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Piecewise linear functions with slope 1 satisfy this requirement, but these in turn are not continuous. This motivates our following proposal of using the family of continuous piecewise linear calibration maps, with unconstrained slopes. Table 1 A selection of fit-on-test estimators of calibration ...
Stoica, Prentice-Hall International Series in Systems and Control Engineering (1989), and Numerical Methods for Unconstrained Optimization and Non-linear Equations, J. E. J. Dennis and R. B. Schnabel, Prentice-Hall (1983). The resulting model may be tested by using the same input ...
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DESCRIPTION This module provides functions for building a number of test systems of varying complexity, useful for testing both OpenMM and various codes based on pyopenmm. Note that the PYOPENMM_SOURCE_DIR must be set to point to where the PyOpenMM package is unpacked. EXAMPLES Create...
DESCRIPTION This module provides functions for building a number of test systems of varying complexity, useful for testing both OpenMM and various codes based on pyopenmm. Note that the PYOPENMM_SOURCE_DIR must be set to point to where the PyOpenMM package is unpacked. EXAMPLES ...
DESCRIPTION This module provides functions for building a number of test systems of varying complexity, useful for testing both OpenMM and various codes based on pyopenmm. Note that the PYOPENMM_SOURCE_DIR must be set to point to where the PyOpenMM package is unpacked. EXAMPLES Cr...
Therefore, the objective function of the VBISI method is changed from a constrained objective function to an unconstrained objective function using a penalty function. The penalty function sets the value of the objective function to infinity if the parameters do not satisfy the following conditions. ...
However, more sophisticated methods could be employed for refinement concerning the selection of tuning parameters and kernel functions, although they do not necessarily guarantee a better performance, possibly due to over-fitting; see Remark 2 of Lee, Lee and Moon [38]. Furthermore, in this ...
PSO algorithm is based on groups, and solves an unconstrained D-dimensional optimization problem by minimization of the objective or the fitness function [30,31,32]. In this study, the fitness function is the evaluation factor Ipq (Equation (11)). In PSO algorithm, each particle keeps track ...