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Statistically significant variables that were not highly correlated were selected for multivariate Cox proportional hazard regression to maximize model log-likelihood.
The proposed identification methods are designed to especially exploit expert knowledge to maximize model quality under the present system and measurement limitations (loss of contact, limited excitation bandwidth).
These issues necessitate the development of strategies to maximize model compatibility across operating systems, to ensure numerically accurate simulations for alternative compiler selections, and to understand how these choices affect computational speed.
A novel model selection strategy known as "ADDRESS" (A Distance Decay REgression Selection Strategy) was used to select optimized buffer distances for potential predictor variables and maximize model performance.
To maximize model quality, only species with greater than 30 point locations were used [38].
The specific combination of queries used was chosen to maximize model fit.
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ANTEO+ was, however, specifically built for the forced convection regime, trying to maximize modeling efficiency inside that regime; to make it applicable also for these SMRs concepts, its validity domain has been extended to the mixed convection regime.
The simulation of the hypothetical models is embedded in a nonlinear optimization problem to determine an optimal input sequence that maximizes model dissimilarity.
This investigation presents a net revenue maximizing model that can assist network designers in the design and configuration of a cellular system.
Given the high level of uncertainty, we build a stochastic, profit maximizing model to simultaneously determine the optimal network design and the optimal service delivery strategy for a multi-product, multi-level network for repairable service parts.
Use of the utility maximizing model illustrates the difficulties of changing patients' behavior now for the benefit of future health.
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