Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process reg...

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Bibliographic Details
Main Authors: Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.
Other Authors: 57226256715
Format: Article
Published: John Wiley and Sons Ltd 2023
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Institution: Universiti Tenaga Nasional
Description
Summary:Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis