Abstract
In order to meet the demand of online optimal running, a novel soft sensor modeling approach based on Gaussian processes was proposed. The approach is moderately simple to implement and use without loss of performance. It is trained by optimizing the hyperparameters using the scaled conjugate gradient algorithm with the squared exponential covariance function employed. Experimental simulations show that the soft sensor modeling approach has the advantage via a real-world example in a refinery. Meanwhile, the method opens new possibilities for application of kernel methods to potential fields.
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References
Martin G. Consider soft sensors[J]. Chemical Engineering Progress, 1997, 66(7): 66–70.
MacKay D J C. Introduction to Gaussian processes[R]. Cambridge: Cambridge University, 1998.
Seeger M. Gaussian processes for machine learning[R]. Berkeley: University of California at Berkeley, 2004.
Rasmussen C E. Gaussian processes in machine learning[A]. Bousquet O, von Luxburg U, Ratsch G. Advanced Lectures on Machine Learning [C], Heidelberg: Springer-Verlag, 2004. 63–71.
Williams C K I, Rasmussen C E. Gaussian processes for regression[A]. Touretzky D C, Mozer M C, Hasselmo M E. Advances in Neural Information Processing Systems 8[C]. Cambridge: MIT Press, 1997.
Neal R M. Bayesian learning for neural networks[D]. Toronto: Department of Computer Science, University of Toronto, 1995.
Wahba G. Spline Models for Observational Data[M]. Philadelphia: SIAM, 1990.
Scholkopf B, Smola A J. Learning with Kernels[M]. Cambridge: MIT Press, 2002.
FENG Rui, SHEN Wei, SHAO Hui-he. A soft sensor modeling approach using support vector machines[A]. Proceedings of the 22nd American Control Conference[C]. Piscataway: IEEE, 2003. 3702–3707.
WANG Xu-dong, LUO Rong-fu, SHAO Hui-he. Designing a soft sensor for distillation column with the fuzzy distributed radial basis function neural networks[A]. Proceedings of the 35th IEEE Conference on Decision and Control [C]. New York: IEEE, 1996. 1714–1719.
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Foundation item: Project (2002AA412010, 2004AA412050) supported by the National High Technology Research and Development Program of China
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Xiong, Zh., Huang, Gh. & Shao, Hh. Soft sensor modeling based on Gaussian processes. J Cent. South Univ. Technol. 12, 469–471 (2005). https://doi.org/10.1007/s11771-005-0184-9
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DOI: https://doi.org/10.1007/s11771-005-0184-9