Results 91 to 100 of about 8,068,929 (298)

Modelling and forecasting short-term electricity load: a two step methodology [PDF]

The goal of this paper is to develop a forecasting model of the hourly electricity load demand in the area covered by an utility company located in the southeast of Brazil.
Lacir J. Soares, Marcelo Cunha Medeiros
core  

Somatostatin receptor 4 (SSTR4) is a tumor suppressor in cutaneous and head & neck squamous cell carcinomas

Molecular Oncology, EarlyView.
This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi, Tuan Khang Huynh, Adway Kadam, Zahra Kardan, Yue Yan, Amina Jamal Laham, Sampath Kumar Loganathan   +6 more
wiley   +1 more source

Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer

Frontiers in Energy Research
Given the complexity and dynamic nature of short-term load sequence data, coupled with prevalent errors in traditional forecasting methods, this study introduces a novel approach for short-term load forecasting.
Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang   +5 more
doaj   +1 more source

p190A/ARHGAP35 and p190B/ARHGAP5 proteins in endometrial cancer: a novel cancer‐relevant paralog interplay

Molecular Oncology, EarlyView.
This study identifies ARHGAP5, in addition to the frequently mutated ARHGAP35, as significantly mutated in endometrial cancer. Mutations in both genes co‐occur and are associated with their correlated downregulation. Functional CRISPR studies show that both paralogs regulate similar pathways, including actin cytoskeleton organization.
Mathilde Pinault, Capucine Heraud, Mélissa Correia de Oliveira, Véronique Neaud, Valérie Valesco, Valérie Prouzet‐Mauleon, Béatrice Turcq, Jean‐William Dupuy, Anne‐Aurélie Raymond, Sabrina Croce, Frédéric Saltel, Valérie Lagrée, Violaine Moreau   +12 more
wiley   +1 more source

Short-term power load forecasting in distribution networks considering human comfort level

Frontiers in Energy Research
The growth of power demand and the increase of new energy penetration have resulted in a heightened necessity for the precision of short-term power load forecasting in distribution networks. The majority of current research on short-term load forecasting
Yong Li, Hua Wang, Xianbin Huang, Juanyang Hao, Wenting Lei, Quanlin Wang   +5 more
doaj   +1 more source

Comparison of advanced learning algorithms for short-term load forecasting

, 2000
Neural Networks are currently finding practical applications, ranging from 'soft' regulatory control in consumer products to accurate modelling of non-linear systems.
Kodogiannis, V.
core  

Short-term load forecasting using hybrid neural network

, 2022
One of the important factors in generating low cost electrical power is the accurate forecasting of electricity consumption called load forecasting. The major objective of the load forecasting is to trim down the error between actual load and forecasted ...
M Altaf (13304544), A Ahmad (13304592), M Nadeem (6699932)   +2 more
core  

Unique circulating miRNAome signatures captured with distinct molecular states in Lynch syndrome and sporadic colorectal cancer

Molecular Oncology, EarlyView.
Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso, Md Shohel Ul Islam, Rosa M Xicola, Raj Ramesar, Xavier Llor, Sinclair Steele   +5 more
wiley   +1 more source

Stacking for Probabilistic Short-Term Load Forecasting

In this study, we delve into the realm of meta-learning to combine point base forecasts for probabilistic short-term electricity demand forecasting. Our approach encompasses the utilization of quantile linear regression, quantile regression forest, and post-processing techniques involving residual simulation to generate quantile forecasts. Furthermore,
openaire   +3 more sources

Short-term load forecasting model of SCNs.

Accurate short-term load forecasting is of great significance in improving the dispatching efficiency of power grids, ensuring the safe and reliable operation of power grids, and guiding power systems to formulate reasonable production plans and reduce ...
Changfeng Luan (18182330), Haibo Li (629817), Wei Sun (93580), Xinfu Pang (16713651), Wei Liu (20030)   +4 more
core   +1 more source