Results 71 to 80 of about 108,466 (288)
Local Short Term Electricity Load Forecasting: Automatic Approaches
Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new challenges as well as
Bianchi, Filippo Maria +2 more
core +1 more source
A data mining method for short‐term load forecasting in power systems
AbstractThis paper proposes a method for daily maximum load forecasting in power systems. It is based on the integration of the regression tree and the artificial neural network. In this paper, the regression tree is used to extract knowledge or rules as a data‐mining method. That is useful for the information processing of the complicated data.
Hiroyuki Mori, Noriyuki Kosemura
openaire +2 more sources
Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
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 +8 more
wiley +1 more source
Short-term load estimation based on improved DBN-LSTM
Aiming at the rapid change and low forecasting accuracy of short-term power load forecasting, a forecasting model based on the improved deep belief network and long short-term memory network is proposed.
Nan Dong +3 more
doaj +1 more source
Studi Peramalan Beban Rata – Rata Jangka Pendek Menggunakan Metoda Autoregressive Integrated Moving Average (Arima [PDF]
Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State Electricity Company (PLN) as a provider of energy must be able to predict daily electricity needs. Short-term forecasting is the prediction of electricity
Jurnal, R. T. (Redaksi)
core
A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento +3 more
wiley +1 more source
Short-Term Load Forecasting Using a Novel Deep Learning Framework
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 +4 more
doaj +1 more source
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 +8 more
wiley +1 more source
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe +7 more
wiley +1 more source
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source

