A Missing Data Imputation Method for Gas Time Series Based on Spatio-Temporal Graph Attention Network-Echo State Network. [PDF]
Yang J, Qin K, Ye J, Zhao Y, Shu L.
europepmc +1 more source
Food Tastes in the United States: Convergence or Divergence?
ABSTRACT This study investigates how food consumption tastes have changed in recent decades across the United States. Using NielsenIQ data for over 77 million transactions, there is evidence of divergence in food tastes across regions from 2007 to 2016 and across households of different income, education, and race/ethnicity groups.
Michael DeDad
wiley +1 more source
Risk factor identification for large scale amusement facilities using mixture of experts and fusion of multiple models. [PDF]
Hao S, Xing L, Zhang M.
europepmc +1 more source
ABSTRACT Conceptual process design combines discrete configuration choices with continuous operating decisions, often yielding difficult mixed‐integer nonlinear or simulation‐based optimization problems. This work presents an exploratory computational assessment of Ising‐based solvers, simulated annealing, quantum annealing, and entropy computing, as ...
Yirang Park, David E. Bernal Neira
wiley +1 more source
AE-HGNN: attention-enhanced hypergraph neural networks for interpretable stress prediction through higher-order dependency modeling. [PDF]
Garg B +5 more
europepmc +1 more source
Machine learning driven many‐objective moving horizon scheduling optimization
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley +1 more source
Control flow graph based code optimization using graph neural networks. [PDF]
Peker M, Ozturk O.
europepmc +1 more source
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Why is it easier to predict the epidemic curve than to reconstruct the underlying contact network? [PDF]
Keliger D, Horváth I.
europepmc +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source

