Feasibility of the Optimal Design of AI-Based Models Integrated with Ensemble Machine Learning Paradigms for Modeling the Yields of Light Olefins in Crude-to-Chemical Conversions.

Usman AG, Tanimu A, Abba SI, Isik S, Aitani A, Alasiri H.

Open source

DOI
10.1021/acsomega.3c05227
Published
2023-10-18
Container
ACS Omega
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1021/acsomega.3c05227,
  title = {Feasibility of the Optimal Design of AI-Based Models Integrated with Ensemble Machine Learning Paradigms for Modeling the Yields of Light Olefins in Crude-to-Chemical Conversions.},
  author = {Usman AG and  Tanimu A and  Abba SI and  Isik S and  Aitani A and  Alasiri H.},
  year = {2023},
  journal = {ACS Omega},
  doi = {10.1021/acsomega.3c05227},
  url = {https://doi.org/10.1021/acsomega.3c05227}
}

RIS

TY  - JOUR
TI  - Feasibility of the Optimal Design of AI-Based Models Integrated with Ensemble Machine Learning Paradigms for Modeling the Yields of Light Olefins in Crude-to-Chemical Conversions.
AU  - Usman AG
AU  -  Tanimu A
AU  -  Abba SI
AU  -  Isik S
AU  -  Aitani A
AU  -  Alasiri H.
PY  - 2023
JO  - ACS Omega
DO  - 10.1021/acsomega.3c05227
UR  - https://doi.org/10.1021/acsomega.3c05227
ER  -

APA

AG, U., A, T., SI, A., S, I., A, A., & H., A. (2023). Feasibility of the Optimal Design of AI-Based Models Integrated with Ensemble Machine Learning Paradigms for Modeling the Yields of Light Olefins in Crude-to-Chemical Conversions.. ACS Omega. https://doi.org/10.1021/acsomega.3c05227

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