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The acceptance constant that satisfies producer and consumer risk is obtained by minimizing the generalized asymptotic variance of the test statistics.
New designs, with the further property of minimizing the generalized variance of the additional regression coefficients when an enlarged model is fitted, are derived and assessed.
This paper presents an AIS approach applied to optimize the design of an incremental discrete VSC for minimizing the generalized minimum variance strategy.
Simulations are completed to illustrate the validity of the novel approach by illustrating that a controller minimizing the generalized orthogonal functions will achieve the maximum possible attenuation of the global error.
An optimization process is developed in which added lumped masses on the structure are used as design variables to move the node to a preselected location for example to where a low response amplitude is required or to a point which makes the mode shape nearly orthogonal to the force distribution, thereby minimizing the generalized force.
Model selection for the other confounders was carried out by minimizing the Generalized Cross Validation (GCV) criterion.
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The objective is to minimize the generalized compliance within allowable material volume.
The considered objectives jointly minimize the generalized expectation of the total transportation costs and the maximum travel time requirement in terms of generalized value-at-risk (VaR).
A comparison with an optimization formulation that directly minimizes the generalized force indicates that nodal placement gives essentially a minimum generalized force when the node is appropriately placed.
Such methods minimize the generalized asymptotic variance of the maximum likelihood estimators of the model parameters or that of a quantile lifetime.
To this end, continuum approximation models are used to design idealized transit systems that minimize the generalized costs to both the users and the operators of those systems.
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