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Leveraging Machine Learning for Pipeline Condition Assessment

Research article (Journal of Pipeline Systems Engineering and Practice, 2023) · cited 22× · AI/ML
academia openalex:W4376506311
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Leveraging Machine Learning for Pipeline Condition Assessment

Summary

Leveraging Machine Learning for Pipeline Condition Assessment is a scholarly article[1].

Key Facts

  • Leveraging Machine Learning for Pipeline Condition Assessment's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Leveraging Machine Learning for Pipeline Condition Assessment. Retrieved May 24, 2026, from https://4ort.xyz/entity/leveraging-machine-learning-for-pipeline-condition-assessment
MLA “Leveraging Machine Learning for Pipeline Condition Assessment.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/leveraging-machine-learning-for-pipeline-condition-assessment.
BibTeX @misc{4ortxyz_leveraging-machine-learning-for-pipeline-condition-assessment_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Leveraging Machine Learning for Pipeline Condition Assessment}}, year = {2026}, url = {https://4ort.xyz/entity/leveraging-machine-learning-for-pipeline-condition-assessment}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Leveraging Machine Learning for Pipeline Condition Assessment — https://4ort.xyz/entity/leveraging-machine-learning-for-pipeline-condition-assessment (retrieved 2026-05-24)

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