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• W54843639 abstract "This paper describes hybrid multivariate method: Principal Component Analysis improved by Genetic Algorithm. This method determines main Principal Components can be used to detect fault during the operation of industrial process by neural classifier. This technique is applied to simulated data collected from the Tennessee Eastman chemical plant simulator which was designed to simulate a wide variety of faults occurring in a chemical plant based on a facility at Eastman chemical." @default.
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• W54843639 date "2010-01-01" @default.
• W54843639 modified "2023-10-16" @default.
• W54843639 title "Fault Detection of the Tennessee Eastman Process Using Improved PCA and Neural Classifier" @default.
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• W54843639 doi "https://doi.org/10.1007/978-3-642-11282-9_5" @default.
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