The Prediction Model of Cotton Yarn Intensity Based on the CNN-BP Neural Network

摘要

Yarn strength index is a heavy index of yarn quality, Yarn quality can be well controlled by predicting yarn strength index. Generally, multiple non regression algorithms, support vector machines (SVD) and BP neural network algorithms are generally used to predict yarn strength. This paper presents an algorithm to connect the convolution neural network (CNN) with the BP neural network, which is written as the CNN-BP algorithm. We use 20 sets of data to train CNN-BP algorithm, regression, V-SVD algorithm, and BP neural network. We tested CNN-BP algorithm, regression, V-SVD algorithm, and BP neural network with 5 sets of data. The CNN-BP neural network algorithm is the best in these four algorithms.