On the public citation graph
Dynamics-Aware Wind Power Forecasting Framework Based on Latent Channel Decomposition with Future Meteorological Forecasts
0 signed · 12 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.egyr.2024.06.006openalex-snapshot
A review of short-term wind power generation forecasting methods in recent technological trends
inferredcites →https://doi.org/10.1016/j.energy.2020.118371openalex-snapshot
Short-term wind power forecasting approach based on Seq2Seq model using NWP data
inferredcites →https://doi.org/10.1016/j.future.2018.09.054openalex-snapshot
LSTM-EFG for wind power forecasting based on sequential correlation features
inferredcites →https://doi.org/10.1016/j.renene.2012.06.036openalex-snapshot
Predicting the energy output of wind farms based on weather data: Important variables and their correlation
inferredcites →https://doi.org/10.1016/j.renene.2014.09.058openalex-snapshot
Short-term wind power forecasting using adaptive neuro-fuzzy inference system combined with evolutionary particle swarm optimization, wavelet transform and mutual information
inferredcites →https://doi.org/10.1016/j.rser.2013.05.028openalex-snapshot
A review of output power smoothing methods for wind energy conversion systems
inferredcites →https://doi.org/10.1038/s41586-023-06185-3openalex-snapshot
Accurate medium-range global weather forecasting with 3D neural networks
inferredcites →https://doi.org/10.1049/iet-rpg.2019.0614openalex-snapshot
Short‐term wind power forecasting based on two‐stage attention mechanism
inferredcites →https://doi.org/10.1049/rpg2.12085openalex-snapshot
Ultra‐short‐term multi‐step wind power forecasting based on CNN‐LSTM
inferredcites →https://doi.org/10.1080/00401706.1970.10488634openalex-snapshot
Ridge Regression: Biased Estimation for Nonorthogonal Problems
inferredcites →https://doi.org/10.1126/science.adi2336openalex-snapshot
Learning skillful medium-range global weather forecasting
inferredcites →https://doi.org/10.1162/neco.1989.1.2.270openalex-snapshot
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.