Results 141 to 150 of about 8,161 (262)

A robust solution for power grid management using a hybrid deterministic and probabilistic model for short term load forecasting. [PDF]

Sci Rep
Serttas F.
europepmc   +1 more source

A Hybrid Approach to Short-Term Load Forecasting Aimed at Bad Data Detection in Secondary Substation Monitoring Equipment. [PDF]

Sensors (Basel), 2018
Martín P, Moreno G, Rodríguez FJ, Jiménez JA, Fernández I.   +4 more
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

A dataset of exogenous variables and historical electricity demand for short-term load forecasting of the national interconnected electric system (SENI) in the Dominican Republic from 2021 to 2024. [PDF]

Data Brief
Uceta-Acosta RO, Mariano-Hernandez D, Rivas-Peña Y, Ocaña-Guevara VS, Aybar-Mejía M, Domínguez-Garabitos MA.   +5 more
europepmc   +1 more source

Fisher Information Based Meteorological Factors Introduction and Features Selection for Short-Term Load Forecasting. [PDF]

Entropy (Basel), 2018
Cai S, Liu L, Sun H, Yan J.
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

REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13. [PDF]

PeerJ Comput Sci
Miah MSU, Sulaiman J, Islam MI, Masuduzzaman M, Lipu MSH, Nugraha R.   +5 more
europepmc   +1 more source

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

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