Paper Citation Record · LEDGER

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting

As of 19 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2411.16118.

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

pith.paper-citation-record.v1
2411.16118 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:34:39.646181Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact2
verified fuzzy7
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9a06035c-76b9-4143-993c-e7ea7ed7ef5e · outbound

This paper cites Artificial Intelligence for Load Forecasting,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Artificial Intelligence for Load Forecasting,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.574411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b22a045-388b-4adc-b338-52ff1297dea2 · outbound

This paper cites Neural Network-based Power Flow Model,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Neural Network-based Power Flow Model,

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-12T13:34:40.133643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7471f4a8-b7a5-44b5-8388-b55ce6ed3abd · outbound

This paper cites Wholesale Electricity Price Forecasting using Integrated Long-term Recurrent Convolutional Network Model.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Wholesale Electricity Price Forecasting using Integrated Long-term Recurrent Convolutional Network Model

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.334770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e01e406c-2c23-4034-90ea-b1060d7d5c1c · outbound

This paper cites Microgrid Optimal Energy Scheduling Considering Neural Network based Battery Degradation.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Microgrid Optimal Energy Scheduling Considering Neural Network based Battery Degradation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.322444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f1708b9-de2f-4d49-a7ea-7d5371ce04f1 · outbound

This paper cites An Alternative Method for Solving Security-Constraint Unit Commitment with Neural Network Based Battery Degradation Model.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting An Alternative Method for Solving Security-Constraint Unit Commitment with Neural Network Based Battery Degradation Model

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.309747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e3df5b1-f5a1-411e-bc9c-05325ce63d67 · outbound

This paper cites Power load forecasting in the spring festival based on feedforward neural network model,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Power load forecasting in the spring festival based on feedforward neural network model,

Reference 6

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T13:34:40.047013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1c7d5b30-8ac5-4ad3-b913-3150baae8c7d · outbound

This paper cites A Comparative Analysis of Deep Learning Models for Short-Term Load Forecasting,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting A Comparative Analysis of Deep Learning Models for Short-Term Load Forecasting,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.603012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 485f9697-7e60-4c12-b448-4da784e64ae2 · outbound

This paper cites Comparison of Deep Learning-Based Methods for Electrical Load Forecasting.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Comparison of Deep Learning-Based Methods for Electrical Load Forecasting

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.294476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a57eb17b-ab7d-400c-9026-fccf8ccc637c · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.612003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6927c311-76e9-4c97-a8da-8059bdfceb15 · outbound

This paper cites A Comparative Study of LSTM/GRU Models for Energy Long-Term Forecasting in IoT Networks,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting A Comparative Study of LSTM/GRU Models for Energy Long-Term Forecasting in IoT Networks,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.616730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f18b53be-4016-40c6-9ab7-3896757628c9 · outbound

This paper cites A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-12T13:34:39.797104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 40116df4-ef58-4093-a609-8566300f714a · outbound

This paper cites Short-Term Load Forecasting Using Recurrent Neural Networks With Input Attention Mechanism and Hidden Connection Mechanism,.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Short-Term Load Forecasting Using Recurrent Neural Networks With Input Attention Mechanism and Hidden Connection Mechanism,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:39.628732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11c89959-f726-4977-afa6-3f99cf703759 · outbound

This paper cites Household Energy Use in Texas.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Household Energy Use in Texas

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.278955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98984bda-8822-432b-bf1e-107f3b2a74b1 · outbound

This paper cites Building Energy Consumption Breakdown for Owners and Management.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Building Energy Consumption Breakdown for Owners and Management

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.266589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation da68ff49-b655-4817-a6e5-abeb2e5286bd · outbound

This paper cites Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:34:40.253935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35e1dd20-0ec4-42b6-8b18-455bcc64f9c5 · outbound

This paper cites an unresolved cited work.

Comparative Analysis of Machine Learning Models for Short-Term Distribution System Load Forecasting Unresolved cited work

Reference 2022

Resolution: unresolved; raw_fallback, observed 2026-08-12T13:34:40.241024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.