Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:04:05.817410Z
Paper Citation Record · LEDGER
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data
As of 22 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.08882.
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 2026-08-22T06:32:14.747728+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
16 of 16 outbound references displayed
- verified exact0
- verified fuzzy14
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8ce5b2e5-3a4b-4720-9415-e196d38d654c · outbound
This paper cites A solution for water management and leakage detection problems using iots based approach,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data A solution for water management and leakage detection problems using iots based approach,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.079327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a5e33e1d-eca9-4eef-8f63-728473f59f09 · outbound
This paper cites Precise water leak detection using machine learning and real-time sensor data,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Precise water leak detection using machine learning and real-time sensor data,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.065086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c0a8d794-0930-4d8e-8a86-0b44fecee31a · outbound
This paper cites Leakage detection via edge processing in lorawan-based smart water distribution networks,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Leakage detection via edge processing in lorawan-based smart water distribution networks,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.050335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 31cb60a5-b746-4861-b098-0720da3c3386 · outbound
This paper cites Real-time leakage zone detection in water distribution networks: A machine learning-based stream processing algorithm,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Real-time leakage zone detection in water distribution networks: A machine learning-based stream processing algorithm,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.035345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a3fecd84-ad33-4a7d-a307-ed7f625dabbf · outbound
This paper cites Advanced strategies for monitoring water consumption patterns in households based on iot and machine learning,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Advanced strategies for monitoring water consumption patterns in households based on iot and machine learning,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.021719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cd2026a1-d4a0-4429-ae6c-f04caec62aad · outbound
This paper cites A survey on data imputation techniques: Water distribution system as a use case,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data A survey on data imputation techniques: Water distribution system as a use case,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:06.006247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a99a6972-e2a0-4497-8932-d3650eeb5019 · outbound
This paper cites Data imputation for multivariate time series sensor data with large gaps of missing data,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Data imputation for multivariate time series sensor data with large gaps of missing data,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.987858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 308bade8-28d9-467d-b509-8baa367103a5 · outbound
This paper cites K-nearest neighbor (k-nn) based missing data imputation,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data K-nearest neighbor (k-nn) based missing data imputation,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.971941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 783a06f2-460e-4dba-b25e-6966bd22c74b · outbound
This paper cites Missforest—non-parametric missing value imputation for mixed-type data,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Missforest—non-parametric missing value imputation for mixed-type data,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.956170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation df4b7c97-d896-4d49-93bd-739aa8c9f5d0 · outbound
This paper cites Saits: Self-attention- based imputation for time series,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Saits: Self-attention- based imputation for time series,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.941001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 647cbad3-f8c0-4f87-bed2-f1e432233e76 · outbound
This paper cites A transfer learning-based lstm strategy for imputing large-scale consecutive missing data and its application in a water quality prediction system,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data A transfer learning-based lstm strategy for imputing large-scale consecutive missing data and its application in a water quality prediction system,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.924765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0b7a2e62-0c1c-4d62-96a5-69fcfae93755 · outbound
This paper cites Timesnet: Temporal 2d-variation modeling for general time series analysis,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Timesnet: Temporal 2d-variation modeling for general time series analysis,
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:04:05.797209Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aac70750-053e-49a5-b48a-f9c7207c4cb6 · outbound
This paper cites Handling missing data in near real-time environmental monitoring: A system and a review of selected methods,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Handling missing data in near real-time environmental monitoring: A system and a review of selected methods,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.898845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4543b06e-d36c-4d7b-8292-be59b3706ffb · outbound
This paper cites Recurrent neural networks for multivariate time series with missing values,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Recurrent neural networks for multivariate time series with missing values,
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:04:05.807095Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76205663-3e4b-44da-ac7f-23faae7d0d86 · outbound
This paper cites A smart water metering deployment based on the fog computing paradigm,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data A smart water metering deployment based on the fog computing paradigm,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.870337Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d3e8a2ed-a6ea-4f62-90e5-8375bb4b93c4 · outbound
This paper cites Identifying water consumption patterns in education buildings before, during and after covid-19 lockdown periods,.
Filling in the Blanks: Applying Data Imputation in incomplete Water Metering Data Identifying water consumption patterns in education buildings before, during and after covid-19 lockdown periods,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T05:04:05.854655Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.