The role of neural networks in the optimisation of rolling processes

Larkiola, Jari; Myllykoski, P.; Korhonen, Ari; Cser, L.

doi:10.1016/s0924-0136(98)00206-4

Cited by 54 publications

(26 citation statements)

References 18 publications

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“…It is an amazing achievement that models like these are now used for the on-line control and automation of entire rolling mills [68][69][70][71].…”

Section: Expression Of Data and Control Algorithmsmentioning

confidence: 99%

Neural Networks and Information in Materials Science

Bhadeshia

2009

Statistical Analysis

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Abstract:Neural networks have pervaded all aspects of materials science resulting in the discovery of new phenomena and have been used in quantitative design and control. At the same time, they have introduced a culture in which both noise and modeling uncertainties are considered in order to realize the value of empirical modeling. This review deals with all of these aspects using concrete examples to highlight the progress made, whilst at the same time emphasizing the limitations of the method. 

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“…It is an amazing achievement that models like these are now used for the on-line control and automation of entire rolling mills [68][69][70][71].…”

Section: Expression Of Data and Control Algorithmsmentioning

confidence: 99%

Neural Networks and Information in Materials Science

Bhadeshia

2009

Statistical Analysis

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“…However, the credibility and successful application of neural network must be based on the accuracy and amount of measured learning data, method and a good understanding process [8].…”

Section: Introductionmentioning

confidence: 99%

A NR–BFGS method for fast rigid-plastic FEM in strip rolling

Mei

2012

Finite Elements in Analysis and Design

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“…Considering the cold rolling process, the requirements to enhance the quality of the products are typically thickness and shape. The extensive literature shows several strategies to reach these objectives, inclusive through non-conventional techniques as neural networks (Larkiola et al, 1996;Larkiola et al, 1998;Yang et al, 2004a), fuzzy logic (Jung et al, 1995;Zhu et al, 2003) and genetic programming (Son et al, 2004). The only condition for the new strategies is to represent correctly the behavior of the process in a quantitative and qualitative form, for different operation points, so that these can be used in the design of on-line control and supervision systems.…”

Section: Introductionmentioning

confidence: 99%