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Title: Designing neural networks for manufacturing process control systems
Authors: Messom, Christopher H.
Hinde, Chris J.
West, Andrew A.
Williams, David J.
Keywords: Learning (artificial intelligence)
Neural nets
Process computer control
Issue Date: 1992
Publisher: © IEEE
Citation: MESSOM, C.H. ... et al, 1992. Designing neural networks for manufacturing process control systems. IN: Proceedings of the IEEE International Symposium on Intelligent Control, 11-13 Aug, pp. 423-429
Abstract: The design of neural networks for the control of discrete manufacturing processes is addressed. Rather than treating the networks as adaptive black boxes, an architecture that links the weights associated with the nodes and thus allows the relationships and internal structure to be tightly constrained is introduced. The constrained search space gives greater confidence in the internal representations that have been induced by the training set and therefore about the correct behavior of the network between the given limits. The method is illustrated by applying it to the dispensing of adhesives
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ISIC.1992.225128
URI: https://dspace.lboro.ac.uk/2134/4121
ISBN: 0780305469
Appears in Collections:Conference Papers and Presentations (Computer Science)

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