015 (1), 969450, 2015 | 14 | 2015 |
| Empirical mode decomposition–least squares support vector machine based for water demand forecasting A Shabri, R Samsudin, U Teknologi Int. J. Adv. Soft Comput. Its Appl 7 (2), 2015 | 13 | 2015 |
| Combining deep neural network and fourier series for tourist arrivals forecasting A Shabri, R Samsudin, Y Yusoff IOP Conference Series: Materials Science and Engineering 864 (1), 012094, 2020 | 11 | 2020 |
| Combined group method of data handling models using artificial bee colony algorithm in time series forecasting NA Yahya, R Samsudin, A Shabri, F Saeed Procedia computer science 163, 319-329, 2019 | 11 | 2019 |
| The Effect of Kernel Functions on Cryptocurrency Prediction Using Support Vector Machines NA Hitam, AR Ismail, R Samsudin, EH Alkhammash International Conference of Reliable Information and Communication …, 2021 | 9 | 2021 |
| New hybridization of empirical mode decomposition and least squares support vector machine model in forecasting Malaysia exchange rates NIA Rashid, A Shabri, R Samsudin 2017 International Conference on Robotics, Automation and Sciences (ICORAS), 1-5, 2017 | 9 | 2017 |
