Dealing with complexity: an overview of the neural network approach

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Craddock, R. and Warwick, K. (1998) Dealing with complexity: an overview of the neural network approach. In: The UKACC '98 International Conference on Control, 1-4 September 1998, Swansea, UK, pp. 705-708. doi: 10.1049/cp:19980315

Abstract/Summary

The problem of complexity is particularly relevant to the field of control engineering, since many engineering problems are inherently complex. The inherent complexity is such that straightforward computational problem solutions often produce very poor results. Although parallel processing can alleviate the problem to some extent, it is artificial neural networks (in various forms) which have recently proved particularly effective, even in dealing with the causes of the problem itself. This paper presents an overview of the current neural network research being undertaken. Such research aims to solve the complex problems found in many areas of science and engineering today.

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Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/21626
Identification Number/DOI 10.1049/cp:19980315
Refereed Yes
Divisions Science
Uncontrolled Keywords complex systems, control engineering, inherent complexity, neural network
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