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The information extracted from the registered spectra was treated and then modeled following two different chemometric approaches: a linear one based on multiple linear regression models, and a non-linear one based on the employment of artificial neural networks.
Empirical models were formulated based on multiple linear models.
Different model structures and parameters were determined based on multiple linear regression and principal component regression.
Relationships between urban characteristics and the computed inundation water depths have been based on multiple linear regressions.
However, the mixture toxicities were effectively predicted by the integrated CA with IA based on multiple linear regression model (ICIM).
In addition, models that can effectively predict LST distribution were developed based on multiple linear regression method (MLRM) and the partial least squares regression method (PLSRM).
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NIR models were developed based on multiple-linear regression (MLR) and partial least square (PLS) regression employing preprocessing technologies (baseline correction, smoothening, multiplicative scatter correction (MSC) and second order derivatisation).
This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques.
We study the control of a solution copolymerization reactor using a model predictive control algorithm based on multiple piecewise linear models.
The selected tool for analysis and design of stabilizing controllers is based on multiple Lyapunov functions and linear matrix inequalities.
MPCA establishes multiple dimensions based on multiple factors and then computes multiple linear subspaces representing multiple varying factors.
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