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The problem is formulated as a model of mixed integer nonlinear programming.
Subsequently, we present a data-driven approach to model individual objects, which is particularly formulated as a model instance recognition problem.
The synthesis problem of fault detection and isolation (FDI) filters can be formulated as a model matching problem and solved using an H∞-norm optimization approach.
It is shown that such design task can be formulated as a model predictive control (MPC) problem, where the solution takes a form of a look-up table.
The concept of the epidemiological transition was formulated as a model for integrating epidemiology with demographic changes in human populations (1, 2, 27).
In this work, we show how the task of identifying age-dependent gene expression patterns from ageing microarray datasets can be formulated as a model selection problem and solved accordingly.
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The problem of devising strategies for improving chillers' efficiency is here formulated as a model-based optimisation and it is solved by means of an ad hoc hybrid algorithm which combines a deterministic method and stochastic one.
The problem of input-output linearization in continuous time is formulated as a model-predictive control problem, for processes with full-state measurements and for processes with incomplete state measurements and deadtimes.
Later, the problem was formulated as a simulation model and a comparative analysis was performed on these models.
This is simply the F-S model formulated as a loglinear model, which provides initial parameter estimates for the next model.
The DEA model was initially formulated as a deterministic model, but there have been numerous developments that take into account uncertainty including chance-constrained (CC) DEA, imprecise DEA (IDEA), Monte Carlo simulation and bootstrapping.
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