| Predictive model for assessing and optimizing solar still performance using artificial neural network under hyper arid environment AF Mashaly, AA Alazba, AM Al-Awaadh, MA Mattar Solar Energy 118, 41-58, 2015 | 88 | 2015 |
| MLP and MLR models for instantaneous thermal efficiency prediction of solar still under hyper-arid environment AF Mashaly, AA Alazba Computers and Electronics in Agriculture 122, 146-155, 2016 | 69 | 2016 |
| Identifying capabilities and potentials of system dynamics in hydrology and water resources as a promising modeling approach for water management AF Mashaly, AG Fernald Water 12 (5), 1432, 2020 | 61 | 2020 |
| Thermal performance analysis of an inclined passive solar still using agricultural drainage water and artificial neural network in arid climate AF Mashaly, AA Alazba Solar Energy 153, 383-395, 2017 | 47 | 2017 |
| Assessing the performance of solar desalination system to approach near-ZLD under hyper arid environment AF Mashaly, AA Alazba, AM Al-Awaadh Desalination and Water Treatment 57 (26), 12019–12036, 2016 | 32 | 2016 |
| Neural network approach for predicting solar still production using agricultural drainage as a feedwater source AF Mashaly, AA Alazba Desalination and Water Treatment 57 (59), 28646-28660, 2016 | 30 | 2016 |
| Comparative investigation of artificial neural network learning algorithms for modeling solar still production AF Mashaly, AA Alazba Journal of Water Reuse and Desalination 5 (4), 480-493, 2015 | 30 | 2015 |
| Area determination of solar desalination system for irrigating crops in greenhouses using different quality feed water AF Mashaly, AA Alazba, AM Al-Awaadh, MA Mattar Agricultural Water Management 154, 1-10, 2015 | 25 | 2015 |
| Comparison of ANN, MVR, and SWR models for computing thermal efficiency of a solar still AF Mashaly, AA Alazba International Journal of Green Energy 13 (10), 1016-1025, 2016 | 22 | 2016 |
| ANFIS modeling and sensitivity analysis for estimating solar still productivity using measured operational and meteorological parameters AF Mashaly, AA Alazba Water Science and Technology: Water Supply 18 (4), 1437-1448, 2018 | 20 | 2018 |
| Application of adaptive neuro-fuzzy inference system (ANFIS) for modeling solar still productivity AF Mashaly, AA Alazba Journal of Water Supply: Research and Technology—AQUA 66 (6), 367-380, 2017 | 18 | 2017 |
| Artificial intelligence for predicting solar still production and comparison with stepwise regression under arid climate AF Mashaly, AA Alazba Journal of Water Supply: Research and Technology—AQUA 66 (3), 166-177, 2017 | 13 | 2017 |
| Assessing the accuracy of ANN, ANFIS, and MR techniques in forecasting productivity of an inclined passive solar still in a hot, arid environment AF Mashaly, AA Alazba Water SA 45 (2), 239-250, 2019 | 12 | 2019 |
| Membership function comparative investigation on productivity forecasting of solar still using adaptive neuro‐fuzzy inference system approach AF Mashaly, AA Alazba Environmental Progress & Sustainable Energy 37 (1), 249–259, 2018 | 12 | 2018 |
| Experimental and modeling study to estimate the productivity of inclined passive solar still using ANN methodology in arid conditions AF Mashaly, AA Alazba Journal of Water Supply: Research and Technology-Aqua 67 (4), 332-346, 2018 | 5 | 2018 |
| Analyzing and Assessing Dynamic Behavior of a Physical Supply and Demand System for Sustainable Water Management under a Semi-Arid Environment AF Mashaly, AG Fernald Water 14 (12), 1939, 2022 | 3 | 2022 |
| Comparison of adaptive neuro-fuzzy inference system and multiple nonlinear regression for the productivity prediction of inclined passive solar still AF Mashaly, AA Alazba Journal of Water Supply: Research and Technology—AQUA 68 (2), 98-110, 2019 | 2 | 2019 |
