Results 211 to 220 of about 67,939 (291)

Developing and validating machine learning models to predict vaccine hesitancy and literacy among adults in the United States. [PDF]

Front Public Health
Zheng Y, Frew PM, Wang D, Song Y, Patterson-Lomba O, Feizi A, Li T, Eiden AL.   +7 more
europepmc   +1 more source

Identifying Faults in Power Transformers Based on Machine‐Learning Algorithms Compared With Other Techniques

Energy Science &Engineering, EarlyView.
General framework of ensemble learning technique for transformer fault diagnostics compared with traditional dissolved gas analysis methods. ABSTRACT This paper implemented a comprehensive variety of modern machine‐learning techniques, which were demonstrated to be effective in handling complex tabular data, generating accurate predictions, and ...
Osama E. Gouda, Nourhan Ramadan, Matti Lehtonen, Mohamed M. F. Darwish   +3 more
wiley   +1 more source

Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study. [PDF]

Intensive Care Med Exp
Yeh YC, Yang HY, Chiu CT, Chao A, Chuang YC, Chan WS.   +5 more
europepmc   +1 more source

A Rapid Post‐Disaster Restoration Method for Networked Microgrids Based on Adaptive Quantum Particle Swarm Optimization

Energy Science &Engineering, EarlyView.
To enhance the power restoration speed of networked microgrids (NMGs) after extreme natural disasters and reduce the power outage of the system, this paper proposes a rapid post‐disaster restoration method for NMGs based co‐optimization of fault repair and load restoration.
Yunfan Zhang, Qiang Li, Jun Zhang, Chaohuang Xu   +3 more
wiley   +1 more source

Modeling the Friction Behavior of Low-Carbon Steel Sheets Using Various Machine Learning Algorithms Based on Strip Drawing Test Data. [PDF]

Materials (Basel)
Trzepieciński T.
europepmc   +1 more source

Random Integrated Subdata Ensemble Method for Key Variable Selection in Rare Event Setting

Journal of Forecasting, EarlyView.
ABSTRACT We propose a general variable selection procedure to identify key input variables by applying elastic net regression to representative subdata in place of the full sample to select variables. We combine the lists of selected variables from each subdata through ensemble techniques, using the frequency of selecting the variable across different ...
Ching‐Chi Yang, Justin Deng, Lih‐Yuan Deng, Henry Horng‐Shing Lu   +3 more
wiley   +1 more source

Machine learning model for predicting hospital-acquired functional decline in older patients with postoperative cardiovascular surgery. [PDF]

World J Clin Cases
Hiramatsu R, Imaoka S, Minata S, Sako H, Sato N.   +4 more
europepmc   +1 more source

Exploring the Nexus Between Sustainability Index and Central European Stock Markets Competitiveness: Evidence Through Time–Frequency Analysis and SHAP

Journal of Forecasting, EarlyView.
ABSTRACT Sustainability has become an important factor shaping financial markets and investor behavior. This paper examines the relationship between sustainability indices and Central European stock markets using a time–frequency approach. Wavelet coherence is employed to capture time‐varying co‐movements between sustainability indices and stock market
Zuzana Janková, Dipak Kumar Jana, Michal Páleš, Elena Fleaca, Petr Dostál   +4 more
wiley   +1 more source