Two- and Three-Layer Recurrent Elman Neural Networks as Models of Dynamic Processes

Antoni Wysocki , Maciej Ławryńczuk

Abstract

The goal of paper is to study and compare the effectiveness of two- and three-layer Elman recurrent neural networks used for modelling of dynamic processes. Training of such networks is discussed. For a neutralisation reactor benchmark system it is shown that the rudimentary Elman structure with two layers is much better in terms of accuracy and the number of parameters. Furthermore, its training is much easier.
Author Antoni Wysocki IAiIS
Antoni Wysocki,,
- The Institute of Control and Computation Engineering
, Maciej Ławryńczuk IAiIS
Maciej Ławryńczuk,,
- The Institute of Control and Computation Engineering
Pages165-175
Publication size in sheets0.5
Book Szewczyk Roman, Kaliczyńska Małgorzata, Zieliński Cezary: Challenges in Automation, Robotics and Measurement Techniques. Proceedings of AUTOMATION-2016, March 2-4, 2016, Warsaw, Poland, Advances in Intelligent Systems and Computing, vol. 440, 2016, Springer International Publishing, ISBN 978-3-319-29356-1, [978-3-319-29357-8], 919 p., DOI:10.1007/978-3-319-29357-8
DOIDOI:10.1007/978-3-319-29357-8_15
URL http://link.springer.com/chapter/10.1007/978-3-319-29357-8_15
projectDevelopment of methodology of control, decision support and production management. Project leader: Zieliński Cezary, , Phone: 5102, start date 19-05-2015, end date 31-12-2016, 504/02233/1031, Completed
WEiTI Działalność statutowa
Languageen angielski
File
Wysock Lawrynczuk automation_2016.pdf 472.95 KB
Score (nominal)15
ScoreMinisterial score [Punktacja MNiSW] = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) [Punktacja MNiSW (2013-2016)] = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Citation count*0 (2018-06-16)
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