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The article presents an attempt based on experimental data to employ neural network for predicting intermixing ratios for loose materials in a drum mixer. Obtained predicted research results were compared to empirical data using the Pearson's test. Obtained correlation coefficient value is 96%, and proves good data matching.
W pracy dokonano oceny wpływu wybranych parametrów geometrii mieszadła na moc mieszania materiałów ziarnistych. Badania przeprowadzono w mieszalniku bębnowym z mieszadłem mechanicznym i wałem pionowym. Do mieszania zastosowano mieszadło łapowe o różnych średnicach, wysokościach oraz kątach nachylenia.
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