Abstract
In order to forecast the quality of cotton yarn based on the cotton fiber indexes more accurately, a yarn quality forecasting model based on Mind Evolutionary Algorithm (MEA) was used to optimize the BP neural network prediction of yarn strength and yarn evenness. The model adopts the Mind Evolutionary Algorithm to complete the BP network weights and threshold optimization, giving full play to the advantages of this method in the field of global optimization. The results show that the BP neural network prediction model based on Mind Evolutionary Algorithm to optimize is superior to the single BP neural network prediction model.
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