Real-time property prediction for an industrial rubber-mixing process with probabilistic ensemble Gaussian process regression models

Journal of Applied Polymer Science

Volumn 132, Issue 6, 2015, Pages

  Liu, Yi ^a   Gao, Zengliang ^a  

^a ZHEJIANG UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

applications; manufacturing; rubber

Indexed keywords

APPLICATIONS; BAYESIAN NETWORKS; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INFERENCE ENGINES; MANUFACTURE; MATHEMATICAL MODELS; MIXING; REACTOR CORES; REGRESSION ANALYSIS; RUBBER; VISCOSITY;

GAUSSIAN PROCESS REGRESSION; GAUSSIAN PROCESS REGRESSION MODEL; OPERATING CONDITION; PREDICTION ACCURACY; PREDICTION UNCERTAINTY; PROBABILISTIC ENSEMBLE; REAL-TIME PROPERTIES; VISCOSITY PREDICTION;

RUBBER APPLICATIONS;

EID: 84912562670     PISSN: 00218995     EISSN: 10974628     Source Type: Journal    
DOI: 10.1002/app.41432     Document Type: Article

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