This paper presents a method of selecting cotton bales to meet the specified ring yarn properties using artificial neural networks. Five yarn properties and yarn count were used as inputs, whereas the Spinning Consistency Index (SCI) and micronaire were the outputs to the neural network models. Bales were selected according to the predicted combinations of SCI and micronaire. The properties of yarns spun from selected bales show good association with the target yarn properties.
Contents
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Publicly AvailableSELECTING COTTON BALES BY SPINNING CONSISTENCY INDEX AND MICRONAIRE USING ARTIFICIAL NEURAL NETWORKSSeptember 19, 2023
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Publicly AvailableELECTRICAL PROPERTIES OF CONDUCTIVE POLYMERS: PET – NANOCOMPOSITES’ FIBRESSeptember 19, 2023
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Publicly AvailableINTEREST OF A COMPOUND YARN TO IMPROVE FABRIC PERFORMANCESeptember 19, 2023
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Publicly AvailableTHE MECHANISM OF END BREAKAGE IN RING SPINNING: A STATISTICAL MODEL TO PREDICT THE END BREAK IN RING SPINNINGSeptember 19, 2023
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Publicly AvailableMODELLING AND SIMULATION OF THE MECHANICAL BEHAVIOUR OF WEFT-KNITTED FABRICS FOR TECHNICAL APPLICATIONSSeptember 19, 2023
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September 19, 2023
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Publicly AvailableDIFFUSION OF DISPERSE DYES INTO SUPERMICROFIBRESSeptember 19, 2023