Triboinformatic analysis and prediction of B<sub>4</sub>C and granite powder filled Al 6082 composites using machine learning regression models.

The results indicate a clear trend: as the sliding distance increases, both wear loss and COF also rise.

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The results indicate a consistent increase in wear loss across all composite samples as the applied load rises, while the COF shows a decreasing trend with increasing load.

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