For this research, our main purpose is to obtain a better understanding of the Earths tectonic processes in the Texas region, which requires us to analyze the Earth structure. We expand on a constrained optimization approach for a joint inversion least-squares (LSQ) algorithm to characterize a one-dimensional Earth’s structure of Texas with the use of multiple geophysical data sets. We employed...

in this paper, we propose the least-squares method for computing the positive solution of a m  n fully fuzzy linear system (ffls) of equations, where m > n, based on kaman's arithmetic operations on fuzzy numbers that introduced in [18]. first, we consider all elements of coecient matrix are non-negative or non-positive. also, we obtain 1-cut of the fuzzy number vector solution of the n...

we present a methodology for characterization and an approach for computing the solutions of fuzzy linear systems with lr fuzzy variables. as solutions, notions of exact and approximate solutions are considered. we transform the fuzzy linear system into a corresponding linear crisp system and a constrained least squares problem. if the corresponding crisp system is incompatible, then the fuzzy ...

The Cubed Sphere grid is an important tool to approximate functions or data on the sphere. We introduce approximation framework this based least squares and a suitably chosen subspace of spherical harmonics. main claim that for equiangular with step size π/(2N), relevant harmonics one all SH degree less than 2N. This choice, which matches Nyquist’s cutoff frequency along equatorial great circle...