Application of artificial neural networks to predict the COVID-19 outbreak HR Niazkar, M Niazkar Global Health Research and Policy 5 (1), 1-11, 2020 | 128 | 2020 |
COVID-19 Outbreak: Application of Multi-gene Genetic Programming to Country-based Prediction Models M Niazkar, HR Niazkar Electronic Journal of General Medicine 17 (5), 2020 | 70 | 2020 |
Assessment of modified honey bee mating optimization for parameter estimation of nonlinear Muskingum models M Niazkar, SH Afzali Journal of Hydrologic Engineering 20 (4), 04014055, 2015 | 69 | 2015 |
Analysis of water distribution networks using MATLAB and Excel spreadsheet: h‐based methods M Niazkar, SH Afzali Computer Applications in Engineering Education 25 (1), 129-141, 2017 | 61 | 2017 |
Application of new hybrid optimization technique for parameter estimation of new improved version of Muskingum model M Niazkar, SH Afzali Water resources management 30, 4713-4730, 2016 | 54 | 2016 |
Applications of innovative polygonal trend analyses to precipitation series of Eastern Black Sea Basin, Turkey T Hırca, G Eryılmaz Türkkan, M Niazkar Theoretical and Applied Climatology 147 (1), 651-667, 2022 | 45 | 2022 |
Streamline performance of Excel in stepwise implementation of numerical solutions M Niazkar, SH Afzali Computer Applications in Engineering Education 24 (4), 555-566, 2016 | 41 | 2016 |
Parameter estimation of an improved nonlinear Muskingum model using a new hybrid method M Niazkar, SH Afzali Hydrology Research 48 (5), 1253-1267, 2017 | 38 | 2017 |
Optimum design of lined channel sections M Niazkar, SH Afzali Water Resources Management 29, 1921-1932, 2015 | 37 | 2015 |
New nonlinear variable-parameter Muskingum models M Niazkar, SH Afzali KSCE Journal of Civil Engineering 21, 2958-2967, 2017 | 35 | 2017 |
Assessment of artificial intelligence models for calculating optimum properties of lined channels M Niazkar Journal of Hydroinformatics 22 (5), 1410-1423, 2020 | 34 | 2020 |
Assessment of Artificial Intelligence Models for Developing Single‐Value and Loop Rating Curves M Niazkar, M Zakwan Complexity 2021 (1), 6627011, 2021 | 32 | 2021 |
Revisiting the estimation of Colebrook friction factor: a comparison between artificial intelligence models and CW based explicit equations M Niazkar KSCE Journal of Civil Engineering 23 (10), 4311-4326, 2019 | 32 | 2019 |
Novel grain and form roughness estimator scheme incorporating artificial intelligence models M Niazkar, N Talebbeydokhti, SH Afzali Water resources management 33, 757-773, 2019 | 32 | 2019 |
Application of Excel spreadsheet in engineering education M Niazkar, SH Afzali First International & Fourth National Conference on Engineering Education, 2015 | 32 | 2015 |
Assessment of three mathematical prediction models for forecasting the covid‐19 outbreak in Iran and Turkey M Niazkar, G Eryılmaz Türkkan, HR Niazkar, YA Türkkan Computational and mathematical methods in medicine 2020 (1), 7056285, 2020 | 31 | 2020 |
A Comparative Analysis of Data‐Driven Empirical and Artificial Intelligence Models for Estimating Infiltration Rates M Zakwan, M Niazkar Complexity 2021 (1), 9945218, 2021 | 23 | 2021 |
Machine learning-based downscaling: Application of multi-gene genetic programming for downscaling daily temperature at Dogonbadan, Iran, under CMIP6 scenarios M Niazkar, MR Goodarzi, A Fatehifar, MJ Abedi Theoretical and Applied Climatology 151 (1), 153-168, 2023 | 22 | 2023 |
One dimensional hydraulic flow routing incorporating a variable grain roughness coefficient M Niazkar, N Talebbeydokhti, SH Afzali Water Resources Management 33, 4599-4620, 2019 | 22 | 2019 |
Developing a new accuracy-improved model for estimating scour depth around piers using a hybrid method M Niazkar, SH Afzali Iranian Journal of Science and Technology, Transactions of Civil Engineering …, 2019 | 22 | 2019 |