Results 41 to 50 of about 7,175,735 (307)

A survey on wind power forecasting with machine learning approaches

Neural computing & applications (Print)
Wind power forecasting techniques have been well developed over the last half-century. There has been a large number of research literature as well as review analyses.
Yang Yang, Hao Lou, Jinran Wu, Shaotong Zhang, Shangce Gao   +4 more
semanticscholar   +1 more source

Solar Power Forecasting Using Deep Learning Techniques

IEEE Access, 2022
The recent rapid and sudden growth of solar photovoltaic (PV) technology presents a future challenge for the electricity sector agents responsible for the coordination and distribution of electricity given the direct dependence of this type of technology
Meftah Elsaraiti, A. Merabet
semanticscholar   +1 more source

Short-term photovoltaic power forecasting method based on irradiance correction and error forecasting

Energy Reports, 2021
Accurate photovoltaic (PV) power forecasting is of great significance for safe and stable operation for PV power plant and reasonable dispatching of power grids, and it is also a fundamental technology to ensure the high ratio of PV power generation ...
Yanhong Ma, Qingquan Lv, Ruixiao Zhang, Yanqi Zhang, Honglu Zhu, Wansi Yin   +5 more
doaj   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

The forecasting power of the microbiome

Trends in Microbiology, 2023
Microorganisms are informative biological integrators of past and present environmental abiotic and biotic conditions. At the same time, they are directly involved in ecosystem processes. Unfortunately, the complexity of microbial communities has so far resulted in most studies being descriptive. Here, we suggest that signals in the microbiome data can
Sara Correa-Garcia, Philippe Constant, Etienne Yergeau   +2 more
openaire   +3 more sources

Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting

Energies, 2022
The energy generated by a solar photovoltaic (PV) system depends on uncontrollable factors, including weather conditions and solar irradiation, which leads to uncertainty in the power output.
M. López Santos, X. García-Santiago, Fernando Echevarría Camarero, Gonzalo Blázquez Gil, Pablo Carrasco Ortega   +4 more
semanticscholar   +1 more source

A Lightweight Terrain‐Constraint Model for Wind Spatial Downscaling

Journal of Geophysical Research: Machine Learning and Computation
High‐resolution wind fields has always been the goal of refined meteorological forecasting. Using advanced deep learning algorithms for wind downscaling is an effective approach to achieve this goal. However, the lack of physical process understanding in
Anboyu Guo, Qiyang Liu, Jiuke Wang, Yuanyong Gao, Lixin Wei, Xiaojiang Song, Chi Zhang, Kai Liu, Shuping Ma, Jiu Jiang   +9 more
doaj   +1 more source

By dawn or dusk—how circadian timing rewrites bacterial infection outcomes

FEBS Letters, EarlyView.
The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo, Catherine S. Palmer, Jacqueline M. Kimmey   +2 more
wiley   +1 more source

Probabilistic photovoltaic power forecasting model based on deterministic forecasts [PDF]

E3S Web of Conferences, 2020
This paper presents an original probabilistic photovoltaic (PV) power forecasting model for the day-ahead hourly generation in a PV plant. The probabilistic forecasting model is based on 12 deterministic models developed with different techniques. An optimization process, ruled by a genetic algorithm, chooses the forecasts of the deterministic models ...
Fernandez-Jimenez, L. Alfredo, Terreros-Olarte, Sonia, Zorzano-Santamaria, Pedro J., Mendoza-Villena, Montserrat, Garcia-Garrido, Eduardo   +4 more
openaire   +4 more sources

TransPVP: A Transformer-Based Method for Ultra-Short-Term Photovoltaic Power Forecasting

Energies
The increasing adoption of renewable energy, particularly photovoltaic (PV) power, has highlighted the importance of accurate PV power forecasting. Despite advances driven by deep learning (DL), significant challenges remain, particularly in capturing ...
Jinfeng Wang, Wenshan Hu, Lingfeng Xuan, Feiwu He, Chaojie Zhong, Guowei Guo   +5 more
doaj   +1 more source