Soft sensor based on Gaussian process regression and its application in erythromycin fermentation process
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چکیده
منابع مشابه
Soft Sensor Modeling of Product Concentration in Glutamate Fermentation using Gaussian Process Regression
Corresponding Author: Rongjian Zheng Key Laboratory of Advanced Process Control for Light Industry( Ministry of Education), Jiangnan University, Wuxi, China Email: [email protected] Abstract: The on-line control of glutamate fermentation process is difficult, owing to the typical uncertainties of biochemical process and the lack of suitable on-line sensors for primary process variables. A pred...
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In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase a...
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Corresponding Author: Rongjian Zheng Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China E-mail: [email protected] Abstract: Glutamate fermentation is inherently nonlinear, multi-phase and an aerobic fermentation process. As long measurement delays and expensive apparatus cost, on-line measurement of the product concentration ...
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We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while off-diagonal blocks are approximated. Partitioning input data points, we present a two-layer hierarchical model for GP regression, where prototypes of clusters in the upper layer are involved for coarse modeling by a GP...
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We introduce Latent Gaussian Process Regression which is a latent variable extension allowing modelling of non-stationary processes using stationary GP priors. The approach is built on extending the input space of a regression problem with a latent variable that is used to modulate the covariance function over the input space. We show how our approach can be used to model non-stationary process...
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ژورنال
عنوان ژورنال: Chemical Industry and Chemical Engineering Quarterly
سال: 2016
ISSN: 1451-9372,2217-7434
DOI: 10.2298/ciceq150125026m