The aim of the paper is to present a new global optimization method for determining all the optima of the Least Squares Method (LSM) problem of pairwise comparison matrices. Such matrices are used, e.g., in the Analytic Hierarchy Process (AHP). Unlike some other distance minimizing methods, LSM is usually hard to solve because of the corresponding nonlinear and non-convex objective function. It...

Application of least-squares Kirchhoff migration (LSM) to synthetic reverse vertical seismic profile data (RVSP) demonstrates that LSM reduces the migration artifacts, improves the image resolution and produces a more accurate image than the standard migration, but cannot completely recover the model reflectivity for AVO analysis because of the limited data coverage. The influence of incomplete...

This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation. The state transition matrix is updated without the use of any forgetting function. This yields a robust estimation of model parameters in the presence of noise. The computational ...

The straightness and flatness errors are generally assessed by using the Least Squares Method (LSM). However, the results obtained from LSM often overestimate the tolerances, and are not consistent with the ISO standards’ definitions. To this end, this paper presents a method to evaluate those errors by using particle swarm optimization (PSO). The realization technique is detailed. The experime...

Traffic sampling technology has been widely deployed in front of many high-speed network applications to alleviate the great pressure on packet capturing.Increasingly passive traffic measurement employs sampling at the packet level. Packet sampling has become an attractive and scalable means to measure flow data on high-speed links. However, knowing the number and length of the original flows i...

This paper introduces a novel approximation technique that uses Tensor Product Bernstein Polynomials (TPBPs) as base functions. An Evolution Strategy (ES) is proposed for finding suitable control points for TPBPs so that the resulting approximation functions fit given finite samplings of data points very well. Also for more difficult test data sets taken from functions containing discontinuitie...

Oceanographic images obtained from environmental satellites by a wide range of sensors allow characterizing natural phenomena through different physical measurements. For instance Sea Surface Temperature (SST) images, altimetry data and ocean color data can be used for characterizing currents and vortex structures in the ocean. The purpose of this thesis is to derive a relatively complete frame...