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- W2147201468 abstract "A decision support system using artificial neural networks is implemented with real world data of a glass furnace process at Samsung. It provides the functions such as process model identification, set-point control and interpreting input factors. Since a glass furnace process is highly complex, a traditional attempt to develop a model from first principles often proves to be a difficult and costly procedure. However, the decision support system using artificial neural networks does not require a priori knowledge of a glass furnace process and proves to be useful in identifying the model directly by input/output data collected from the plant. This paper shows the method of finding the partial derivative value at some point from trained weights, the conversion method of a 3-layered perceptron network into a 2-layered one, and the interpretation method of neural networks solutions." @default.
- W2147201468 created "2016-06-24" @default.
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- W2147201468 date "2005-08-24" @default.
- W2147201468 modified "2023-09-27" @default.
- W2147201468 title "A decision support system using neural networks in a glass furnace process" @default.
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- W2147201468 doi "https://doi.org/10.1109/ijcnn.1993.714304" @default.
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