Sensitivity coefficients for matrix-based LCA

A matrix method for estimating linear regression coefficients based on fuzzy numbers

In this paper, a new method for estimating the linear regression coefficients approximation is presented based on Z-numbers. In this model, observations are real numbers, regression coefficients and dependent variables (y) have values ​​for Z-numbers. To estimate the coefficients of this model, we first convert the linear regression model based on Z-numbers into two fuzzy linear regression mode...

The use of matrix perturbation theory for addressing sensitivity and uncertainty issues in LCA

LCA, even when modeled in the traditional way with linear equations, may show strong non-linear sensitivities. Well-developed tools from matrix perturbation theory may be employed to investigate LCA systems for the presence and location of such extreme sensitivities. This knowledge is useful for stability analysis, error analysis and for detecting and resolving round-off problems in the computa...

Differential Equation of Sensitivity Matrix for Final Velocity Constraint

Bounds for Matrix Coefficients and Arithmetic Applications

— We explain an important result of Hee Oh [16] on bounding matrix coefficients of semi-simple groups and survey some applications.

Heat Transfer Coefficients Investigation for TiO2 Based Nanofluids

From a regression analysis perspective, this paper focused on literature about TiO2 nano particles. The particles on focus entailed those that had been suspended in ethylene glycol and water – at a ratio of 60:40. Indeed, regression analysis has gained application in contexts such as the turbulent Reynolds number, especially with the aim of establishing the impact of the ratio of the...