… The objective function of crisp clustering [17, 18], and the objective function of fuzzy clustering
are used to do a simple affine arithmetic, where the parameter θ is a variable to control the …

This paper presents a review of the literature concerning temperature dependency in the
system-level analysis of overhead transmission systems. Traditional power flow and state …

… Popular implementations include the simple, yet blind and often inaccurate interval analysis
(IA), as well as the affine arithmetic, which provides a linear parametric approximation [11]. A …

… In category (C3), [9] and [10] use an interval-based approach (interval arithmetic or affine
arithmetic) to propagate errors. The interval-based approach uses pre-characterized libraries …

… introduced by Nikolaev and Iba [3] that considers the use of transfer polynomials combined
with a recursive least squares algorithm, the robust symbolic regression with affine arithmetic …

… Affine arithmetic (AA) is utilized in Ref. [45] to model the interval uncertainties and
sensitivities in nodal power injections. Pourghasem et al. …

… A novel quantization error estimation based on affine arithmetic (AA) is presented, as well
as its practical application to the automatic WLA of LTI and non-linear differentiable DSP …

This paper presents a mixed perturbation Monte-Carlo method for static and reliability analysis
of structural systems with a mixture of random and interval parameters/loadings. Using a …

… The proposal also suggests an understanding of the mathematical content of interconnected
way, such as: simple interest with affine arithmetic progression and function, compound …

… Affine arithmetic further tracks the sources of errors as affine forms for better precision. It … ,
affine arithmetic also tracks the correlations between sources. Hence, affine arithmetic yields a …