Statistical analysis of nonlinear processes based on penalty factor (Q1719451)
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scientific article; zbMATH DE number 7017679
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Statistical analysis of nonlinear processes based on penalty factor |
scientific article; zbMATH DE number 7017679 |
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Statistical analysis of nonlinear processes based on penalty factor (English)
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8 February 2019
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Summary: A new process monitoring approach is proposed for handling the nonlinear monitoring problem in the electrofused magnesia furnace (EFMF). Compared to conventional method, the contributions are as follows: (1) a new kernel principal component analysis is proposed based on loss function in the feature space; (2) the model of kernel principal component analysis based on forgetting factor is updated; (3) a new iterative kernel principal component analysis algorithm is proposed based on penalty factor.
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