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Uncertainty quantification plays a significant role in establishing reliability of mathematical models, while applying to process optimization or technology feasibility studies.
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Therefore, MVU cannot be applied to process monitoring directly.
A central composite design was applied to process optimization.
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This model can be also applied to process design evaluation for complicated machining processes.
A novel hazard identification methodology applied to process systems is presented in this paper.
The proposed algorithm is applied to process the ESESM (Experimental Scientific-Education Micro-Satellite) flight data.
The MSKPCA based on SFM (SFM-MSKPCA) algorithm is first proposed and applied to process monitoring.
Artificial neural networks were applied to process data from on-site LIBS analysis of soil samples.
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