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Online measurement of the melt index is typically unavailable in industrial polypropylene production processes, soft sensing models are therefore required for estimation and prediction of this important quality variable. Polymerization is a highly nonlinear process, which usually produces products with multiple quality grades. In the present paper, an effective soft sensor, named Combined Local Gaussian Process Regression (CLGPR), is developed for prediction of the melt index. While thedoi:10.1016/j.conengprac.2011.01.002 fatcat:wwfk54uhm5hczgex6zcv7rj66q