Nexus between trade, CO2 emissions, renewable energy, and health expenditure in Pakistan I Ullah, A Rehman, FU Khan, MH Shah, F Khan The International journal of health planning and management 35 (4), 818-831, 2020 | 92 | 2020 |
A comparative analysis of machine learning models: a case study in predicting chronic kidney disease H Iftikhar, M Khan, Z Khan, F Khan, HM Alshanbari, Z Ahmad Sustainability 15 (3), 2754, 2023 | 36 | 2023 |
On predictive modeling using a new flexible Weibull distribution and machine learning approach: Analyzing the COVID-19 data Z Ahmad, Z Almaspoor, F Khan, M El-Morshedy Mathematics 10 (11), 1792, 2022 | 27 | 2022 |
Estimation of finite population mean using dual auxiliary variable for non-response using simple random sampling S Ahmad, S Hussain, M Aamir, F Khan, MN Alshahrani, M Alqawba Aims Mathematics 7 (3), 4592-4613, 2022 | 22 | 2022 |
A novel probabilistic approach based on trigonometric function: model, theory with practical applications OH Odhah, HM Alshanbari, Z Ahmad, F Khan, AAAH El-Bagoury Symmetry 15 (8), 1528, 2023 | 20 | 2023 |
The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models F Khan, S Muhammadullah, A Sharif, CC Lee Energy Economics 130, 107269, 2024 | 18 | 2024 |
An application of hybrid models for weekly stock market index prediction: Empirical evidence from SAARC countries Z Peng, FU Khan, F Khan, PA Shaikh, D Yonghong, I Ullah, F Ullah Complexity 2021 (1), 5663302, 2021 | 18 | 2021 |
Revisiting the relationship between remittances and CO2 emissions by applying a novel dynamic simulated ARDL: empirical evidence from G-20 economies FU Khan, A Rafique, E Ullah, F Khan Environmental Science and Pollution Research 29 (47), 71190-71207, 2022 | 15 | 2022 |
A new probability distribution: model, theory and analyzing the recovery time data HM Alshanbari, OH Odhah, Z Ahmad, F Khan, AAAH El-Bagoury Axioms 12 (5), 477, 2023 | 14 | 2023 |
Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms FU Khan, F Khan, PA Shaikh Future Business Journal 9 (1), 25, 2023 | 12 | 2023 |
A new modification of the flexible Weibull distribution based on power transformation: Monte Carlo simulation and applications F Khan, Z Ahmad, SK Khosa, MA Alomair, AM Alomair, A khalid Alsharidi Heliyon 9 (6), 2023 | 12 | 2023 |
On fitting and forecasting the log-returns of cryptocurrency exchange rates using a new logistic model and machine learning algorithms Z Ahmad, Z Almaspoor, F Khan, SE Alhazmi, M El-Morshedy, ... AIMS Math 7, 18031-18049, 2022 | 12 | 2022 |
On the implementation of a new version of the Weibull distribution and machine learning approach to model the COVID-19 data Y Zhou, Z Ahmad, Z Almaspoor, F Khan, E Tag-Eldin, Z Iqbal, ... Mathematical biosciences and engineering: MBE 20 (1), 337-364, 2023 | 11 | 2023 |
Comparison of Weighted Lag Adaptive LASSO with Autometrics for Covariate Selection and Forecasting Using Time‐Series Data S Muhammadullah, A Urooj, F Khan, MN Alshahrani, M Alqawba, ... Complexity 2022 (1), 2649205, 2022 | 11 | 2022 |
An ARIMA-ANN hybrid model for monthly gold price forecasting: empirical evidence from Pakistan F Khan, A Urooj, S Muhammadullah Pakistan Econ Rev 4 (1), 61-75, 2021 | 10 | 2021 |
Predictive modeling of the COVID-19 data using a new version of the flexible Weibull model and machine leaning techniques RA Bantan, Z Ahmad, F Khan, M Elgarhy, Z Almaspoor, GG Hamedani, ... Math. Biosci. Eng 20 (2), 2847-2873, 2023 | 9 | 2023 |
Evaluating the performance of feature selection methods using huge big data: a Monte Carlo simulation approach F Khan, A Urooj, SA Khan, SK Khosa, S Muhammadullah, Z Almaspoor Mathematical Problems in Engineering 2022 (1), 6607330, 2022 | 8 | 2022 |
A comparison of Autometrics and penalization techniques under various error distributions: evidence from Monte Carlo simulation F Khan, A Urooj, K Ullah, B Alnssyan, Z Almaspoor Complexity 2021 (1), 9223763, 2021 | 8 | 2021 |
Comparing the forecast performance of advanced statistical and machine learning techniques using huge big data: evidence from Monte Carlo experiments F Khan, A Urooj, SA Khan, A Alsubie, Z Almaspoor, S Muhammadullah Complexity 2021 (1), 6117513, 2021 | 7 | 2021 |
A new family of distributions using a trigonometric function: Properties and applications in the healthcare sector OH Odhah, HM Alshanbari, Z Ahmad, F Khan, AAH El-Bagoury Heliyon 10 (9), 2024 | 6 | 2024 |