Paper Citation Record · LEDGER

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.28481.

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

pith.paper-citation-record.v1
2607.28481 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T06:00:23.132224Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

32 of 32 outbound references displayed

verified exact0
verified fuzzy0
unresolved31
parse uncertain0
malformed identifier1
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External citation measurements

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Outbound references

Observation 17ba07b6-e241-48ec-92a4-10787fd9fdcd · outbound

This paper cites Modeling the structural deterioration of urban drainage pipes: the state-of-the-art in statistical methods.Urban Water Journal, 7(1):47–59, 2010.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Modeling the structural deterioration of urban drainage pipes: the state-of-the-art in statistical methods.Urban Water Journal, 7(1):47–59, 2010

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:21.970184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4086734b-f181-48e8-a57a-06280e33fa75 · outbound

This paper cites Logic tensor networks.Artificial Intelligence, 303:103649, 2022.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Logic tensor networks.Artificial Intelligence, 303:103649, 2022

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.169979Z

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Observation aa11cb3f-2f3c-429c-9c70-3f800c4a5691 · outbound

This paper cites Pn-owl: A two stage algorithm to learn fuzzy concept inclusions from owl ontologies.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Pn-owl: A two stage algorithm to learn fuzzy concept inclusions from owl ontologies

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.285074Z

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Observation 0c6d960f-2ac6-4f5e-af3f-e00a54adabcd · outbound

This paper cites Fuzzy owl-boost: Learning fuzzy concept inclusions via real-valued boosting.Fuzzy Sets and Systems, 438:164–186, 2022.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Fuzzy owl-boost: Learning fuzzy concept inclusions via real-valued boosting.Fuzzy Sets and Systems, 438:164–186, 2022

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.444321Z

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Observation 883b0417-3ada-4720-8959-e3966fa861f1 · outbound

This paper cites Neuro-fuzzy approaches for san- itary sewer pipeline condition assessment.Journal of Computing in Civil engineering, 15(1):4–14, 2001.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Neuro-fuzzy approaches for san- itary sewer pipeline condition assessment.Journal of Computing in Civil engineering, 15(1):4–14, 2001

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.544924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation effd23ff-887e-4c42-9005-eff2f099533a · outbound

This paper cites Fast effective rule induction.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Fast effective rule induction

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.663366Z

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Observation a2d8d638-8dbb-495f-8905-612392d8ba1f · outbound

This paper cites Neural Logic Machines.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Neural Logic Machines

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.826223Z

Source-reported events for the cited work

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Observation 5cdb8b73-5d2b-4c3a-890b-489168d4ee2d · outbound

This paper cites Approaches to sewer maintenance: A review.Urban Water, 2:343–356, 12 2000.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Approaches to sewer maintenance: A review.Urban Water, 2:343–356, 12 2000

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.891429Z

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Observation 1293bf83-a5a0-49b0-a54f-7a5179932b9d · outbound

This paper cites Un- derground sewer pipe condition assessment based on convolutional neural networks.Automation in Construction, 106:102849, 2019.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Un- derground sewer pipe condition assessment based on convolutional neural networks.Automation in Construction, 106:102849, 2019

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.898245Z

Source-reported events for the cited work

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Observation 737c9510-22ca-4a45-860d-c929d197d87f · outbound

This paper cites Multi-task classification of sewer pipe defects and properties using a cross-task graph neural network decoder.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Multi-task classification of sewer pipe defects and properties using a cross-task graph neural network decoder

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.908201Z

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Observation 16e7e24e-b1a7-4a14-9f71-24ea2c760245 · outbound

This paper cites A survey on image- based automation of cctv and sset sewer inspections.Automation in Con- struction, 111:103061, 2020.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks A survey on image- based automation of cctv and sset sewer inspections.Automation in Con- struction, 111:103061, 2020

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.913639Z

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Observation 4a451ecf-0078-466e-bb30-9ee04f0e3c90 · outbound

This paper cites an unresolved cited work.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.919974Z

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Observation 5ecf8d35-f7e2-480c-bada-0916edd44171 · outbound

This paper cites Klir and Bo Yuan.Fuzzy sets and fuzzy logic: theory and appli- cations.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Klir and Bo Yuan.Fuzzy sets and fuzzy logic: theory and appli- cations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.926695Z

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Observation 39106a7f-a36e-4054-adf3-78e49932791b · outbound

This paper cites Concept bottleneck models.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Concept bottleneck models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.931904Z

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Observation 5790d126-e590-4534-9add-96d7969f399a · outbound

This paper cites Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks.Automa- tion in Construction, 91:273–283, 2018.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks.Automa- tion in Construction, 91:273–283, 2018

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.938881Z

Source-reported events for the cited work

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Observation ed8d45fc-5e3e-4f7d-8eee-447eab6d7f84 · outbound

This paper cites Sewer damage detection from imbalanced cctv inspection data using deep convolutional neural networks with hierarchical classification.Automation in Construction, 101:199–208, 2019.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Sewer damage detection from imbalanced cctv inspection data using deep convolutional neural networks with hierarchical classification.Automation in Construction, 101:199–208, 2019

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.947498Z

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Observation d0f14a06-f98a-464c-b8ee-b2caeb33c806 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Swin transformer: Hierarchical vision transformer using shifted windows

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.952678Z

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Observation 206955d3-13b4-49af-818b-907056fdbc57 · outbound

This paper cites A model of mul- timedia information retrieval.Journal of the ACM, 48(5):909–970, 2001.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks A model of mul- timedia information retrieval.Journal of the ACM, 48(5):909–970, 2001

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.963940Z

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Observation 3aba64bd-7f07-4fff-98f0-fda8fa527725 · outbound

This paper cites Mitchell.Machine Learning.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Mitchell.Machine Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.980694Z

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Observation 804b0adf-6701-4846-b464-08157dba616c · outbound

This paper cites Ross Quinlan.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Ross Quinlan

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.987871Z

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Observation 22555806-16be-40ad-9a7a-42d5aaae7b1b · outbound

This paper cites Ross Quinlan.C4.5: Programs for Machine Learning.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Ross Quinlan.C4.5: Programs for Machine Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:22.996030Z

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Observation b1ca2cb0-6f4e-49e2-8ab2-db8c29360a5b · outbound

This paper cites Neuro-Symbolic Artificial Intelligence: Current Trends.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Neuro-Symbolic Artificial Intelligence: Current Trends

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.001375Z

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Observation 3d921fc4-365b-4053-882c-0d45250d784b · outbound

This paper cites Neuro-fuzzy network for the classi- fication of buried pipe defects.Automation in Construction, 15(1):73–83, 2006.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Neuro-fuzzy network for the classi- fication of buried pipe defects.Automation in Construction, 15(1):73–83, 2006

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.006583Z

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Observation 3b9f5e51-e6cf-4e43-a43f-ca5d3b4deabe · outbound

This paper cites Classification of underground pipe scanned images using feature extraction and neuro-fuzzy algorithm.IEEE Transactions on Neural Networks, 13(2):393–401, 2002.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Classification of underground pipe scanned images using feature extraction and neuro-fuzzy algorithm.IEEE Transactions on Neural Networks, 13(2):393–401, 2002

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.014204Z

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Observation 820e12b3-39d7-4299-9eed-cc0de0295974 · outbound

This paper cites Managing uncertainty and vagueness in description log- ics, logic programs and description logic programs.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Managing uncertainty and vagueness in description log- ics, logic programs and description logic programs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.021290Z

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Observation 445bf282-ea6f-49b5-abb8-387c4f6c2832 · outbound

This paper cites CRC Studies in Informatics Series.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks CRC Studies in Informatics Series

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.027008Z

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Observation c3e88a8c-56f7-41e2-8d3b-ae0c2a26ea61 · outbound

This paper cites Sewer asset management–state of the art and research needs.Urban Water Journal, 16(9):662–675, 2019.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Sewer asset management–state of the art and research needs.Urban Water Journal, 16(9):662–675, 2019

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.031925Z

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Observation c52c85d0-30b1-4f1d-91b8-932ac5cceb09 · outbound

This paper cites an unresolved cited work.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.036726Z

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Observation 4f879353-3cdb-45a1-acae-d23b79a229e7 · outbound

This paper cites an unresolved cited work.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.078669Z

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Observation e655f850-9595-4fcd-9774-229cd927a27d · outbound

This paper cites Morgan Kaufmann, 3rd edition, 2011.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Morgan Kaufmann, 3rd edition, 2011

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.106040Z

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Observation a5465f8e-efa0-4409-a1df-91c965fcd778 · outbound

This paper cites NeurASP: Embracing Neural Networks into Answer Set Programming.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks NeurASP: Embracing Neural Networks into Answer Set Programming

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-31T06:00:23.116955Z

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Observation 1d973028-0960-41fc-8d63-704afe9e2fef · outbound

This paper cites Automatic sewer defect detection and severity quantification based on pixel-level semantic segmentation.Tunnelling and Underground Space Technology, 123:104403, 2022.

A Fuzzy Rule-based Neuro-Symbolic Approach for Pipe Severity Prediction in Sewer Networks Automatic sewer defect detection and severity quantification based on pixel-level semantic segmentation.Tunnelling and Underground Space Technology, 123:104403, 2022

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-07-31T06:00:23.132224Z

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Pith citing papers

No inbound Pith citation observations are available.