A novel neural-evolutionary framework for predicting weight on the bit in drilling operations

This study compares the performance of artificial neural networks (ANN) trained by grey wolf optimization (GWO), biogeography-based optimization (BBO), and Levenberg–Marquardt (LM) to estimate the weight on bit (WOB). To this end, a dataset consisting of drilling depth, drill string rotational speed...

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Detalles Bibliográficos
Autores principales: Dowlatabadi, Masrour, Azizi, Saeed, Dehbashi, Mohsen, Sadeqi, Hamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613297/
https://www.ncbi.nlm.nih.gov/pubmed/37898632
http://dx.doi.org/10.1038/s41598-023-45760-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613297/
https://www.ncbi.nlm.nih.gov/pubmed/37898632
http://dx.doi.org/10.1038/s41598-023-45760-6

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