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An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development

Research article (Proceedings of the 7th Unconventional Resources Technology Conference, 2019) · cited 10× · AI/ML
academia openalex:W2967315555
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An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development

Summary

An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development is a scholarly article[1].

Key Facts

  • An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development'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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APA 4ort.xyz Knowledge Graph. (2026). An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-integrated-machine-learning-framework-for-optimizing-unconventional-resources-development
MLA “An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-integrated-machine-learning-framework-for-optimizing-unconventional-resources-development.
BibTeX @misc{4ortxyz_an-integrated-machine-learning-framework-for-optimizing-unconventional-resources-development_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development}}, year = {2026}, url = {https://4ort.xyz/entity/an-integrated-machine-learning-framework-for-optimizing-unconventional-resources-development}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development — https://4ort.xyz/entity/an-integrated-machine-learning-framework-for-optimizing-unconventional-resources-development (retrieved 2026-05-24)

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