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Paper Citation Record · LEDGER

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching

As of 22 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2507.11726.

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

pith.paper-citation-record.v1
2507.11726 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:09:01.163434Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34ca3564-8500-474a-b921-3a12874d1744 · outbound

This paper cites Corrective switching algorithm for relieving overloads and voltage violations,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Corrective switching algorithm for relieving overloads and voltage violations,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:04.467299Z

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.

source=pdf_text observed=2026-08-06T17:08:59.458501Z digest=sha256:de7175463b365c8cdf9cd9b29ee618d2a3e79ddf4d623158aadc27e4b6edf0ec

Observation 39361177-9341-4cb3-a50e-bc3f82482729 · outbound

This paper cites Optimal transmission switching considering voltage security and n-1 contingency analysis,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Optimal transmission switching considering voltage security and n-1 contingency analysis,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:04.190972Z

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.

source=pdf_text observed=2026-08-06T17:08:59.551415Z digest=sha256:2b2d683be25019611c2e2599983adebfb80a87c44d9c7461135075d40afc8969

Observation 78aae21b-b53d-4eef-8de1-83ca91e5d599 · outbound

This paper cites Optimal network reconfiguration for congestion management by deterministic and genetic algorithms,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Optimal network reconfiguration for congestion management by deterministic and genetic algorithms,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:03.934916Z

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.

source=pdf_text observed=2026-08-06T17:08:59.734953Z digest=sha256:47eeff58da275f87405c21367553c44e2c19741552c6eebf2269944217780461

Observation cb051ec8-7bec-45b9-9c94-5cb5e1b8f59a · outbound

This paper cites Optimal transmission switching,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Optimal transmission switching,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:03.725983Z

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.

source=pdf_text observed=2026-08-06T17:08:59.843652Z digest=sha256:47c95ba92a7afad6fdff32e6f68a81b65bd0297cd2a79ba421678851b752527d

Observation 6c761f84-405d-4649-b908-2723c559667a · outbound

This paper cites Loss reduction by network switching,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Loss reduction by network switching,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:03.441342Z

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.

source=pdf_text observed=2026-08-06T17:08:59.976904Z digest=sha256:439a405d0ce982e39e1b07182f0a6234bef9e4b7d34154cf6f18c33ba4fe3871

Observation ccbbe0ef-7d28-4ae2-aae5-ade7f358478c · outbound

This paper cites Transmission switching with connectivity-ensuring constraints,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Transmission switching with connectivity-ensuring constraints,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:03.101929Z

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.

source=pdf_text observed=2026-08-06T17:09:00.113168Z digest=sha256:899a268d1ce0ac26366f6f68e9487b8efc507a6ec58bf593bcdff090c7be758b

Observation 12576c50-6365-4718-95db-149c4b68ae12 · outbound

This paper cites Optimal transmission switching considering probabilistic reliability,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Optimal transmission switching considering probabilistic reliability,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:02.832450Z

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.

source=pdf_text observed=2026-08-06T17:09:00.249687Z digest=sha256:17d8a76fb81bab2ec8d9db5627fb8f60a9703d3e63b28118143aed75356c949e

Observation 9a095373-e84b-4e6a-b519-5e38ebb33b24 · outbound

This paper cites Congestion management using optimal transmission switching,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Congestion management using optimal transmission switching,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:02.521428Z

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.

source=pdf_text observed=2026-08-06T17:09:00.359169Z digest=sha256:7aa3b8a0f3eb930c52074efdd91f8b5d95a702914672712d87365a0155a2289f

Observation 2844943a-487d-4d43-b042-7ae158e1e4e7 · outbound

This paper cites Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:02.249064Z

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.

source=pdf_text observed=2026-08-06T17:09:00.481776Z digest=sha256:7883c574fb614845bfa4976f2894709c4509d92c1b72467fc80b9ba514477219

Observation 8e8fb142-c841-4b3b-8b0d-80f0fd5bfd2d · outbound

This paper cites Model-free real-time ev charging scheduling based on deep reinforcement learning,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Model-free real-time ev charging scheduling based on deep reinforcement learning,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:02.014446Z

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.

source=pdf_text observed=2026-08-06T17:09:00.593981Z digest=sha256:87203adcd0746114ce11bb42e3e20176d40068c49bd5993e411ae51d566e52d4

Observation 2afe2d34-3470-4e01-8565-7d0b5a23fc2f · outbound

This paper cites Incentive-based demand response for smart grid with reinforcement learning and deep neural network,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Incentive-based demand response for smart grid with reinforcement learning and deep neural network,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:01.750056Z

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.

source=pdf_text observed=2026-08-06T17:09:00.712341Z digest=sha256:f294c0e8e84d057d7dbf78ba6701b1b6db3fde77a87f359045c14ea60aadc6c1

Observation f096af96-1ede-40fe-916b-267648ec8382 · outbound

This paper cites Data-driven load frequency control for stochastic power systems: A deep reinforcement learning method with continuous action search,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Data-driven load frequency control for stochastic power systems: A deep reinforcement learning method with continuous action search,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:09:01.453999Z

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.

source=pdf_text observed=2026-08-06T17:09:00.843494Z digest=sha256:1a51b41ddf0610040840fe6af294619008d85188f2f0d7743bbd697a32786631

Observation d6f0c3d9-e885-45a1-afec-35257997050e · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Soft Actor-Critic Algorithms and Applications

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T17:09:01.026343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:09:01.026343Z digest=sha256:02d12b94071f83766315b32d9ae2b3f761730eb42da37986c00fb851fb5e9594

Observation dca900f8-71b5-4247-b6fd-a94be787f7cd · outbound

This paper cites Dueling network architectures for deep reinforcement learning,.

A Deep Reinforcement Learning Method for Multi-objective Transmission Switching Dueling network architectures for deep reinforcement learning,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T17:09:01.163434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:09:01.163434Z digest=sha256:68bc0c77b4f758443b4c807e56715ee98dbd098cb9c21056d8cfcef787e2cd7b

Pith citing papers

No inbound Pith citation observations are available.