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A neural network modeling method for batch process

Lookup NU author(s): Dr Jie ZhangORCiD

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Abstract

For the production of high quality chemicals batch manufacture plays an important role. Since some parameters of a batch chemical reaction are difficult to measure with conventional instruments, Artificial Neural Network (ANN) model has become a useful tool for the estimation of chemical reaction indexes. Data restructuring is an effective method for improving properties and accuracy of the ANN model. This paper constructed an ANN model for estimating the number-average molecular weight and polydispersity in batch polymerization process and presented the method of training data restructuring. The results were satisfactory. © Springer-Verlag 2004.

Publication metadata

Author(s): Liu Y, Yang X, Zhang J

Publication type: Book Chapter

Publication status: Published

Book Title: Advances in Neural Networks - ISNN 2004

Year: 2004

Volume: 3174

Pages: 874-879

Print publication date: 01/01/2004

Series Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publisher: Springer

Place Published: Berlin

URL: http://dx.doi.org/10.1007/978-3-540-28648-6_139

DOI: 10.1007/978-3-540-28648-6_139

Library holdings: Search Newcastle University Library for this item

ISBN: 9783540228431

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