Paper Citation Record · LEDGER

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting

As of 18 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2412.02722.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.02722 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:08:24.515529Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:59:59.644474Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T11:59:59.721996Z

Reference resolution

32 of 32 outbound references displayed

verified exact4
verified fuzzy15
unresolved5
parse uncertain0
malformed identifier5
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 649eb846-380d-4660-956c-ee459bfec955 · outbound

This paper cites Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:28.096552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 51c35aa0-de59-4355-b07e-036aa6b441dc · outbound

This paper cites Relationships be- tween meteorological variables and monthly electricity demand.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Relationships be- tween meteorological variables and monthly electricity demand

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:28.063638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37a6511f-8aec-4faf-875b-6dcd4ddec335 · outbound

This paper cites Incorporat- ing air temperature into mid-term electricity load forecasting mod- els using time-series regressions and neural networks.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Incorporat- ing air temperature into mid-term electricity load forecasting mod- els using time-series regressions and neural networks

Reference 3

Resolution: malformed identifier; no resolver link, observed 2026-08-12T00:08:23.514014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2a5fe47-4da8-468a-9952-67b3932e634a · outbound

This paper cites Explainability and interpretability in electric load forecasting using machine learning techniques – a review.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Explainability and interpretability in electric load forecasting using machine learning techniques – a review

Reference 4

Resolution: malformed identifier; no resolver link, observed 2026-08-12T00:08:23.518845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed37eedf-cf30-45ea-b4d5-e3e1c7692152 · outbound

This paper cites Empirical mode decomposition based deep learning for electricity demand forecasting.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Empirical mode decomposition based deep learning for electricity demand forecasting

Reference 5

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T00:08:26.598911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e63ab041-5f33-42ca-bbc4-4d0da8776bd0 · outbound

This paper cites Monthly electricity demand forecasting based on a weighted evolving fuzzy neural network approach.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Monthly electricity demand forecasting based on a weighted evolving fuzzy neural network approach

Reference 6

Resolution: verified exact; doi, observed 2026-08-12T00:08:24.824311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 16530686-ae83-4f94-9c2b-200a131ada2d · outbound

This paper cites A multivariate ensemble learning method for medium-term energy forecasting.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting A multivariate ensemble learning method for medium-term energy forecasting

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.924802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e4d9ab1-e1f6-4f71-a4ff-4d7349fd762f · outbound

This paper cites Analyzing the impact of weather variables on monthly electricity demand.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Analyzing the impact of weather variables on monthly electricity demand

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.900762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 14a121cc-f7b9-442f-abd3-ad7e15af6740 · outbound

This paper cites Are shocks to electricity consumption transitory or permanent? sub-national evidence from turkey.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Are shocks to electricity consumption transitory or permanent? sub-national evidence from turkey

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.824471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2cebe3fe-49a6-4277-bbc3-852e68feee20 · outbound

This paper cites Pattern similarity-based machine learning methods for mid-term load forecasting: A comparative study.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Pattern similarity-based machine learning methods for mid-term load forecasting: A comparative study

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:23.756848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e982488-e258-46b7-9cec-983d488ff5f7 · outbound

This paper cites 3ETS+RD-LSTM: A new hybrid model for electrical energy consumption forecasting, in: Yang, H., Pa- supa, K., Leung, A.C.S., Kwok, J.T., Chan, J.H., King, I.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting 3ETS+RD-LSTM: A new hybrid model for electrical energy consumption forecasting, in: Yang, H., Pa- supa, K., Leung, A.C.S., Kwok, J.T., Chan, J.H., King, I

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.808472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dc7b16a8-848a-49b6-969d-8aa3b8a7ef04 · outbound

This paper cites A hybrid residual dilated LSTM and exponential smoothing model for midterm electric load forecast- ing.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting A hybrid residual dilated LSTM and exponential smoothing model for midterm electric load forecast- ing

Reference 12

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T00:08:26.301072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 917456c6-663c-4ecc-bea9-7796e0deb55c · outbound

This paper cites Medium term system load forecasting with a dynamic artificial neural network model.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Medium term system load forecasting with a dynamic artificial neural network model

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.693065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c29f9bb2-eff6-4f5b-8ec6-9fdd5a1ae48d · outbound

This paper cites an unresolved cited work.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:23.940333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ae7a4c1-1713-43c8-ba77-4d57aa1cc18f · outbound

This paper cites Forecasting: Principles and Practice.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Forecasting: Principles and Practice

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.581155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fd3735ba-6d90-4e20-beb9-e9353936bfb7 · outbound

This paper cites Prob- abilistic forecasting method for mid-term hourly load time series based on an improved temporal fusion transformer model.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Prob- abilistic forecasting method for mid-term hourly load time series based on an improved temporal fusion transformer model

Reference 16

Resolution: malformed identifier; no resolver link, observed 2026-08-12T00:08:24.027982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd2e9996-26ea-4c16-a271-07b2243ddcae · outbound

This paper cites Mid-long term load forecasting model based on support vector machine optimized by improved sparrow search algorithm.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Mid-long term load forecasting model based on support vector machine optimized by improved sparrow search algorithm

Reference 17

Resolution: verified exact; doi, observed 2026-08-12T00:08:24.712416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d471df3-d3cf-4c31-8ff1-3e9167cee5a7 · outbound

This paper cites Combination of manifold learning and deep learning algorithms for mid-term electrical load forecasting.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Combination of manifold learning and deep learning algorithms for mid-term electrical load forecasting

Reference 18

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T00:08:25.297605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01aa755a-7e44-4434-864b-25a1daeda339 · outbound

This paper cites Enhancing the locality and breaking the memory bottleneck of Trans- former on time series forecasting, in: Advances in Neural Information Processing Systems 32, pp.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Enhancing the locality and breaking the memory bottleneck of Trans- former on time series forecasting, in: Advances in Neural Information Processing Systems 32, pp

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.564683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 943c5043-dadd-44e6-9740-103e658f676b · outbound

This paper cites N-BEATS: Neural basis expansion analysis for interpretable time series forecasting, in: ICLR.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting N-BEATS: Neural basis expansion analysis for interpretable time series forecasting, in: ICLR

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.452498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 528badf6-3760-4b13-baf3-cfa21e646d27 · outbound

This paper cites N-beats neural network for mid-term electricity load forecasting.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting N-beats neural network for mid-term electricity load forecasting

Reference 21

Resolution: malformed identifier; no resolver link, observed 2026-08-12T00:08:24.263377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66b5a0ee-a9b3-4576-8fd2-2ed53109a7c1 · outbound

This paper cites Analysis and forecasting of monthly electricity de- mand time series using pattern-based statistical methods.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Analysis and forecasting of monthly electricity de- mand time series using pattern-based statistical methods

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.418251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 054bfdc9-4421-42cb-af25-d1e3bb857634 · outbound

This paper cites an unresolved cited work.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Unresolved cited work

Reference 23

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T00:08:27.384583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 480cacf5-bc3c-4b2d-aeaf-c1cc0e43a7f6 · outbound

This paper cites an unresolved cited work.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-12T00:08:27.278046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 491408a4-cb8c-4266-8f43-f1b8d2956f39 · outbound

This paper cites Pattern-based forecasting monthly electricity demand using multilayer perceptron, in: Artificial Intelligence and Soft Computing, Springer International Publishing, Cham.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Pattern-based forecasting monthly electricity demand using multilayer perceptron, in: Artificial Intelligence and Soft Computing, Springer International Publishing, Cham

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.217941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1bcf1506-bf81-46b5-ae33-096e8dbeea40 · outbound

This paper cites Pattern-based long short-term memory for mid-term electrical load forecasting, in: 2020 International Joint Conference on Neural Networks (IJCNN), pp.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Pattern-based long short-term memory for mid-term electrical load forecasting, in: 2020 International Joint Conference on Neural Networks (IJCNN), pp

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:27.050852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58576582-225a-439e-9a4c-07c2b6d58cfd · outbound

This paper cites A novel two-stage framework for mid-term electric load forecasting.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting A novel two-stage framework for mid-term electric load forecasting

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:24.408190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef706d39-f0f3-44ab-8451-ed74e2e65315 · outbound

This paper cites Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:24.446383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1684db89-b443-4f4e-83cf-acbfc3ca8ec3 · outbound

This paper cites Energy models for demand forecast- ing—a review.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Energy models for demand forecast- ing—a review

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:26.973669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7c8c962f-96ca-4f57-a976-be0f88758715 · outbound

This paper cites Multi- step short-term power consumption forecasting with a hybrid deep learn- ing strategy.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Multi- step short-term power consumption forecasting with a hybrid deep learn- ing strategy

Reference 30

Resolution: verified exact; doi, observed 2026-08-12T00:08:24.592267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 138f8f01-c926-44e7-b77a-5bdeed5547b4 · outbound

This paper cites Attention is all you need, in: Proceedings of 31st Conference on Neural Information Processing Systems (NIPS 2017), pp.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Attention is all you need, in: Proceedings of 31st Conference on Neural Information Processing Systems (NIPS 2017), pp

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:08:26.956781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b370100e-b4d1-44a9-9302-f5a3f2d9b35e · outbound

This paper cites an unresolved cited work.

Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting Unresolved cited work

Reference 1240

Resolution: verified exact; doi, observed 2026-08-12T00:08:24.691214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 60a8f2b5-9491-4c52-9deb-285b7de8e5d4 · inbound

Explainability-Driven Feature Engineering for Mid-Term Electricity Load Forecasting in ERCOT's SCENT Region cites this paper.

Explainability-Driven Feature Engineering for Mid-Term Electricity Load Forecasting in ERCOT's SCENT Region Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:59:59.729200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.