The BP Neural Network Modeling on Worsted Spinning with Grey Superior Theory and Correlation Analysis

摘要

The characteristic of worsted spinning procedures and the BP neural network modeling technology all have been summarily analyzed. Based on the nonlinear and vague relationship depend on fibers’ performance and craft parameters, the grey superior theory and correlation analysis method are proposed to select more important parameters. Therefore, the input layer node numbers reduce; the network topology structure is simplified that the network’s accuracy and performance are all enhanced greatly. After modeling, the relative mean error percents (MEP) between the predict results and measured value for the yarns’ four quality variables, such as Yarn unevenness, strength, extension at break and ends-down rate, reduce to 2.55%, 2.23%, 2.78% and 1.82% respectively compared to the former 4.56%, 3.35%, 4.24% and 3.95%. The correlation coefficients between them for the four quality variables all have the remarkable enhancement.