Results 211 to 220 of about 45,151 (266)

Risk of Retinopathy Associated with Long‐Term Use of Hydroxychloroquine in Patients with Rheumatic Diseases: A Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among patients receiving long‐term HCQ with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain optical coherence tomography (SD‐OCT) for screening ...
Narsis Daftarian, Chloe Yue, Steve D Levasseur, Hui Xie, J. Antonio Avina‐Zubieta   +4 more
wiley   +1 more source

A Combined Persistence and Physical Approach for Ultra-Short-Term Photovoltaic Power Forecasting Using Distributed Sensors. [PDF]

Sensors (Basel)
Malinkovich Y, Sitbon M, Lineykin S, Dagan KJ, Baimel D.   +4 more
europepmc   +1 more source

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques. [PDF]

Sci Rep
Guermoui M, Fezzani A, Mohamed Z, Rabehi A, Ferkous K, Bailek N, Bouallit S, Riche A, Bajaj M, Dost Mohammadi SA, Ali E, Ghoneim SSM.   +11 more
europepmc   +1 more source

Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions. [PDF]

Sci Rep
Belletreche M, Bailek N, Abotaleb M, Bouchouicha K, Zerouali B, Guermoui M, Kuriqi A, Alharbi AH, Khafaga DS, El-Shimy M, El-Kenawy EM.   +10 more
europepmc   +1 more source

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Building power demand forecasting

it - Information Technology, 2016
Abstract Buildings acting as flexible loads have been often proposed to mitigate the volatility of renewable energy sources. Thereby, an accurate short-term demand forecast is indispensable for effective demand side management. At the same time, standardized load profiles, commonly used in the distribution grid, are inadequate for load ...
Valgaev, Oleg, Kupzog, Friederich
openaire   +3 more sources

A Fast and Stable Forecasting Model to Forecast Power Load

International Journal of Pattern Recognition and Artificial Intelligence, 2015
As the traditional gray forecasting model GM(1, 1) has poor performance in forecasting the fast-growing power load, we present a chaotic co-evolutionary particle swarm optimization (CCPSO) algorithm, one with better efficiency than the PSO algorithm. Based on the GM(1, 1) model, the CCPSO algorithm is adopted to solve the values of parameters a and b ...
Li-Zhi Tan, Aijia Ouyang, Xuyu Peng, Er-Xi Li, Tung Khac Truong, Libo Hao   +5 more
openaire   +1 more source

Wind Power Forecasting

2014
The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble modeling with artificial intelligence methods. This state-of-the-science forecasting system includes specific technologies for short-term detection of wind power ramps, including a Variational ...
Sue Ellen Haupt, William P. Mahoney, Keith Parks   +2 more
openaire   +2 more sources

Fresh forecasts [wind power forecasting]

Power Engineer, 2005
Wind power forecasting falls broadly into two headings: statistical or physical modelling. Statistical modelling makes no real attempt to model the physical processes that drive the wind, but relies on previous wind speed patterns over time to make a prediction.
openaire   +1 more source

Assessment of power curves in models of wind power forecasting

2016 International Joint Conference on Neural Networks (IJCNN), 2016
The modeling of wind power curve is important in turbine performance monitoring and in wind power forecasting. There are several techniques to fit the power curve of a wind turbine, which can be classified into parametric and nonparametric methods. This paper explores the advantages offered by the nonparametric methods for modeling of wind turbine ...
Ronaldo Ribeiro Barbosa de Aquino, Jonata C. de Albuquerque, Otoni Nóbrega Neto, Milde M. S. Lira, Manoel A. Carvalho, Alcides Codeceira Neto, Aida Araujo Ferreira   +6 more
openaire   +1 more source

Machine Learning for Wind Power Forecasting

2021 International Joint Conference on Neural Networks (IJCNN), 2021
In recent years, Brazil has been increasing research and consequently the use of another type of energy generation, wind power, which is currently the second largest source of energy generation in the country. This work aims to develop wind speed forecasting models, using artificial intelligence techniques, including Deep Artificial Neural Networks ...
Yann Fabricio Cardoso de Figueiredo, Lídio Mauro Lima de Campos   +1 more
openaire   +1 more source