Algorithm of a knowledge extraction from neural network on the example of hot-dip zinc coating process

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Algorithm of a knowledge extraction from neural network on the example of hot-dip zinc coating process

Sławomir Golak, Franciszek Grosman, Tadeusz Wieczorek

Politechnika Śląska.

DOI:

https://doi.org/10.7494/cmms.2003.2.0037

Abstract:

One of the major disadvantages of neural networks is that they can be considered as black boxes, since no satisfactory explanation of their work. A method for the analysis of regression neural networks, which provides physical interpretation of examined processes, is described in the paper. Method was verified on a base of test and empirical data of hot-dip zinc coating process.

Cite as:

Golak, S., Grosman, F., Wieczorek, T. (2003). Algorithm of a knowledge extraction from neural network on the example of hot-dip zinc coating process. Computer Methods in Materials Science, 3(2), 72 – 78. https://doi.org/10.7494/cmms.2003.2.0037

Article (PDF):

Keywords:

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