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In Section 'Method', we present our method and provide the mathematical framework of our study.
To show the feasibility of our approach, we use an implementation of the CQC method and provide some experimental results.
We conclude with a discussion of the value of the Delphi method and provide insight into its limitations.
We discuss the relevant details of the numerical method and provide results of the code's performance on standard test problems.
ROMP [20, 26] and compressed sensing matching pursuit (CoSaMP) [24, 26] have the stability guarantee as the ℓ1-minimization method and provide the speed as greedy algorithm.
Automated QSAR modeling workflow follows a RF based feature selection method and provide ranked order of variables without eliminating any variable.
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LMA is basically considered as a Newton type method and provides a rather quadratic convergence.
The research enriches the matrix method and provides concise analytical compliance models for the serial compliant mechanism.
GMJ and JRM developed the method and provided analysis tools.
HB and GF developed the method and provided technical details.
NJS provided assistance on designing the whole genome capture method and provided sequencing capacity for field samples.
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