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Two main parts are included in this method: the linear clustering preprocessing part and the optimal ARIMA modelling and forecasting part.
We use an analytical and systematic method, the linear noise approximation of the chemical master equation along with the decoupling of a stoichiometric matrix.
The computational method, the Linear Matching Method (LMM), is used throughout the analysis for the direct evaluation of shakedown, alternating plasticity and ratcheting behaviors.
Using the method, the linear motor with finite mover can be designed more accurately considering the flux leakage at both end of the mover.
To validate the proposed method, the linear correlations of k 3 estimates were evaluated between 40-min 3P++ and 3P + analyses, as well as between 3P++ and 90-min 4P analyses in clinical PET studies.
In this method, the linear combination of the value forecasted by individual models is considered the output of a hybrid model and the desired weight of each component is calculated using different weighting approaches.
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An effective way to solve this problem is to apply some mathematical curve smoothing methods such as the data average method and the linear iterative method.
Regarding to the 2D methods, the linear correlation and the symmetrical uncertainty showed the highest values of relevance for the lower frequency bands.
Concerning the drag force, two novel methods, the linear and the hyperbolic blending method, respectively, are presented to obtain accurate results.
The convergent exponential θ-method, namely the linear θ-method and the one-leg θ-method in an exponential form, is constructed.
Using two θ-methods, namely the linear θ-method and the one-leg θ-method, several conditions, under which the numerical solutions oscillate, are obtained.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com