As the area covered by C3 and population were difficult to estimate, the utilization index cannot be computed.
Although the substitution model derivatives can be computed analytically in the homogeneous case as well as in Galtier and Gouy's model, they are difficult to compute analytically in the more general case, and are consequently computed numerically in Bio++.
Since it is difficult to compute the fill-in rate at the circuit device level, we analyze the fill-in rate of the coupling system in a second step after the device grouping, once the fill-in entries in (A_{c,c}^{(i)}), (i=1,ldots,p) can be computed.
As analytical derivatives are difficult to compute for the covarion parameters, numerical derivatives are computed for all three covarion switching parameters.
However, when dealing with complex geometries and difficult physical phenomena to be modeled, computing costs still remain high, due to the large number of required numerical simulations feeding the traditional surrogate models.
While position and trees are tightly connected, distance is difficult to compute and it is not clear that there is any exploitable structure.
Since the matrix exponential function (e_{A t)}(t_{1},t_{0})) on time scale can be difficult to compute, it can be estimated by a real exponential one.
In the previous study in [9], it has also been argued that the maximum position error (when distance estimation errors are positive) is difficult to compute because the problem is formulated as a nonconvex problem; however, by means of a relaxation technique, an upper bound on the position error can be obtained efficiently [9].
Above we present a relatively simple joint indicator, RTB/HIV (1), which is not difficult to compute and is easily understood.
