Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley +1 more source
Multidimensional EEG features integration with feature selection strategy for precision diagnosis of depressive disorders. [PDF]
Luo X +6 more
europepmc +1 more source
Mid‐Infrared Spectroscopy and Machine Learning for Chlorogenic Acid Quantification in Coffee
Chlorogenic acid (CGA) concentration in coffee was predicted using mid‐infrared (MIR) spectroscopy and a machine learning approach. Forty‐four roasting stages (140–220 °C) plus a green coffee control were analyzed. A multilayer perceptron regressor, trained on preprocessed MIR data, outperformed traditional peak analysis, enabling accurate and ...
Deborah Herdt +6 more
wiley +1 more source
Analysis and Enhancement of Prediction of Cardiovascular Disease Diagnosis using Machine Learning Models SVM, SGD, and XGBoost [PDF]
Sandeep Tomar +2 more
openalex +1 more source
Classification of Mammography Images Based on Multifractal Analysis of BIMFs. [PDF]
Ghazi F +4 more
europepmc +1 more source
Research frontiers in using biochar for heavy metal remediation. Abstract Heavy metal contamination of water has long been a serious environmental issue. Biochar and biochar‐based composites are emerging as effective and sustainable solutions for heavy metal removal due to their strong adsorption abilities and environmentally friendly nature.
Soumik Chakma +4 more
wiley +1 more source
A Novel Integrated SVM for Fault Diagnosis Using KPCA and GA
Jinning Li
openalex +1 more source
A hybrid CNN-ViT based framework for automatic traffic actions detection in smart cities. [PDF]
Karaduman M +5 more
europepmc +1 more source
Predicting solar cell efficiencies using historical data from a manufacturing process
Abstract The solar cell manufacturing data of a passivated emitter and rear cell solar cell manufacturing plant was studied to assess the effects of tool usage and the processing time spent on each tool on the solar cell efficiency. Since manufacturing processes involve several steps with multiple tools, tracing their quality parameters back to the ...
Sushmita Mittra, Vinay Prasad
wiley +1 more source

