11 Result(s)
within
Mohammed Majeed Hameed
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Article
Open AccessInvestigating a hybrid extreme learning machine coupled with Dingo Optimization Algorithm for modeling liquefaction triggering in sand-silt mixtures
Liquefaction is a devastating consequence of earthquakes that occurs in loose, saturated soil deposits, resulting in catastrophic ground failure. Accurate prediction of such geotechnical parameter is crucial f...
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Article
Open AccessIntroducing high-order response surface method for improving scour depth prediction downstream of weirs
Scour depth downstream of weirs is considered one of the most important hydraulic problems, which greatly influences the stability of weirs. Recently, artificial intelligence (AI) methods have become increasin...
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Article
Improving multi-month hydrological drought forecasting in a tropical region using hybridized extreme learning machine model with Beluga Whale Optimization algorithm
Climate change has increased drought frequency globally, which harms the environment, agriculture, and water resources. This study explores the capacity of a hybrid model based on the integration of extreme le...
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Article
Open AccessImproving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm
Fine particulate matter (PM2.5) is a significant air pollutant that drives the most chronic health problems and premature mortality in big metropolitans such as Delhi. In such a context, accurate prediction of PM
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Article
Inflow forecasting using regularized extreme learning machine: Haditha reservoir chosen as case study
For effective water resource management, water budgeting, and optimal release discharge from a reservoir, the accurate prediction of daily inflow is critical. An attempt has been made using artificial intellig...
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Article
Prediction of high-strength concrete: high-order response surface methodology modeling approach
In the concrete industry, compressive strength is the most essential mechanical property. Therefore, insufficient compressive strength may lead to dangerous failure and, thus, becomes very difficult to repair....
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Article
Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model
The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding ...
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Chapter and Conference Paper
Applying an Efficient AI Approach for the Prediction of Bearing Capacity of Shallow Foundations
This study focused on presenting the potential of artificial intelligence (AI) modeling approach to predict the bearing capacity ( $${\text{Q}}...
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Article
Incorporation of artificial neural network with principal component analysis and cross-validation technique to predict high-performance concrete compressive strength
Compressive strength is the most essential mechanical characterization for concrete due to its crucial role in stating the design standards. Therefore, early, and accurate evaluation of concrete compressive st...
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Chapter and Conference Paper
Prediction of Compressive Strength of High-Performance Concrete: Hybrid Artificial Intelligence Technique
Compressive strength is the most important mechanical property of concrete due to its significant role in numerous design codes and standards. Precise and early estimation of compressive strength of concrete c...
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Article
ANN Based Sediment Prediction Model Utilizing Different Input Scenarios
Modeling sediment load is a significant factor in water resources engineering as it affects directly the design and management of water resources. In this study, artificial neural networks (ANNs) are employed ...
