Results 241 to 250 of about 93,376 (303)
Integrating event information and multi dimensional relationships for improved financial time series forecasting. [PDF]
Du X +7 more
europepmc +1 more source
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca +9 more
wiley +1 more source
FCP-Former: Enhancing Long-Term Multivariate Time Series Forecasting with Frequency Compensation. [PDF]
Li M +5 more
europepmc +1 more source
A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
4D hypercomplex-valued neural network in multivariate time series forecasting. [PDF]
Kycia R, Niemczynowicz A.
europepmc +1 more source
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim +3 more
wiley +1 more source
CLM-former for enhancing multi-horizon time series forecasting and load prediction in smart microgrids using a robust transformer-based model. [PDF]
Rahmatinia SM +2 more
europepmc +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Timestamp-Guided Knowledge Distillation for Robust Sensor-Based Time-Series Forecasting. [PDF]
Yan J, Li H, Bai Y, Liu J, Lv H, Bai Y.
europepmc +1 more source

