Neural Networks in Modelling of Complex Industrial Systems

Autor:	Voula C. Georgopoulos, Peter P. Groumpos, Samuli Pietilä, Ari Nissinen, Heikki N. Koivo
Rok vydání:	1995
Předmět:	Engineering Artificial neural network Neuro-fuzzy Process (engineering) business.industry Cellular neural network Complex system Hierarchical control system Control engineering business Fuzzy logic Nervous system network models
Zdroj:	IFAC Proceedings Volumes. 28:229-234
ISSN:	1474-6670
DOI:	10.1016/s1474-6670(17)51522-0
Popis:	This paper discusses the use of neural networks in the modelling of complex systems in an industrial environment. In particular, issues related to hybrid and hierarchical system modelling and control are presented and neural network architectures that can be applied in such situations arc examined. Also, the model of a laboratory size pilot head box of a paper machine using a neural network is presented as an example process
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1754ae9d55dea7fcb67f40b537036399 https://doi.org/10.1016/s1474-6670(17)51522-0 Zobrazit plný text záznamu