The phrase "approximation in terms of" is correct and usable in written English.
It can be used when discussing a method of expressing or estimating a value or concept using specific variables or parameters.
Example: "The approximation in terms of the variable x allows us to simplify the equation for easier analysis."
Alternatives: "estimate based on" or "approximation regarding".
The analytical approach uses an explicit formulation of the singular approximation in terms of texture coefficients and is valid for arbitrary sample symmetries.
Its dimension affects significantly the accuracy of the approximation, in terms of the relevant properties of the continuous random process under investigation.
This GO equivalency is finally used to define a global operator spheroidal approximation in terms of best matching GO for any such coaxial cylinder pattern.
The selection of support points for generating the response surface is also addressed, and a novel measure is finally introduced for evaluating the efficiency of the response surface approximation in terms of the stochastic sampling accuracy.
For cases when such a spheroidal approximation would remain needed, we propose and compare an "operator spheroidal approximation" in terms of best matching GO, which is exactly operator-identical for dielectric-like properties and nearly identical for elastic-like ones.
The method is validated using a numerical example which compares proposed with exact ones and with those determined from the linear first order approximation in terms of the damping matrix.
This approximation has been extensively done in the literature, in Fig. 3, we verify the impact of this approximation in term of energy inaccuracy before to push further our description.
Easy to compute approximations, in terms of the upper bounds for the expected rain-flow fatigue damage, have been developed.
Statistical analysis of the approximations in terms of mean relative error, maximum positive relative error, maximum negative relative error and correlation quotient are presented.
We report experimental evaluations of the efficiency and effectiveness of the proposed incremental algorithms for constructing probabilistic rough set approximations in terms of the size of data and updating ratio by comparing with a non-incremental algorithm.
