Results 121 to 130 of about 8,068,929 (298)

Short-Term Load Forecasting Using a Novel Deep Learning Framework

, 2018
Short-term load forecasting is the basis of power system operation and analysis. In recent years, the use of a deep belief network (DBN) for short-term load forecasting has become increasingly popular. In this study, a novel deep-learning framework based
Xiaoyu Zhang, Yabing Zha, Tao Zhang, Yajie Liu, Rui Wang   +4 more
core   +1 more source

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi, Katharine Lee, Kerry C. Nix, Miguel Menchaca, Xiwei Shé, Lorelei Santa Maria, Wei Wu, Zihuai He, Fiona M. Baumer   +8 more
wiley   +1 more source

Research on Load Forecasting Based on Bayesian Optimized CNN-LSTM Neural Network

Energies
With the high penetration of renewable energy integration and massive user participation in electricity markets, traditional short-term load forecasting methods exhibit limitations in both adaptability and prediction accuracy.
Pengyang Duan, Huannian Jiao, Jianying Sun, Aiming Han, Zheng Dai, Liang Cheng, Xiaotao Chen   +6 more
doaj   +1 more source

A hybrid model of modal decomposition and gated recurrent units for short-term load forecasting. [PDF]

PeerJ Comput Sci, 2023
Wang CH, Li WQ.
europepmc   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Multi-horizon short-term load forecasting using hybrid of LSTM and modified split convolution. [PDF]

PeerJ Comput Sci, 2023
Ullah I, Muhammad Hasanat S, Aurangzeb K, Alhussein M, Rizwan M, Anwar MS.   +5 more
europepmc   +1 more source

Artificial neural networks in short term load forecasting / Zulkifle Ahmad [PDF]

, 2003
The artificial neuron network (ANN) technique for short-term load forecasting (STLF) has been proposed by several authors in order to evaluate ANN as a viable technique for STLF.
Ahmad, Zulkifle
core  

Acute Kidney Injury After Mechanical Thrombectomy for Stroke in Patients With Pre‐Existing Renal Impairment

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Acute kidney injury (AKI) is a common but often underrecognized complication in ischemic stroke patients undergoing mechanical thrombectomy, particularly among those with pre‐existing renal impairment. This study evaluated the incidence, risk factors, and clinical impact of AKI in this high‐risk population.
Michał Borończyk, Marcel Pilarek, Emilia Jaworska, Natalia Kardas, Oliwia Barnaś, Julia Woźniak, Iga Machała, Julia Węgrzynek‐Gallina, Joanna Siuda, Anna Hawrot‐Kawecka, Anetta Lasek‐Bal   +10 more
wiley   +1 more source

MODE – REGRESSION BASED MODEL FOR SHORT TERM LOAD FORECASTING

Yanbu Journal of Engineering and Science, 2021
Ahmad Al-Subhi, Chokri Belhadj Ahmad
doaj   +1 more source

Short-term load forecasting system based on sliding fuzzy granulation and equilibrium optimizer. [PDF]

Appl Intell (Dordr), 2023
Li S, Wang J, Zhang H, Liang Y.
europepmc   +1 more source