Results 101 to 110 of about 5,303,939 (309)
Prediction in Photovoltaic Power by Neural Networks
Energies, 2017 The ability to forecast the power produced by renewable energy plants in the short and middle term is a key issue to allow a high-level penetration of the distributed generation into the grid infrastructure. Forecasting energy production is mandatory for
Antonello Rosato +3 more
doaj +1 more source
, 2011 Over the past several decades, many techniques and approaches have been proposed and implemented for load and price forecasting. The objective of all of these methods was load and price forecasting with minimal error.
Al-Shakhs, Mohammed H.
core
, 2020 As photovoltaic (PV) power plants are an essential component of modern smart grids, the PV generation forecasting of such plants has recently been gaining interest.
Young-Min Wi +2 more
core +1 more source
Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
wiley +1 more source
Frontiers in Energy ResearchAiming at wind-solar intermittency and low coupling between renewable energy forecasting and shared energy storage (SES) planning in wind-solar-thermal distributed energy clusters, this paper proposes a two-stage framework combining high-precision power ...
Zhongyuan Yan +4 more
doaj +1 more source
Short-Term Power Forecasting Model for Photovoltaic Plants Based on Historical Similarity
Energies, 2013 This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV) plant. The model is called HIstorical SImilar MIning (HISIMI) model; its final structure is optimized by using a genetic algorithm, based on ...
M. Sonia Terreros-Olarte +4 more
doaj +1 more source
Neural Network Models for Inflation Forecasting: An Appraisal [PDF]
We assess the power of artificial neural network models as forecasting tools for monthly inflation rates for 28 OECD countries. For short out-of-sample forecasting horizons, we find that, on average, for 45% of the countries the ANN models were a ...
Adnan Haider, Ali Choudhary
core
Molecular Oncology, EarlyView.Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Journal of Marine Science and EngineeringMultistep-ahead forecasting of chlorophyll concentration is of great significance in red tide early warning systems. Existing methods often neglect the potential adverse interactions between non-predictive variables and chlorophyll while failing to fully
Lei Wang +10 more
doaj +1 more source
Molecular Oncology, EarlyView.The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source