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The multiple prediction orders method can also be utilized to deal with other multi-target learning problems, such as subcellular location prediction [ 37] and functions of proteins [ 20].
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Derivatives reconstruction is used to obtain a second order method.
The result is a uniformly accurate fifth order method.
This paper extends our previous third-order method [S.
While the second order method retained its accuracy, the third order method transformed into a fourth order technique, upon setting the parameter (eta=1).
We compare the proposed higher-order method with the other higher-order methods,,, and that employ higher-order Taylor approximations to the second derivative as shown in [10].
This 2nd order homogenization method is then validated against the 1st order method and finite element analysis.
For example, smart lock maker Lockitron tried to develop its own pre-order method with open source framework Selfstarter, but quit because it was too distracting.
For a fixed parameter (sigma= k/h^{2}), the proposed method behaves like a fourth-order method.
Apparently from the figures, the gradient method and our second order method have the best performance.
Choosing a two-order method to compute (e.g., by scheme (2.2)) and noticing (3.31).
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