论文信息 - USE OF NEURAL NETWORK TO PREDICT INDUSTRIAL DRYER PERFORMANCE

USE OF NEURAL NETWORK TO PREDICT INDUSTRIAL DRYER PERFORMANCE

ABSTRACT The use of neural networks to predict performance of a Yankee dryer is presented. A 3-layer network with 4 inputs and 2 outputs is usd. Training is performed using back-propagation algorithm and data from a Yankee simulation program based on Karlsson and Heikkila's model. The trained network is evaluated using randomly generated test cases as input. The effect of number of training cases and hidden neurons are examined.

Arun S. Mujumdar | B. Huang | A. Mujumdar | B. Huang

[1] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[2] N. V. Bhat,et al. Use of neural nets for dynamic modeling and control of chemical process systems , 1990 .

[3] Josiah C. Hoskins,et al. Artificial neural network models for knowledge representation in chemical engineering , 1990 .

[4] N.V. Bhat,et al. Modeling chemical process systems via neural computation , 1990, IEEE Control Systems Magazine.

[5] Abhay B. Bulsari,et al. Artificial Neural Networks for Predicting Silicon Content in Raw Iron From Blast Furnaces , 1991, ICCI.

[6] George Cybenko,et al. Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..