Results 41 to 50 of about 215,326 (298)

A refined parametric model for short term load forecasting [PDF]

, 2014
We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012).
Charlton, Nathaniel, Singleton, Colin
core   +1 more source

Power load forecasting [PDF]

, 2006
For the electric power factory, the power load forecasting problem, including load forecasting and consumption predicting, is crucial to work planning. According to the predicting time, it can be divided into long-term forecasting, mid-term forecasting ...
Hao, Z., Lu, L., Shao, D.
core  

ANN and ANFIS for Short Term Load Forecasting [PDF]

Engineering, Technology & Applied Science Research, 2018
Load forecasting has become one of the major areas of research in electrical engineering. Short term load forecasting (STLF) is essential for power system planning and economic load dispatch. A variety of mathematical methods has been developed for load forecasting. This paper discusses the influencing factors of STLF and an artificial intelligence (AI)
J. Chakravorty, S. Shah, H. N. Nagraja
openaire   +1 more source

Parent‐to‐Child Information Disclosure in Pediatric Oncology

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor, Flora Hoodin, Michelle Byrd, Kristin A. Kullgren, Leah LaLonde, Lauren Benkoske, Patrick Smith, Dawn Carson, Karen MacDonald, Susumu Inoue, Brenda Kitchen, Kate Gowans, Gregory A. Yanik   +12 more
wiley   +1 more source

Characterizing Parental Concerns About Lasting Impacts of Treatment in Children With B‐Acute Lymphoblastic Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background B‐acute lymphoblastic leukemia (B‐ALL) is the most common pediatric cancer, and while most children in high‐resource settings are cured, therapy carries risks for long‐term toxicities. Understanding parents’ concerns about these late effects is essential to guide anticipatory support and inform evolving therapeutic approaches ...
Kellee N. Parker, Sarah W. Alexander, Lisa M. Jacola, Kimberly A. Buff, Kyobin Hwang, Elham Hashemi, Gregory Stoddard, Lindsay A. Jibb   +7 more
wiley   +1 more source

A Hybrid Stacking Model for Enhanced Short-Term Load Forecasting

Electronics
The high penetration of distributed energy resources poses significant challenges to the dispatch and operation of power systems. Improving the accuracy of short-term load forecasting (STLF) can optimize grid management, thus leading to increased ...
Fusen Guo, Huadong Mo, Jianzhang Wu, Lei Pan, Hailing Zhou, Zhibo Zhang, Lin Li, Fengling Huang   +7 more
semanticscholar   +1 more source

Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation

, 2017
Accurate load forecasting is an important issue for the reliable and efficient operation of a power system. This study presents a hybrid algorithm that combines similar days (SD) selection, empirical mode decomposition (EMD), and long short-term memory ...
Huiting Zheng, Jiabin Yuan, Long Chen
semanticscholar   +1 more source

Short-Term Load Forecasting for Industrial Customers Based on TCN-LightGBM

IEEE Transactions on Power Systems, 2020
Accurate and rapid load forecasting for industrial customers has been playing a crucial role in modern power systems. Due to the variability of industrial customers’ activities, individual industrial loads are usually too volatile to forecast accurately.
Yuanyuan Wang, Jun Chen, Xiaoqiao Chen, Xiangjun Zeng, Yang Kong, Shanfeng Sun, Yongsheng Guo, Y. Liu   +7 more
semanticscholar   +1 more source

Short-Term Load Forecasting Based on Improved TCN and DenseNet

IEEE Access, 2022
With the grid-connected application of renewable energy sources such as wind and photovoltaic power, the nonlinearity and fluctuation of load data makes load forecasting more difficult than ever before.
Ming Liu, Hao Qin, Ran Cao, Suhui Deng
semanticscholar   +1 more source

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül, Neriman Sıla Koç, Berrak Itır Aylı   +2 more
wiley   +1 more source