A5074534697- BIM and Construction Integration
- Hydrological Forecasting Using AI
- Construction Project Management and Performance
- Infrastructure Maintenance and Monitoring
- Water Systems and Optimization
- Hydrology and Drought Analysis
- Energy Load and Power Forecasting
- Municipal Solid Waste Management
- Recycled Aggregate Concrete Performance
- Sustainable Building Design and Assessment
- Hydrology and Watershed Management Studies
- Water Quality Monitoring Technologies
- Building Energy and Comfort Optimization
- Water resources management and optimization
- Occupational Health and Safety Research
- Multi-Criteria Decision Making
- COVID-19 epidemiological studies
- Flood Risk Assessment and Management
- COVID-19 impact on air quality
- Climate variability and models
- Irrigation Practices and Water Management
- Air Quality Monitoring and Forecasting
- Facilities and Workplace Management
- Non-Destructive Testing Techniques
- Urban Stormwater Management Solutions
National Research Centre
2018-2025
Housing and Building National Research Center
2018-2025
Hong Kong Polytechnic University
2023-2024
Cairo University
2023
Concordia University
2023
King Saud University
2023
The World Health Organization has declared COVID-19 as a global pandemic in early 2020. A comprehensive understanding of the epidemiological characteristics this virus is crucial to limit its spreading. Therefore, research applies artificial intelligence-based models predict prevalence outbreak Egypt. These are long short-term memory network (LSTM), convolutional neural network, and multilayer perceptron network. They trained validated using dataset records from 14 February 2020 15 August...
Forecasting meteorological and hydrological drought using standardized metrics of rainfall runoff (SPI/SRI) is critical for the long-term planning management water resources at global regional levels. In this study, various machine learning (ML) techniques including four methods (i.e., ANN, ANFIS, SVM, DT) were utilized to construct forecasting models in Wadi Ouahrane basin northern part Algeria. The performance ML was assessed evaluation criteria, RMSE, MAE, NSE, R2. results showed that all...
Water resources, land and soil degradation, desertification, agricultural productivity, food security are all adversely influenced by drought. The prediction of meteorological droughts using the standardized precipitation index (SPI) is crucial for water resource management. modeling results SPI at 3, 6, 9, 12 months based on five types machine learning: support vector (SVM), additive regression, bagging, random subspace, forest. After training, testing, cross-validation folds sub-basin 1,...
Modular construction (MC) is recognized as pivotal for sustainable development in developed countries. However, its implementation faces barriers residential projects developing nations. This study aims to address the knowledge gap resulting from limited uptake of MC projects, mainly attributed existing barriers. To accomplish this goal, a questionnaire survey was conducted assess significance thirty adoption Subsequently, an exploratory factor analysis method applied categorize these...
The construction industry is a key player in total energy consumption. design and of buildings shall be executed to minimize their negative environmental impacts. Many research studies have focused on reducing operational the past decades. As result, proportion embodied life cycle use has increased. This adopts holistic review method provide comprehensive systematic analysis literature related industry. A bibliometric applied obtain 269 papers from Web Science database during 1996–2020....
AbstractOver the past 20 years, value management (VM) has become a well-established technique, while in underdeveloped countries; informal methods are used for VM-related activities. This study aims to examine barriers VM deployment. These categorized into environment and culture, workshop dynamics, knowledge stakeholders standardization. A review of prior research is conducted identify these barriers, which further through semi-structured interview. The significance determined 335...
Rainfall–runoff modeling has been the core of hydrological research studies for decades. To comprehend this phenomenon, many machine learning algorithms have widely used. Nevertheless, a thorough comparison and effect pre-processing on their performance is still lacking in literature. Therefore, major objective to simulate rainfall runoff using nine standalone hybrid models. The conventional models include artificial neural networks, least squares support vector machines (LSSVMs), K-nearest...
Oil and gas pipelines are lifelines for a country’s economic survival. As result, they must be closely monitored to maximize their performance avoid product losses in the transportation of petroleum products. However, can collapse, resulting dangerous repercussions, financial losses, environmental consequences. Therefore, assessing pipe condition quality would great significance. Pipeline safety is ensured using variety inspection techniques, despite being time-consuming expensive. To...
Drought is one of the most severe climatic calamities, affecting many aspects environment and human existence. Effective planning decision making in disaster-prone areas require accurate reliable drought predictions globally. The selection an effective forecasting model still challenging due to lack information on performance, even though data-driven models have been widely employed anticipate droughts. Therefore, this study investigated application simple extreme learning machine (ELM)...
Purpose The stormwater industry grapples with numerous environmental challenges resulting from producing and using storm materials. Green building materials (GBMs) offer a more ecologically friendly alternative to conventional construction However, establishing criteria for selecting GBMs assessing their sustainability has proven be complex endeavor. Therefore, this paper aims assess the suitability of in management projects. Design/methodology/approach This study investigates identifies...
Purpose There have been numerous efforts to tackle the problem of accumulated construction and demolition wastes worldwide. In this regard, study develops a model for identifying optimum fleet required waste transportation. The proposed is validated through case from sector in New Cairo, Egypt. Design/methodology/approach Various combinations are assessed against time, cost, energy emissions generated Genetic algorithm optimization performed select near-optimum solutions. Complex...
Deteriorated water distribution networks require significant investments to maximize their functionality. The problem is that limited financial resources are allocated for rehabilitation strategies. This deficiency highlights the importance of developing a tool helps decision makers develop maintenance and replacement management plans. optimization employed using two evolutionary algorithms: genetic algorithms particle swarm optimization. efficacy developed model demonstrated through its...
Abstract The majority of water pipelines are subjected to serious deterioration and degradation challenges. This research examines the application optimized neural network models for estimating condition in Shaker Al-Bahery, Egypt. proposed hybrid compared against classical network, adaptive neuro-fuzzy inference system, group method data handling using four evaluation metrics. These metrics are; Fraction Prediction within a Factor Two (FACT2), Willmott's index agreement (WI), Root Mean...