| Lobatto-Milstein Numerical Method in Application of Uncertainty Investment of Solar Power Projects MA Eissa, B Tian Energies 10 (1), 43, 2017 | 28 | 2017 |
| Convergence and stability of split-step theta methods with variable step-size for stochastic pantograph differential equations Y Xiao, MA Eissa, B Tian International Journal of Computer Mathematics 95 (5), 939-960, 2018 | 11 | 2018 |
| Mean‐Square Stability of Split‐Step Theta Milstein Methods for Stochastic Differential Equations MA Eissa, H Zhang, Y Xiao Mathematical Problems in Engineering 2018 (1), 1682513, 2018 | 9 | 2018 |
| Bio-Cyber Interface Parameter Estimation with Neural Network for the Internet of Bio-Nano Things S Mohamed, J Dong, SMA El-Atty, MA Eissa Wireless Personal Communications 123 (2), 1245-1263, 2022 | 8 | 2022 |
| Stochastic Epidemic Model for COVID-19 Transmission under Intervention Strategies in China ZT Win, MA Eissa, B Tian Mathematics 10 (17), 3119, 2022 | 7 | 2022 |
| A stochastic corporate claim value model with variable delay MA Eissa, B Tian Journal of Physics: Conference Series 1053 (1), 012018, 2018 | 7 | 2018 |
| Two families of theta milstein methods in a real options framework B Tian, MA Eissa, S Zhang Proceedings of the 5th Annual International Conference on Computational …, 2016 | 7 | 2016 |
| System of Ordinary Differential Equations Solving Using Cellular Neural Networks MA Ramadan, TS ElDanaf, MA Eissa Journal of Advanced Mathematics and Applications 3 (2), 182-194, 2014 | 7 | 2014 |
| Investigation of dust ion acoustic shock waves in dusty plasma using Cellular Neural Network EE Behery, SK El-Labany, MM Selim, TH Khalil, MA Eissa Physica Scripta 96 (9), 095606, 2021 | 6 | 2021 |
| Lobatto-milstein numerical method in application of uncertainty investment of solar power projects. Energies, 10 (1), 43 MA Eissa, B Tian | 6 | 2017 |
| Potential influence of information systems on bank risk A Alfarra, H Xiaofeng, A Hagag, MA Eissa IAENG International Journal of Computer Science 44 (2), 188-196, 2017 | 5 | 2017 |
| Convergence and Stability of Two Classes of Theta Methods with Variable Step Size for a Stochastic Pantograph Equations MA Eissa, Y Xiao, B Tian Journal of Advanced Mathematics and Applications 5 (2), 95-106, 2016 | 5 | 2016 |
| Approximate Solutions of Partial Differential Equations using Cellular Neural Networks MA Ramadan, TS El-Danaf, MA Eissa | 5 | 2015 |
| Mean-square stability of two classes of theta milstein methods for nonlinear stochastic differential equations MA Eissa Proc. Jangjeon Math. Soc 22, 119-128, 2019 | 4 | 2019 |
| Improve Stock Price Model-Based Stochastic Pantograph Differential Equation MA Eissa, M Elsayed Symmetry 14 (7), 1358, 2022 | 3 | 2022 |
| Convergence, non-negativity and stability of a new Lobatto IIIC-Milstein method for a pricing option approach based on stochastic volatility model MA Eissa, Q Ye Japan Journal of Industrial and Applied Mathematics 38 (2), 391-424, 2021 | 2 | 2021 |
| Numerical Solutions Using Cellular Neural Networks: How to Use Cellular Neural Networks to Approximate Ordinary and Partial Differential Equations MA Eissa, TS ElDanaf, MA Ramadan Publisher: LAP LAMBERT Academic Publishing, Editor: Carolyn Evans, ISBN: 978 …, 2016 | 2 | 2016 |
| Quintic B-Spline Method for Solving Sharma Tasso Oliver Equation TS Eldanaf, M Elsayed, MA Eissa, FEE Abd Alaal Journal of Applied Mathematics and Physics 10 (12), 3920-3936, 2022 | 1 | 2022 |
| Modified Split-Step Theta Milstein Methods for M-Dimensional Stochastic Differential Equation With Respect To Poisson-Driven Jump MA Eissa, F Tian, B Tian Appl. Math 14 (6), 1147-1161, 2020 | | 2020 |
| Research Article Mean-Square Stability of Split-Step Theta Milstein Methods for Stochastic Differential Equations MA Eissa, H Zhang, Y Xiao | | 2018 |
Ahmed HagagLecturer, Scientific Computing Department, Faculty of Computers and Artificial Intelligence, BenhaAdresse e-mail validée de fci.bu.edu.eg