Polynomial Integrated PLS Regression for Predicting Corrosion Inhibition Efficiency of Ionic Liquids

Corrosion degrades and weakens metal surfaces, leading to structural failure and significant safety hazards across various sectors. Data driven machine learning offers a rapid, cost-effective alternative to the expensive and time consuming traditional experimental methods by predicting inhibitor per...

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Hlavní autoři:	Petrus Praditya Aswangga, Muhammad Akrom
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Politeknik Negeri Batam 2025-08-01
Edice:	Journal of Applied Informatics and Computing
Témata:	corrosion inhibitor ionic liquid polynomial function machine learning partial least squares
On-line přístup:	https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/10158
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