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2020 | OriginalPaper | Buchkapitel

Deep Echo State Networks in Industrial Applications

verfasst von : Stefano Dettori, Ismael Matino, Valentina Colla, Ramon Speets

Erschienen in: Artificial Intelligence Applications and Innovations

Verlag: Springer International Publishing

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Abstract

This paper analyzes the impact of reservoir computing, and, in particular, of Deep Echo State Networks, to the modeling of highly non-linear dynamical systems that can be commonly found in the industry. Several applications are presented focusing on forecasting models related to energy content of steelwork byproduct gasses. Deep Echo State Network models are trained, validated and tested by exploiting datasets coming from a real industrial context, with good results in terms of accuracy of the predictions.

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Titel: Deep Echo State Networks in Industrial Applications
verfasst von: Stefano Dettori
Ismael Matino
Valentina Colla
Ramon Speets
Verlag: Springer International Publishing
Buch: Artificial Intelligence Applications and Innovations
Print ISBN: 978-3-030-49185-7

Electronic ISBN: 978-3-030-49186-4

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-49186-4_5

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