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- W1982148110 abstract "A novel estimator model, which incorporates DPCA (dynamic principal component analysis), RBF (radial basis function) networks, and MSA (multi-scale analysis), is proposed to infer the properties of manufactured products from real process variables. DPCA is carried out to select the most relevant process features and to eliminate the correlations of input variables; multi-scale analysis is introduced to acquire much more information and to reduce uncertainty in the system; and RBF networks are used to characterize the nonlinearity of the process. A prediction of the syngas compositions in Texaco coal gasification process is taken as a case study. Research results show that the proposed method provides promising prediction reliability and accuracy." @default.
- W1982148110 created "2016-06-24" @default.
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- W1982148110 date "2008-09-01" @default.
- W1982148110 modified "2023-09-25" @default.
- W1982148110 title "Texaco coal gasification quality prediction by neural estimator based on MSA and dynamic PCA" @default.
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- W1982148110 doi "https://doi.org/10.1109/ical.2008.4636353" @default.
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