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Dynamic recurrent neural networks for a hybrid intelligent decision support system for the metallurgical industry (1999)

Ming Zhou, Shang ; Xu, Li D

Oxford, UK and Boston, USA : Blackwell Publishers Ltd

Expert systems 16 (1999), S. 0

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ISSN: 1468-0394

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Computer Science

Notes: Knowledge-based modeling and implementation of the various manufacturing processes represent an intensive research area. It is known that it is difficult to analyze the mechanisms of many industrial production processes and build dynamic models by employing classical methods for intelligent systems in manufacturing. This paper describes how to use dynamic recurrent neural networks to provide the model base of a hybrid intelligent system for the metallurgical industry with a quality control model. The hybrid system extracts the features of image sequences obtained through the vision detection subsystem and employs a dynamic recurrent neural network to assess and predict the product qualities to further coordinate the entire production process.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/1468-0394.00115

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