a meshless method namely, discrete least square method (dlsm), is presented in the paper for the solution of free surface seepage problem. in this method computational domain is discredited by some nodes and then the set of simultaneous equations are built using moving least square (mls) shape functions and least square technique. the proposed method does not need any background mesh therefore ...

Both migration deconvolution (MD) and least squares migration (LSM) are capable of improving the resolution and suppress acquisition footprints in migrated images. In this report, I investigate the relative performance of these two methods in enhancing migration image quality, suppressing artifacts and computational efficiency. Both MD and LSM were implemented on synthetic data generated from p...

Least squares migration (LSM) is a linearized waveform inversion for estimating a subsurface reflectivity model that, relative to conventional migration, offers improved spatial resolution of migration images. The cost, however, is that LSM typically requires 10 or more iterations, which is about 20 times or more the CPU cost of conventional migration. To alleviate this expense, I present a deb...

In a recent paper Longstaff & Schwartz (2001) suggest a method to American option valuation based on simulation. The method is termed the Least Squares Monte-Carlo (LSM) method, and although it has become widely used not much is known about the properties of the estimator. This paper corrects this shortcoming using theory from the literature on seminonparametric series estimators. A central par...

Least squares migration (LSM) is applied to synthetic data with the purpose of removing the ”acquisition footprint” noise from migrated sections. Results for simple point scatterer and meandering stream channel models suggest that LSM can significantly attenuate the acquisition footprint noise. For comparison, the corresponding Kirchhoff migrated sections show noticeable artifacts due to a coar...

The titrimetric method is used for on-site measurement of the concentration of volatile fatty acids (VFAs) in anaerobic treatment. In current practice, specific and interpolated pH-volume data points are used to obtain the concentration of VFA by solving simultaneous equations iteratively to convergence (denoted as SEq). Here, the least squares method (LSM) is introduced as an elegant alternati...

In this paper, we illustrate how to value American-style options using the Least-Squares Monte Carlo (LSM) approach proposed by Longstaff and Schwartz (2001) and investigate whether there exists an optimal regression complexity in the LSM framework for options pricing. In particular, we use the smoothing spline in the regression step, which allows us to control the regression complexity on a co...

In this study, the momentum and energy equations of laminar flow of a non-Newtonian fluid are solved in an axisymmetric porous channel using the least square and Galerkin methods. The bottom plate is heated by an external hot gas, and a coolant fluid is injected into the channel from the upper plate. The arising nonlinear coupled partial differential equations are reduced to a set of coupled no...

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...