Nature

Ensemble machine learning models for predicting strength of concrete with foundry sand and coal bottom ash as fine aggregate replacements

Natural sand scarcity and environmental concerns have encouraged the adoption of industrial waste materials in sustainable concrete. Foundry sand (FS) and coal bottom ash (CBA), both industrial waste ...
Nature

Robust diabetic prediction using ensemble machine learning models with synthetic minority over-sampling technique

Millions of individuals throughout the world suffer from the chronic condition diabetes. It is characterized by elevated blood sugar levels due to inadequate insulin production or utilization. Insulin ...
pv magazine International

Ensemble deep learning for PV cell defect detection

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...
Medical Xpress

Integrating machine learning with statistical methods enhances disease risk prediction models

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...