Modelling of thermal shrinkage of seamless steel pipes using artificial neural networks (ANN) focussing on the influence of the ANN architecture

Modelling of thermal shrinkage of seamless steel pipes using artificial neural networks (ANN) focussing on the influence of the ANN architecture

This paper presents two main novel findings. (1) The first finding is the development of an artificial neural network (ANN) model for thermal shrinkage of seamless steel pipes, which represents a new application for ANNs. Mill operators need such fast and accurate models to predict the final pipe ou...

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Bibliographic Details
Main Authors: Raphael Langbauer, Georg Nunner, Thomas Zmek, Jürgen Klarner, René Prieler, Christoph Hochenauer
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Results in Engineering
Subjects:
Diameter prediction
Artificial neural network
Model response
Steel pipe
Hot rolling
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123023001263

Internet

http://www.sciencedirect.com/science/article/pii/S2590123023001263

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