Results 191 to 200 of about 60,468 (320)

Forecasting Local Ionospheric Parameters Using Transformers

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract We present a novel method for forecasting key ionospheric parameters using transformer‐based neural networks. The model provides accurate forecasts and uncertainty quantification of the F2‐layer peak plasma frequency (foF2), the F2‐layer peak density height (hmF2), and total electron content for a given geographic location.
D. J. Alford‐Lago, C. W. Curtis, A. T. Ihler, D. P. Drob, K. A. Zawdie   +4 more
wiley   +1 more source

SynQPF‐Net: Short‐Term Precipitation Forecasts by Integrating GraphCast Predictions and High‐Resolution Observational Analyses

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract While data‐driven global weather models (e.g., GraphCast) excel at large‐scale circulation forecasts, they exhibit systematic biases in heavy precipitation prediction due to European Centre for Medium‐Range Weather Forecasts Reanalysis (ERA5) uncertainties and neural networks' tendency to over‐smooth rainfall fields.
Dandan Chen, Dan Yao, Yaqiang Wang
wiley   +1 more source

Mitigating the Negative Transfer in Multi‐Task Learning for Harmful Language Detection in Spanish and Arabic

Expert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT Negative transfer continues to limit the benefits of multi‐task learning (MTL) in harmful language detection, where related tasks must share representations without diluting task‐specific nuances. We introduce task awareness (TA), a methodological framework that explicitly conditions MTL models on the task they must solve.
Angel Felipe Magnossão de Paula, Imene Bensalem, Damiano Spina, Paolo Rosso   +3 more
wiley   +1 more source

Optimal performance of simple low-cost optical physical unclonable functions resilient to machine learning attacks : ¹Eulambia advanced technologies Ltd., Athens, Greece, ²Department of informatics & Telecommunications, National and kapodistrian university of Athens, Athens, Greece. [PDF]

Sci Rep
Akriotou M, Bartsokas T, Veinidis C, Syvridis D.   +3 more
europepmc   +1 more source

Optimising Image Feature Extraction and Selection: A Comprehensive Review With Spark Case Studies

Expert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT As benchmark image datasets expand in sample size and feature complexity, the challenge of managing increased dimensionality becomes apparent. Contrary to the expectation that more features equate to enhanced information and improved outcomes, the curse of dimensionality often hampers performance.
J. Guzmán Figueira‐Domínguez, Beatriz Remeseiro, Verónica Bolón‐Canedo   +2 more
wiley   +1 more source

Design and Experimental Validation of a Photocatalyst Recommender Based on a Large Language Model

Angewandte Chemie, Volume 138, Issue 4, 22 January 2026.
Choosing a photocatalyst for a given reaction can be challenging due to complex mechanisms and multiple parameters that govern the outcome of a photocatalyzed reaction. Herein, we disclose a machine learning (ML) model that can suggest catalysts for a given reaction using an online portal.
Francis Millward, Michał Kulczykowski, Jay Badland‐Shaw, Sara Szymkuc, Rajan Suraksha, Aniket Kumar Srivastawa, Violaine Manet, Máire Griffin, Megan Bryden, Thomas Comerford, Lea Hämmerling, Aminata Mariko, Bartosz A. Grzybowski, Eli Zysman‐Colman   +13 more
wiley   +2 more sources

Deep Learning-Based Multi-Lead ECG Reconstruction from Lead I with Metadata Integration and Uncertainty Estimation. [PDF]

Sensors (Basel)
Nakanishi R, Hirata A, Kubota Y.
europepmc   +1 more source

Remaining Useful Life Prediction in an Aerospace Engine: A Multivariable Fuzzy Time Series Classification Approach

Expert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT Failures in safety‐critical systems such as aircraft engines pose severe economic and societal risks. This study introduces a novel Remaining Useful Life (RUL) prediction method uniquely combining diverse techniques. Specifically, the proposed methodology integrates fuzzy time series analysis with sliding window segmentation and Multinomial ...
Luiz Rogério de Freitas Júnior, Frederico Gadelha Guimarães   +1 more
wiley   +1 more source