Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-25T20:08:37.164201Z
Paper Citation Record · LEDGER
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning
As of 4 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:1906.08374.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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
Reference resolution
15 of 15 outbound references displayed
- verified exact0
- verified fuzzy15
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 025e4954-43de-4af0-b992-f058cf3b47d4 · outbound
This paper cites Smart meters: Distribution network operators privacy plans.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Smart meters: Distribution network operators privacy plans
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.639128Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf00daf2-5ed4-4640-9d86-a16c1ebe8b82 · outbound
This paper cites Valuation of measurement data for low voltage network expansion planning.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Valuation of measurement data for low voltage network expansion planning
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.646758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0e8037e0-dc66-40a7-aff5-8b2bd8b07dd4 · outbound
This paper cites Opti- mal charging of electric vehicles taking distribution network constraints into account.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Opti- mal charging of electric vehicles taking distribution network constraints into account
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.665564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 02f8c30c-bda3-4023-b884-0e2dc59f51cc · outbound
This paper cites Management of power quality issues in low voltage networks using electric vehicles: Experi- mental validation.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Management of power quality issues in low voltage networks using electric vehicles: Experi- mental validation
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.654708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 60012a78-8d4a-4991-aa0d-5eeb85dfe53d · outbound
This paper cites Techno-economic assessment of voltage control strategies in low volt- age grids.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Techno-economic assessment of voltage control strategies in low volt- age grids
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.675623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 164c58d2-ff46-4e40-adf2-bd6fe6d00b03 · outbound
This paper cites Distributed energy resources integration challenges in low-voltage networks: V oltage control limitations and risk of cascading.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Distributed energy resources integration challenges in low-voltage networks: V oltage control limitations and risk of cascading
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.627529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c3b3e1cf-b4e4-4657-90a4-847eee511ab9 · outbound
This paper cites State forecasting and operational planning for distribution network energy management systems.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning State forecasting and operational planning for distribution network energy management systems
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.650812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 26d35b30-6552-4f74-a2e8-3c6eb8e01236 · outbound
This paper cites High-resolution stochastic integrated thermal-electrical domestic demand model.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning High-resolution stochastic integrated thermal-electrical domestic demand model
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.661967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 013064ca-f34f-48e9-b99b-3bd4cbd4dcf3 · outbound
This paper cites Electric vehicles’ impact on british distribution networks.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Electric vehicles’ impact on british distribution networks
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.631171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation db2fadcf-7c07-412d-8857-f2c2fe7233fb · outbound
This paper cites Structure learning in power distribution networks.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Structure learning in power distribution networks
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.650424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 85aadb30-c319-4399-87c3-fb2e809eb16b · outbound
This paper cites Exact topology and parameter estimation in distribution grids with minimal observability.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Exact topology and parameter estimation in distribution grids with minimal observability
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.658160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b1f6b3cc-7d66-48bb-a46d-e537e8bc2f8f · outbound
This paper cites V oltage estimation in active distribution grids using neural networks.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning V oltage estimation in active distribution grids using neural networks
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.668972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8d7d7cd3-8eb7-4b33-8d0d-71472872594e · outbound
This paper cites Tensorflow™.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Tensorflow™
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.678918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 918f3735-8330-4277-a4ec-98f1a1abd02d · outbound
This paper cites Development of low voltage network templatespart i: Substation clustering and classification.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Development of low voltage network templatespart i: Substation clustering and classification
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.672193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ac9a4c4a-d407-423e-a9fc-d5d82ada67d7 · outbound
This paper cites Analysis and clustering of residential customers energy behavioral demand using smart meter data.
Predicting the Voltage Distribution for Low Voltage Networks using Deep Learning Analysis and clustering of residential customers energy behavioral demand using smart meter data
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-25T20:17:08.654346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
No inbound Pith citation observations are available.