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Different modeling schemes, namely ARX models as linear approach, and adaptive-network-based fuzzy inference system (ANFIS) as intelligent modeling approach have been evaluated.
Common methods of studying extreme events, such as the statistical approach, the empirical-physical approach or the numerical modeling approach, have some limitations, and study of them has been largely empirical.
Recently, economic evaluation studies using a modeling approach have reported that many of the new vaccines would substantially reduce disease-specific mortality and provide good value for money in low- to middle-income country settings [ 6- 9].
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The conventional modeling approach has been the Kronecker model [23 25] which separates spatial correlation at the transmitter and receiver ends.
While these existing metabolic modeling approaches mainly focus on the influence of metabolic genes on biofilm formation, no modeling approach has been published to quantify the microbial biofilm formation upon the change in the environmental nutrient conditions; however, the availability of environmental nutrients has been shown to influence microbial biofilm formation.
The modeling approach has been applied to the Sydney dilute reacting sprays.
A numerical modeling approach has been developed for predicting temperatures in municipal solid waste landfills.
This object-role modeling approach has been used productively in industry for over 25 years.
Until now, such a biology-based modeling approach has not been used within the regulatory context.
It turned out that this modeling approach has value, but requires very careful consideration of the input data.
In this paper, an improved modeling approach has been developed and validated for GaN high electron mobility transistors (HEMTs).
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