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Machine learning and interactive GUI for concrete compressive strength prediction
Concrete compressive strength (CS) is a crucial performance parameter in concrete
structure design. Reliable strength prediction reduces costs and time in design and prevents …
structure design. Reliable strength prediction reduces costs and time in design and prevents …
Numerical and machine learning modeling of GFRP confined concrete-steel hollow elliptical columns
This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical
cross section. The investigation was carried out by gathering information through literature …
cross section. The investigation was carried out by gathering information through literature …
Stacked ensemble model for optimized prediction of triangular side orifice discharge coefficient
This research focuses on optimizing the prediction of discharge coefficient (Cd) of triangular
side orifices (TSO) using a novel stacked model (SM) incorporating five machine learning …
side orifices (TSO) using a novel stacked model (SM) incorporating five machine learning …
Enhancing discharge prediction over Type-A piano key weirs: An innovative machine learning approach
Piano key weirs (PKWs) are an increasingly popular hydraulic structure due to their higher
discharge capacity than linear weirs. Accurately predicting the discharge of PKWs is …
discharge capacity than linear weirs. Accurately predicting the discharge of PKWs is …
Machine learning models for predicting water quality index: optimization and performance analysis for El Moghra, Egypt
Assessing groundwater quality is vital for irrigation, but financial constraints in develo**
countries often result in infrequent sampling. This study comprehensively analyzes the …
countries often result in infrequent sampling. This study comprehensively analyzes the …
Determining seepage loss predictions in lined canals through optimizing advanced gradient boosting techniques
Ensuring accurate estimation of seepage loss is critical for advancing water sustainability,
especially in water-scarce regions. This study is aimed at evaluating the performance of …
especially in water-scarce regions. This study is aimed at evaluating the performance of …
Machine learning and interactive GUI for estimating roller length of hydraulic jumps
Hydraulic jumps reduce kinetic energy after ogee spillways, improve wastewater
chlorination, and serve many hydraulic applications. This study utilized seven Machine …
chlorination, and serve many hydraulic applications. This study utilized seven Machine …
Stacked-based machine learning to predict the uniaxial compressive strength of concrete materials
Compressive strength is a key factor in the design and durability of concrete structures.
Accurate prediction of compressive strength helps optimize material use and reduce …
Accurate prediction of compressive strength helps optimize material use and reduce …
Hydraulic assessment of different types of piano key weirs
ABSTRACT Piano Key Weir (PKW) is a non-linear weir with a small foundation footprint that
allows large discharges through a narrow channel. The presence of overhangs classifies it …
allows large discharges through a narrow channel. The presence of overhangs classifies it …
Stacked-based hybrid gradient boosting models for estimating seepage from lined canals
MK Elshaarawy - Journal of Water Process Engineering, 2025 - Elsevier
Accurate seepage loss estimation from lined canals is crucial for effective water
management, especially in water-scarce regions. This study explores seepage loss …
management, especially in water-scarce regions. This study explores seepage loss …