Abstract
This work discusses modelling of a neutralisation process by means of two recurrent modelling techniques: polynomials and neural networks. Model structures and training algorithms are shortly discussed. Two recurrent model classes are compared in terms of accuracy and complexity. Advantages of neural models are emphasised.
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Chaber, P., Ławryńczuk, M. (2015). Recurrent Polynomial and Neural Structures in Modelling of a Neutralisation Process. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Progress in Automation, Robotics and Measuring Techniques. ICA 2015. Advances in Intelligent Systems and Computing, vol 350. Springer, Cham. https://doi.org/10.1007/978-3-319-15796-2_3
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DOI: https://doi.org/10.1007/978-3-319-15796-2_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15795-5
Online ISBN: 978-3-319-15796-2
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