Comparing Machine Learning Models For Predicting Water Pipelines Condition. - Nehal Elshaboury; Mohamed M. Marzouk (NILES, 2020)

On the Utilization of an Ensemble of Meta-Heuristics for Simulating Energy Consumption in Buildings. - Eslam Mohammed Abdelkader; Nehal Elshaboury; Abobakr Al-Sakkaf (Int. J. Appl. Metaheuristic Comput., 2022)

Prioritizing water distribution pipelines rehabilitation using machine learning algorithms. - Nehal Elshaboury; Mohamed M. Marzouk (Soft Comput., 2022)

Green artificial intelligence for cost-duration variance prediction (CDVP) for irrigation canals rehabilitation projects. - Haytham H. Elmousalami; Nehal Elshaboury; Ahmed H. Elyamany (Expert Syst. Appl., 2024)

Prediction of monthly groundwater level using a new hybrid intelligent approach in the Tabriz plain, Iran. - Ehsan Mirzania; Mohammed Achite; Nehal Elshaboury; Okan Mert Katipoglu; Mohsen Saroughi (Neural Comput. Appl., 2024)

Correction: Prediction of monthly groundwater level using a new hybrid intelligent approach in the Tabriz plain, Iran. - Ehsan Mirzania; Mohammed Achite; Nehal Elshaboury; Okan Mert Katipoglu; Mohsen Saroughi (Neural Comput. Appl., 2024)

Time-to-failure based deterioration factors of water networks: Systematic review and prioritization. - Beenish Bakhtawar; Tarek Zayed; Nehal Elshaboury (Reliab. Eng. Syst. Saf., 2025)