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- W2090755243 abstract "This paper illustrates the implementation of a fuzzy expert system for continuous steel casting diagnostics in an artificial neural network. Developing an expert system is often time consuming even after knowledge acquisition. Artificial neural networks offer an advantageous alternative to coding such knowledge in an expert system shell or writing a program for it. Earlier work illustrated the feasibility of using a feed-forward neural network for knowledge storage and inferencing, like an expert system, for predicting operational problems in continuous steel casting. The inputs to the network were in terms of truth values, information about an incoming ladle of steel, and the output was about its suitability for successful continuous casting, giving an indication on whether problems would be encountered in the beginning and/or at the end of the casting. 66 rules generated by inductive learning from hypothetical cases were put into the productive network consisting of 12 inputs, 82 nodes in the hidden layer and 2 outputs." @default.
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- W2090755243 date "1993-01-01" @default.
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- W2090755243 title "Implementing a fuzzy expert system in an artificial neural network" @default.
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- W2090755243 doi "https://doi.org/10.1016/0098-1354(93)80258-o" @default.
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