| DBSCAN: Past, present and future K Khan, SU Rehman, K Aziz, S Fong, S Sarasvady The fifth international conference on the applications of digital …, 2014 | 377 | 2014 |
| An Application of Oversampling, Undersampling, Bagging and Boosting in Handling Imbalanced Datasets. BW Yap, K Abd Rani, HA Abd Rahman, S Fong, Z Khairudin, NN Abdullah DaEng, 13-22, 2013 | 306 | 2013 |
| Accelerated particle swarm optimization and support vector machine for business optimization and applications XS Yang, S Deb, S Fong Networked Digital Technologies: Third International Conference, NDT 2011 …, 2011 | 286 | 2011 |
| Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges S Huang, J Yang, S Fong, Q Zhao Cancer letters 471, 61-71, 2020 | 259 | 2020 |
| Developing residential wireless sensor networks for ECG healthcare monitoring N Dey, AS Ashour, F Shi, SJ Fong, RS Sherratt IEEE Transactions on Consumer Electronics 63 (4), 442-449, 2017 | 248 | 2017 |
| Wolf search algorithm with ephemeral memory R Tang, S Fong, XS Yang, S Deb Seventh international conference on digital information management (ICDIM …, 2012 | 248 | 2012 |
| Accelerated PSO swarm search feature selection for data stream mining big data S Fong, R Wong, AV Vasilakos IEEE transactions on services computing 9 (1), 33-45, 2015 | 243 | 2015 |
| Finding an accurate early forecasting model from small dataset: A case of 2019-ncov novel coronavirus outbreak SJ Fong, G Li, N Dey, RG Crespo, E Herrera-Viedma arXiv preprint arXiv:2003.10776, 2020 | 225 | 2020 |
| A survey of data mining and deep learning in bioinformatics K Lan, D Wang, S Fong, L Liu, KKL Wong, N Dey Journal of medical systems 42, 1-20, 2018 | 216 | 2018 |
| Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction SJ Fong, G Li, N Dey, RG Crespo, E Herrera-Viedma Applied soft computing 93, 106282, 2020 | 187 | 2020 |
| Optimization for allocating BEV recharging stations in urban areas by using hierarchical clustering A Ip, S Fong, E Liu 2010 6th International conference on advanced information management and …, 2010 | 183 | 2010 |
| Medical cyber-physical systems: A survey N Dey, AS Ashour, F Shi, SJ Fong, JMRS Tavares Journal of medical systems 42, 1-13, 2018 | 175 | 2018 |
| AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest P Bhadra, J Yan, J Li, S Fong, SWI Siu Scientific reports 8 (1), 1-10, 2018 | 154 | 2018 |
| Epileptic seizures prediction using machine learning methods SM Usman, M Usman, S Fong Computational and mathematical methods in medicine 2017, 2017 | 150 | 2017 |
| A novel hybrid self-adaptive bat algorithm I Fister, S Fong, J Brest The Scientific World Journal 2014, 2014 | 135 | 2014 |
| Metaheuristic algorithms: optimal balance of intensification and diversification XS Yang, S Deb, S Fong Applied Mathematics & Information Sciences 8 (3), 977, 2014 | 131 | 2014 |
| Integrating nature-inspired optimization algorithms to K-means clustering R Tang, S Fong, XS Yang, S Deb Seventh International Conference on Digital Information Management (ICDIM …, 2012 | 123 | 2012 |
| Feature Selection Methods: Case of Filter and Wrapper Approaches for Maximising Classification Accuracy. YB Wah, N Ibrahim, HA Hamid, S Abdul-Rahman, S Fong Pertanika Journal of Science & Technology 26 (1), 2018 | 114 | 2018 |
| Social group optimization–assisted Kapur’s entropy and morphological segmentation for automated detection of COVID-19 infection from computed tomography images N Dey, V Rajinikanth, SJ Fong, MS Kaiser, M Mahmud Cognitive Computation 12, 1011-1023, 2020 | 98 | 2020 |
| Elephant search algorithm for optimization problems S Deb, S Fong, Z Tian 2015 tenth international conference on digital information management (ICDIM …, 2015 | 89 | 2015 |
Xin-She Yang (DPhil)Computational intelligence, swarm intelligence, optimization, metaheuristics, nature-inspiredVerified email at mdx.ac.uk
