Paper Citation Record · LEDGER

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity

As of 17 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2501.17166.

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

pith.paper-citation-record.v1
2501.17166 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:33:50.794822Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:59:52.738625Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:59:58.384129Z

Reference resolution

18 of 18 outbound references displayed

verified exact2
verified fuzzy13
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98367c87-1a54-4e59-a8fc-b388d478e4d7 · outbound

This paper cites Monitoring globa l carbon emissions in 2022,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Monitoring globa l carbon emissions in 2022,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.133767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b3e4c70a-13c6-41bb-a4af-3734ad049695 · outbound

This paper cites Greenhouse gas emissions trajectories for th e information and communication technology sector compatible with the un fccc paris agreement,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Greenhouse gas emissions trajectories for th e information and communication technology sector compatible with the un fccc paris agreement,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.116867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0aec8bf1-922f-4ed1-9b45-bca3265db6de · outbound

This paper cites Critical review of biomimicry in the ﬁeld of design,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Critical review of biomimicry in the ﬁeld of design,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.100403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 56b87865-25ab-4ee5-afb3-73c667a6e1bb · outbound

This paper cites Swarm intelligence in cellular robo tic systems,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Swarm intelligence in cellular robo tic systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.083288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d54e2389-dc40-4bc3-a140-6f7cbad12b4c · outbound

This paper cites A systematic literature review on swarm intelligence based intrusion detection system: past, pres ent and future,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity A systematic literature review on swarm intelligence based intrusion detection system: past, pres ent and future,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.067134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2a9f82ba-78a5-4c67-a64b-7dd3a8941394 · outbound

This paper cites Quantifying the Carbon Emissions of Machine Learning.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Quantifying the Carbon Emissions of Machine Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T18:33:50.731940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9be458fe-f09b-48e9-8b6d-7e2fbeb13239 · outbound

This paper cites A Systematic Literature R eview on Swarm Intelligence Based Intrusion Detection System: Past , Present and Future,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity A Systematic Literature R eview on Swarm Intelligence Based Intrusion Detection System: Past , Present and Future,

Reference 7

Resolution: verified exact; doi, observed 2026-08-10T18:33:50.857791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a5a035c0-e87a-4b50-8228-8b45bcb0b8e3 · outbound

This paper cites Modeling and estimation of co2 emissions in china based on artiﬁcial intelligence,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Modeling and estimation of co2 emissions in china based on artiﬁcial intelligence,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.051298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d5534674-2ded-4372-bcf2-4cdff0612e11 · outbound

This paper cites Prediction of co2 emissions in china by g eneralized regression neural network optimized with fruit ﬂy optimiza tion algo- rithm,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Prediction of co2 emissions in china by g eneralized regression neural network optimized with fruit ﬂy optimiza tion algo- rithm,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.035578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81b28559-4727-463d-9c0d-ea87058c757b · outbound

This paper cites Modeling and foreca sting CO2 emissions in China and its regions using a novel ARIMA-LS TM model,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Modeling and foreca sting CO2 emissions in China and its regions using a novel ARIMA-LS TM model,

Reference 10

Resolution: verified exact; doi, observed 2026-08-10T18:33:50.839750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4f14e3d-7732-4041-91ee-c9b864f085f5 · outbound

This paper cites Driving factors of co2 emis sions: further study based on machine learning,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Driving factors of co2 emis sions: further study based on machine learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.019327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 62b2d1bc-22b1-4177-b4a6-ebe7b10d1bea · outbound

This paper cites Comparative analysis of co2 emissions and economic perfor mance in the united states and china: Navigating sustainable development in the climate change era,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Comparative analysis of co2 emissions and economic perfor mance in the united states and china: Navigating sustainable development in the climate change era,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:51.001580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b4e99863-26cd-41c7-b98d-c1d6b1f92867 · outbound

This paper cites Forecasting chinese provincial c o2 emissions: A universal and robust new-information-based g rey model,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Forecasting chinese provincial c o2 emissions: A universal and robust new-information-based g rey model,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:50.983593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9484ebb0-6cea-405c-b132-fc73dc54609d · outbound

This paper cites Sim- pliﬁed swarm optimization for hyperparameters of convolut ional neural networks,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Sim- pliﬁed swarm optimization for hyperparameters of convolut ional neural networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:50.967308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be3111fe-d07a-4dbe-876d-c558e07c5ae1 · outbound

This paper cites Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T18:33:50.777154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 931b8494-d8b6-48d5-96f9-df114262bde7 · outbound

This paper cites Bio-inspired computing: Algorithms revi ew, deep analysis, and the scope of applications,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Bio-inspired computing: Algorithms revi ew, deep analysis, and the scope of applications,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:50.950017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f8bed8e-4293-4cae-b432-b3d9cc759189 · outbound

This paper cites Hybrid genetic and penguin search optimiz ation algorithm (ga-pseoa) for efﬁcient ﬂow shop scheduling solu tions,.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity Hybrid genetic and penguin search optimiz ation algorithm (ga-pseoa) for efﬁcient ﬂow shop scheduling solu tions,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:33:50.932276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1a01d85c-c7e6-43f2-8d94-75ec53d7932f · outbound

This paper cites A Brief Review of Nature-Inspired Algorithms for Optimization.

Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity A Brief Review of Nature-Inspired Algorithms for Optimization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T18:33:50.794822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 19316935-86e3-4118-b1f2-7ef08f7821db · inbound

A Biomimetic Way for Coral-Reef-Inspired Swarm Intelligence for Carbon-Neutral Wastewater Treatment cites this paper.

A Biomimetic Way for Coral-Reef-Inspired Swarm Intelligence for Carbon-Neutral Wastewater Treatment Optimizing Carbon Footprint in ICT through Swarm Intelligence with Algorithmic Complexity

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:59:58.443126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.