A machine learning-based analysis for predicting fragility curve parameters of buildings
Fragility curves are one of the substantial means required for seismic risk assessment of
buildings in the framework of performance-based earthquake engineering (PBEE) …
buildings in the framework of performance-based earthquake engineering (PBEE) …
[KİTAP][B] Biochar and application of machine learning: a review
This study discusses biochar and machine learning application. Concept of biochar,
machine learning and different machine learning algorithms used for predicting adsorption …
machine learning and different machine learning algorithms used for predicting adsorption …
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 …
[HTML][HTML] Compressive strength of concrete containing furnace blast slag; optimized machine learning-based models
Abstract Replacing Ordinary Portland Cement (OPC) with industrial waste like Ground
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …
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 …
[HTML][HTML] Compressive strength of concrete material using machine learning techniques
Significant efforts have been made to improve the strength of concrete by utilizing industrial
waste like Fly Ash as a partial replacement of cement in the concrete. However, predicting …
waste like Fly Ash as a partial replacement of cement in the concrete. However, predicting …
Machine learning methods for identification and classification of events in ϕ-OTDR systems: a review
The phase sensitive optical time-domain reflectometer (φ-OTDR), or in some applications
called distributed acoustic sensing (DAS), has been a popularly used technology for long …
called distributed acoustic sensing (DAS), has been a popularly used technology for long …
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 …
Spatial variations and health risk assessment of heavy metal levels in groundwater of Qatar
The present work's objective is to give a comprehensive overview of the quality of
groundwater in Qatar in terms of heavy metals content as well as investigating the cause …
groundwater in Qatar in terms of heavy metals content as well as investigating the cause …
Improved intelligent methods for power transformer fault diagnosis based on tree ensemble learning and multiple feature vector analysis
This paper discusses the impact of the feature input vector on the performance of dissolved
gas analysis-based intelligent power transformer fault diagnosis methods. For this purpose …
gas analysis-based intelligent power transformer fault diagnosis methods. For this purpose …