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A lack of these presumptions may force modelers to choose linear over non-linear models to minimize the number of parameters to estimate and reduce the search space.
The study presents several mathematical programming models to minimize the cost or maximize the profit.
The algorithm behind EBK generates several semivariogram models to minimize the prediction error generated from the uncertainty of model parameters.
Both logistic regression and Bayesian models (to minimize type-1 errors) were used, adjusted for potential confounders.
For static traffic model, we formulate integer programming models to minimize the total power consumption in the network.
In order to improve the subjective video quality in the process of encode, they create three visual distortion sensitivity models to minimize the perceptual distortion.
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In Model Formulation section, the mathematical model to minimize the total annual inventory cost is established.
So a model to minimize the maximum eigenvalue is built in Section 4.
Gokcen and Erel (1998) demonstrated basic assembly line balancing model to minimize number of stations.
Chen and Fan (2012) developed a two-stage stochastic programming model to minimize the system cost.
Furthermore, a non-convex optimization model to minimize input energy consumption is proposed.
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