Global optimisation algorithms can then be used to find model parameter values that minimise the value of E T, i.e. minimise the difference between the model outputs and the data.
It was most convenient to minimise the values of relative deviations, i.e. those which consider also the values of estimated parameters as expressed for example in percent.
In life-cycle costing analyses, optimal design is usually achieved by minimising the expected value of the discounted costs.
The robustness of the objective function is achieved by minimising the maximum value of unsatisfactory degree functions of the uncertainty parameters while the feasibility robustness is ensured by an optimisation conducting the worst-case analysis at a lower level.
Minimising the absolute value of the sum of the partial autocorrelation function was used to assess the appropriateness of the degree of smoothing.
The subset that minimised the Akaike Information Criterion value was selected as the model ultimately used for fitting.
In that meta-analysis sensitivity and specificity estimates for the detection of polyps of all sizes combined were 75%and96%6%, but the presence of significant heterogeneity between the different studies minimised the statistical value of these outcomes.
The problem of minimising the number of distinct values among a set of variables subject to difference constraints occurs in many real-life contexts.
