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However, the solution of an optimization problem using a cost functional (a function of functions of time) is quite different, and substantially harder to solve, than previous optimization problems using cost functions, which depended simply on two variables (such as substrate and enzyme levels in [ 25]).
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Periodic control theory is used to define a cost functional for LQ-control, that measures the performance of a sampled-data system in relation to a desired continuous time performance.
Although individual graphene nanoribbons have been produced by longitudinal unzipping of carbon nanotubes or patterned growth in large scale, it is still a challenge to construct these unique structures into macroscopic functional architectures using a cost-effective method.
To perform such an optimization, a numerical method to determine the location and extent of defects in piezoelectric plates is developed by combining the solution of an identification inverse problem, using genetic algorithms and gradient-based methods to minimize a cost functional, and using an optimized finite element code and meshing algorithm.
Cost-effectiveness will be analyzed using a cost-utility analysis.
Cost-effectiveness will be measured using a cost-evaluation questionnaire.
The model-based inverse problem is solved by minimizing a cost functional using genetic algorithms.
This task is formulated as a constrained optimization problem with a cost functional of least squares type using information obtained from measurements.
Rather than using a predefined set of forces in the image, variational level set methods seek to produce a level set function that minimises a predefined cost function, more specifically known as energy functional also sometimes called a cost functional.
This paper presents the estimation of a cost function for HIV prevention services using two datasets, using a flexible functional form.
Throughout the task, their brain activity was monitored using a technique called functional magnetic resonance imaging (fMRI).
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