Results 181 to 190 of about 128,623 (299)

Improved Neural Networks with Random Weights for Short-Term Load Forecasting. [PDF]

PLoS One, 2015
Lang K, Zhang M, Yuan Y.
europepmc   +1 more source

Race and Household Income are Associated with Disease Outcomes in Pediatric Patients with ANCA‐associated Vasculitis Hospitalized in the United States

Arthritis Care &Research, Accepted Article.
Objectives Race and household income impact outcomes in patients with rheumatic conditions; however, their role in pediatric anti‐neutrophil cytoplasmic antibody (ANCA)‐associated vasculitis (AAV) remains poorly understood. We aimed to evaluate whether race/ethnicity and household income are associated with severe AAV disease and renal outcomes among ...
Roberto Alejandro Valdovinos, William Daniel Soulsby III, Emily von Scheven   +2 more
wiley   +1 more source

UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data. [PDF]

Sci Rep
Zhou S, Zhang Q, Xiao P, Xu B, Luo G.
europepmc   +1 more source

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

Deep learning-driven hybrid model for short-term load forecasting and smart grid information management. [PDF]

Sci Rep
Wen X, Liao J, Niu Q, Shen N, Bao Y.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Planar Solid‐State Nanopores Toward Scalable Nanofluidic Integration Based on CMOS Technology

Advanced Engineering Materials, EarlyView.
We present a scalable silicon‐based fabrication strategy for planar solid‐state nanopores to enable their integration with complex nanofluidic systems. Prototype devices demonstrate normal voltage‐current characteristics, good noise performance, and appreciable streaming currents. Our CMOS‐compatible fabrication process offers precise geometric control
Ngan Hoang Pham, Chenyu Wen, Mohammad Hadi Khaksaran, Won‐Yong Lee, Javier Cruz, Klas Hjort, Dongping Wu, Shi‐Li Zhang   +7 more
wiley   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +3 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Fuzzy Clustering-Based Deep Learning for Short-Term Load Forecasting in Power Grid Systems Using Time-Varying and Time-Invariant Features. [PDF]

Sensors (Basel)
Chan KY, Yiu KFC, Kim D, Abu-Siada A.
europepmc   +1 more source