4-CBA Concentration Soft Sensor Based on Modified Back Propagation Algorithm Embedded with Ridge Regression

Abstract

Abstract Considering that there exist many factors having highly nonlinear effects on the concentration of the 4-carboxybenzaldehyde (4-CBA), which is the most important intermediate product of the oxidation of the p-xylene (PX) to terephthalic acid (TA), a modified back propagation algorithm embedded with ridge regression (BP-RR) was proposed to develop a soft sensor of the 4CBA concentration. To overcome the two main flaws of regulaz multi-layer neural networks, i.e. the tendency of overfitting and the difficulty to determine the optimal number of neurons for the hidden layer, fustly, a three-layer network is selected and the number of the hidden-layer neurons is determined according to the number of the training samples and the number of the neural network pazameters. Then, BP is applied to learn from the training samples. In sequel, the ridge regression is employed to remove the multicollinearity among the hidden-layer-node outputs and obtain the optimal weights (and thresholds) between the hidden lay...