During the last thirty years there has been a rapidly growing interest in the field of genetic algorithms (GAs). The field is at a stage of tremendous growth, as evidenced by the increasing number of conferences, workshops, and papers concerning it, as well as the emergence of a central journal for the field. With their great robustness, genetic algorithms have proven to be a promising technique for many optimisation, design, control, and machine learning applications. This paper presents a new technique for detecting the source of fault in spinning mills from spectrograms by using genetic algorithm.
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Publicly AvailableDETECTING THE FAULT FROM SPECTROGRAMS BY USING GENETIC ALGORITHM TECHNIQUESSeptember 20, 2023
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Publicly AvailableINVESTIGATION INTO THE PERIODICITY OF MASS VARIATION OF YARN AND ITS EFFECT ON FABRIC APPEARANCESeptember 20, 2023
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Publicly AvailableNEW APPROACH TO A THEORETICAL STUDY OF SOME OF THE PARAMETERS IN THE KNITTING PROCESS, AND THEIR INFLUENCE ON KNIT-FABRIC STITCH DENSITYSeptember 20, 2023
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Publicly AvailableMOISTURE TRANSMISSION THROUGH TEXTILESSeptember 20, 2023
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Publicly AvailableGRAFTING MMA ONTO FLAX UNDER THE INFLUENCE OF MICROWAVE RADIATION AND THE USE OF FLAX-g-POLY(MMA) IN PREPARING PF COMPOSITESSeptember 20, 2023
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Publicly AvailableTEXTILE PREFORMS FOR DENTAL APPLICATIONSSeptember 20, 2023