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Showing 6 of 6 academic articles

Extrapolative prediction in multiphase flow pipelines: a multi-fidelity surrogate approach with stacking ensemble

Pengcheng Cao, Kai Wang, Ting Zhang, Lihui Yang • Engineering Applications of Computational Fluid Mechanics (2026)

Accurate extrapolation of multiphase flow behaviour in offshore pipelines is hindered by limited field data, simulator bias, and strong nonlinearities. A multi-fidelity surrogate approach with stacking ensemble is proposed to address these ...

DOAJ Open Access (DOAJ) DOI: 10.1080/19942060.2026.2646081

Day-Ahead Electric Load Forecasting for the Residential Building with a Small-Size Dataset Based on a Self-Organizing Map and a Stacking Ensemble Learning Method

Jaehyun Lee, Jinho Kim, Woong Ko • Applied Sciences (2019)

Electric load forecasting for buildings is important as it assists building managers or system operators to plan energy usage and strategize accordingly. Recent increases in the adoption of advanced metering infrastructure (AMI) have made b...

DOAJ Open Access (DOAJ) DOI: 10.3390/app9061231

Comprehensive framework of machine learning and deep learning architectures with metaheuristic optimization for high-fidelity prediction of nanofluid specific heat capacity

Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports (2025)

Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-28268-z

Stacking Ensemble Approach for Churn Prediction: Integrating CNN and Machine Learning Models with CatBoost Meta-Learner

Tan Yan Lin, Pang Ying Han, Ooi Shih Yin, Khoh Wee How et al. • Journal of Engineering Technology and Applied Physics (2023)

In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...

DOAJ Open Access (DOAJ) DOI: 10.33093/jetap.2023.5.2.12

An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients

Faezeh Aghamirzaei, Ahmad Ali Abin, Farzaneh Futuhi • Archives of Academic Emergency Medicine (2025)

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble ma...

DOAJ Open Access (DOAJ) DOI: 10.22037/aaemj.v13i1.2560