Results 131 to 140 of about 72,416 (315)

Short-term load forecasting based on a semi-parametric additive model [PDF]

Short-term load forecasting is an essential instrument in power system planning, operation and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance ...
Rob Hyndman, Shu Fan
core  

CX3CL1 in Early Detection of Alzheimer's Disease: Plasma Dynamics Across Age and Disease Stages

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Backgrounds Alzheimer's disease (AD) is characterized by amyloid‐beta plaques, tau tangles, and neuroinflammation. C‐X3‐C motif chemokine ligand 1 (CX3CL1, also known as fractalkine), a neuroimmune chemokine implicated in AD pathogenesis, shows inconsistent alterations in plasma/serum across studies.
Ling Wang, Yujie Liu, Fei Li, Xuelin Li, Lanlan Li, Jie Zhang, Yali Xu   +6 more
wiley   +1 more source

Day-Ahead Energy Price Forecasting with Machine Learning: Role of Endogenous Predictors

Accurate Day-Ahead Energy Price (DAEP) forecasting is essential for optimizing energy market operations. This study introduces a machine learning framework to predict the DAEP with a 24 h lead time, leveraging historical data and forecasts available at ...
Chibuike Chiedozie Ibebuchi
core   +1 more source

Five‐Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework.
Paulina Gonzalez‐Latapi, Caroline Gochanour, Seung Ho Choi, Hyunkeun Cho, Chelsea Caspell‐Garcia, Christopher Coffey, Michael Brumm, David‐Erick Lafontant, Yuge Xiao, Thomas Tropea, John Seibyl, Caroline Tanner, Charles S. Venuto, Karl Kieburtz, Lana M. Chahine, Kathleen L. Poston, Andrew Siderowf, Kenneth Marek, Tanya Simuni, The Parkinson's Progression Markers Initiative   +19 more
wiley   +1 more source

A Hybrid Framework for Offshore Wind Power Forecasting: Integrating CNN-BiGRU-XGBoost with Advanced Feature Engineering and Analysis

Energies
This paper proposes a hybrid forecasting model for offshore wind power, combining CNN, BiGRU, and XGBoost to address the challenges of fluctuating wind speeds and complex meteorological conditions.
Yongguo Li, Jiayi Pan, Jiangdong Wang
doaj   +1 more source

Forecasting Solar Radiation and Photovoltaic Power

Complementing empirical and physical models, statistical and machine learning (ML) methods are widely used in solar irradiance and power forecasting. To train time-series models, the availability of irradiance and/or photovoltaic (PV) power measurements is crucial, as is proper quality control of the data.
Lorenz, Elke, Nouri, Bijan, Cros, Sylvain, Nielsen, Kristian, Fritz, Rafael, Good, Garrett, Pierro, Marco, Sanchez Hernandez, Guadalupe, Lauret, Philippe, David, Mathieu, Amaro, Rodrigo, Fernandez Peruchena, Carlos, Cornaro, Cristina   +12 more
openaire   +5 more sources

Forecasting the Occurrence of Electricity Price Spikes: A Statistical-Economic Investigation Study

This research proposes an investigative experiment employing binary classification for short-term electricity price spike forecasting. Numerical definitions for price spikes are derived from economic and statistical thresholds.
Manuel Zamudio López, Hamidreza Zareipour, Mike Quashie   +2 more
core   +1 more source

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

Predictive control of wind turbines by considering wind speed forecasting techniques

, 2009
A wind turbine system is operated such that the points of wind rotor curve and electrical generator curve coincide. In order to obtain maximum power output of a wind turbine generator system, it is necessary to drive the wind turbine at an optimal rotor ...
Jovanovic, Milutin, Narayana, Mahinsasa, Putrus, Ghanim, Lung, P. S.   +3 more
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