The influence of different methods of curved boundary approximation on the quality of solution is investigated; practical evaluation of accuracy is performed.
Compared with other QLFs, such as step-loss and piecewise linear loss functions, the quadratic QLF may be a good approximation of measuring the quality of a product, particularly over the range of characteristic values in the neighborhood of the target value.
The net-to-gross ratio provides an approximation of the reservoir quality and might be an indicator of the productive geobodies' connectivity.
Figure 10 Bit rates allocated to the users in Figure 9 by the proposed algorithm described in Algorithm 2. As discussed in Section 4.1, we consider the concave approximation of the service quality.
By plugging Z ^ x 1, x 2 which is the cumulative ζ ^ x 1, x 2 into (6), the concave approximation of the service quality can be obtained by Y ^ s, x = ∑ i = 1 N s − 1 β s, i − β s, i + 1 Z ^ x, X s, i + β s, N s Z ^ x, X s, N s (8) Figure 5 Bit value according to the step function (4) and the approximation function (7).
The method is derived from the hypothesis that the HVS is highly adapted for extracting the structural information from the visual scene, and therefore, a measurement of structural similarity can provide a good approximation of the perceived image quality.
Since a model is always an approximation of the real world, the quality of implemented data is important to achieve reliable results.
Previous researches focus on good kernel approximation while the quality of eigenvector approximation is rarely explored.
Because this last method used indices of abundance, not just presence or absence, the method may give a better approximation of habitat quality than do the other methods.
With the increase of P, the errors from piecewise linear approximation decrease because the quality of piecewise linear representation increase.
