| Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange MS Ismail, MSM Noorani, M Ismail, FA Razak, MA Alias Applied Soft Computing 93, 106422, 2020 | 47 | 2020 |
| Early warning signals of financial crises using persistent homology MS Ismail, MSM Noorani, M Ismail, FA Razak, MA Alias Physica A: Statistical Mechanics and Its Applications 586, 126459, 2022 | 22 | 2022 |
| Detecting early warning signals of major financial crashes in bitcoin using persistent homology MS Ismail, SI Hussain, MSM Noorani IEEE Access 8, 202042-202057, 2020 | 16 | 2020 |
| MS; Ismail, M.; Abdul Razak, F.; Alias, MA Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala … MS Ismail, M Noorani Appl. Soft Comput. J 93, 106422, 2020 | 8 | 2020 |
| Early warning signals of financial crises using persistent homology and critical slowing down: evidence from different correlation tests MS Ismail, MS Md Noorani, M Ismail, F Abdul Razak Frontiers in Applied Mathematics and Statistics 8, 940133, 2022 | 7 | 2022 |
| Modeling the Characteristics of Unhealthy Air Pollution Events Using Bivariate Copulas MS Ismail, N Masseran Symmetry 15 (4), 907, 2023 | 3 | 2023 |
| The dynamical properties of even shift space MS Ismail, SC Dzul-Kifli AIP Conference Proceedings 1870 (1), 2017 | 2 | 2017 |
| Risk assessment for extreme air pollution events using vine copula MS Ismail, N Masseran Stochastic Environmental Research and Risk Assessment, 1-28, 2024 | | 2024 |
| Modeling Asymmetric Dependence Structure of Air Pollution Characteristics: A Vine Copula Approach MS Ismail, N Masseran, MA Alias, S Abu Bakar Mathematics 12 (4), 576, 2024 | | 2024 |
Mohd Salmi Md NooraniProfessor of Mathematics, Universiti Kebangsaan MalaysiaVerified email at ukm.edu.my
