Paper Citation Record · LEDGER

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation

As of 21 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2501.16377.

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

pith.paper-citation-record.v1
2501.16377 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:17:18.347097Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

13 of 13 outbound references displayed

verified exact1
verified fuzzy11
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6c2299a4-0588-44df-8636-8eda218fc7c1 · outbound

This paper cites Battery 2030: Resilient, sustainable, and circular,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Battery 2030: Resilient, sustainable, and circular,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.587161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5280f93a-2401-497b-9452-bc8f9bb039d5 · outbound

This paper cites Sagpcn: Self-attention graph pooling convolutional network for battery state of health estimation,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Sagpcn: Self-attention graph pooling convolutional network for battery state of health estimation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.570189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dd7cb78f-5a2e-4c83-ba00-2f816647e521 · outbound

This paper cites Practical battery health monitoring using uncertainty-aware bayesian neural network,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Practical battery health monitoring using uncertainty-aware bayesian neural network,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.552936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c18038f-62ca-43d5-91ff-3e5b50b7f16f · outbound

This paper cites An end-cloud collaboration approach for state-of-health estimation of lithium-ion batteries based on bi-lstm with collaboration of multi-feature and attention mechanism,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation An end-cloud collaboration approach for state-of-health estimation of lithium-ion batteries based on bi-lstm with collaboration of multi-feature and attention mechanism,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.538241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 20e815e8-65ae-4190-8972-e8d64536c087 · outbound

This paper cites Optimized data-driven approach for remaining useful life prediction of lithium-ion batteries based on sliding window and systematic sampling,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Optimized data-driven approach for remaining useful life prediction of lithium-ion batteries based on sliding window and systematic sampling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.521899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 401e8989-a73f-4286-bfd6-1193e7603bf2 · outbound

This paper cites State of health estimation and re- maining useful life prediction for lithium-ion batteries by improved particle swarm optimization-back propagation neural network,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation State of health estimation and re- maining useful life prediction for lithium-ion batteries by improved particle swarm optimization-back propagation neural network,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.505411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da87a517-c0ac-43ef-bae8-e11a53ea20aa · outbound

This paper cites A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.489756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f0cec5b5-69e7-42ff-b091-48d22b257015 · outbound

This paper cites Variational mode decomposition,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Variational mode decomposition,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T15:17:18.322405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b7ecf19-7b1f-44f1-94ce-9fa3bf7b48cf · outbound

This paper cites Remaining useful life prediction for lithium-ion batteries based on cs-vmd and gru,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Remaining useful life prediction for lithium-ion batteries based on cs-vmd and gru,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.462600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cff305c3-d8d7-44be-b16f-32d9e127420e · outbound

This paper cites Edge–cloud collaborative estimation lithium-ion battery soh based on mewoa-vmd and transformer,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Edge–cloud collaborative estimation lithium-ion battery soh based on mewoa-vmd and transformer,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.446960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c892d4b0-1f73-4699-b8b2-ec807a1dc55c · outbound

This paper cites A new optimizer using particle swarm theory,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation A new optimizer using particle swarm theory,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.431158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1176405f-7730-4499-9711-2b0c84380206 · outbound

This paper cites Battery data set,.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation Battery data set,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:17:18.414164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d8612227-ec38-4a5f-a32a-0f0d094b1e38 · outbound

This paper cites GiNet: Integrating Sequential and Context-Aware Learning for Battery Capacity Prediction.

Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation GiNet: Integrating Sequential and Context-Aware Learning for Battery Capacity Prediction

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:17:18.395968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.