Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:29:59.714619Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2506.10536.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:29:59.714619Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
36 of 36 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Electrical interconnectors: Market opportunities, regulatory issues, technology con- siderations and implications for the gb energy sector
Reference 1
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows A hybrid model for multi-day-ahead electricity price forecasting considering price spikes
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Beyond the merit order effect: Impact of the rapid expansion of renewable energy on electricity market price
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Dynamic pricing strat- egy for electric vehicle charging stations to distribute the congestion and maximize the revenue
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows The effect of flow-based market coupling on cross- border exchange volumes and price convergence in central western euro- pean electricity markets
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs
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Source-reported events for the cited work
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Forecasting day-ahead electricity prices: A review of state-of-the-art al- gorithms, best practices and an open-access benchmark
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Observation ba2ba666-3d60-431d-b374-a723bb0fcf1c · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows An optimized deep learning approach for forecasting day-ahead electricity prices
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Day-ahead elec- tricity price forecasting employing a novel hybrid frame of deep learning methods: A case study in nsw, australia
Reference 12
Source-reported events for the cited work
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Observation b5d890e1-e3f3-4609-946b-bb861941dc5c · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows A hybrid gru-lightgbm model for day-ahead electricity price forecasting
Reference 13
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Observation 62544092-9ffa-4014-b049-17dd99d3879b · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Muyeen, Mohammad Abdul Mannan, and Innocent Kamwa
Reference 14
Source-reported events for the cited work
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Observation 09e8a994-c5d1-4162-a3a9-171c5f314690 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows An ensemble approach for enhanced day- ahead price forecasting in electricity markets
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Source-reported events for the cited work
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Observation 037c4aae-03ea-4bd6-9daf-4388da9f8fef · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Day- ahead electricity price forecasting using artificial intelligence-based algo- rithms
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Source-reported events for the cited work
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Observation 6a5ae2e9-ae1c-47cc-a354-3d7bdff40753 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Elec- tricity price forecasting on the day-ahead market using machine learning
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Day-ahead electricity price forecasting strategy based on machine learning and optimization algorithm
Reference 18
Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Electricity price forecasting on day ahead market via a multivariate cnn-lstm model
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Forecasting day-ahead electricity price with artificial neural networks: a comparison of architectures
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Applying machine learning to electricity price forecasting in simulated energy market scenarios
Reference 21
Source-reported events for the cited work
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Reference 22
Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Chapter 7 - foundations of neural networks
Reference 23
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Observation b4a77f72-877a-4279-9693-c5b5ca20f37c · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Recurrent neural networks for time series forecasting: Current status and future directions
Reference 24
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Recurrent Neural Networks (RNNs): Architectures, Training Tricks, and Introduction to Influential Research , pages 117–138
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Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Long short-term memory neural net- works
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Source-reported events for the cited work
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Observation 9a8f7ad3-323d-4260-9b9c-15b9e721d378 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Georgilakis
Reference 29
Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows The benefits of integrat- ing european electricity markets
Reference 30
Source-reported events for the cited work
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Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Short term wholesale electricity market designs: A review of identified challenges and promising solutions
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Source-reported events for the cited work
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Observation 4e0411be-b4cf-4dc3-a2d7-e3d764c662f1 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Renewable energy statistics, 2023
Reference 33
Source-reported events for the cited work
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Observation 496ca98f-0c5a-46b6-9a74-4dd080cdd933 · outbound
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Reference 34
Source-reported events for the cited work
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Observation 7ee8a664-6464-45db-b0b7-2a996e122947 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Market’s coupling - price coupling of regions (pcr), 2024
Reference 35
Source-reported events for the cited work
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Observation 9bf1781e-b681-4db6-9954-03ecf7f1c071 · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Balancing market, 2024
Reference 36
Source-reported events for the cited work
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Observation 16d3b440-b8df-4d82-9d7e-fde7f6ce7f1e · outbound
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows Unsupervised domain adaptation methods for photovoltaic power forecasting
Reference 37
Source-reported events for the cited work
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No inbound Pith citation observations are available.