This requires a computationally intensive framework for determining the relevance of each data set by solving an optimization problem.
6, 7 Another mathematical solution are multivariate methods, which are based on least-square minimization of the global diffusion coefficient data set, followed by an optimization of the amplitudes of different components.
More likely, these values will be set by automatic optimization methods when high throughput data is used to refine models that are initially built manually by experts.
The label problem is then set as an optimization problem by minimizing the energy function E ( α, k, θ, z ) = U ( α, k, θ, z ) + V ( α, z ) (2).
By setting an optimization target, selecting a set of sub mappings with diverse-shaped EXIT curves and then optimizing their percentages, irregular mapping with maximum extrinsic mutual information after a target number of iterations is derived.
Given a loss function l and a penalty function Ω, large-margin classifiers can then be trained on a given training set by solving the following constrained optimization problem: (2) where μ is a parameter that controls the trade-off between fitting the data, i.e. minimizing R emp (f), and monitoring the regularity of the classifier, i.e. monitoring Ω(w).
Lunter et al. [ 3] demonstrated systematic biases caused by the optimization criteria set by the Needleman-Wunsch approach.
The optimization problem is set by taking into consideration three different possible objective functions (OFs): the maximum of the peak structural displacement standard deviation, the average hysteretic dissipated energy of a protected building with reference to an unprotected one, and a functional damage that considers the two indexes previously described.
The problem is set up as optimization problems solved by a genetic algorithm while the required multiphysics simulation is performed by finite element analysis.
In Figure 3, the intervention sets (U for the up-regulation set) identified by each optimization method are shown above their corresponding optimal target flux values.
