In this paper, we deal with a new family of iterative methods for approximating the solution nonlinear systems non-differentiable operators. The novelty is that it m-step generalization Steffensen-type method by updating divided difference operator in first two steps but not following ones. This procedure allows us to increase both order convergence and efficiency index respect obtained updates...

• A comparison between ten methods for computing the T 2 distribution was performed. Various regularization techniques and penalty functions were tested. Our findings demonstrated need regularization. list of recommendations selecting optimal algorithms provided. The implemented packaged in a freely distributed toolbox. Multi-component relaxometry allows probing tissue microstructure by assessi...

normal 0 false false false en-us x-none fa microsoftinternetexplorer4 aim : for the purpose of cost modeling, the semi-parametric single-index two-part model was utilized in the paper. furthermore, as functional gastrointestinal diseases which are well-known as common causes of illness among the society people in terms of both the number of patients and prevalence in a specific time interval, t...

weather data generators (wgs) have been developed for an extension of time series of such weather variables as rainfall, temperature and relative humidity to provide better understanding of systems affected by climatic factors. different algorithms have been applied in these generators, broadly divided into parametric & non-parametric ones. in this study, the performance of non-parametric gener...

The research works presented concern the study of parameterized verificationmethods for real time systems. The aim is to propose formal methods that can be appliedon systems whose specifications are not yet completely defined. To that end, parameters areintroduced into the formal models in order to add some degrees of freedom. The goal is thento guide the conception of the syste...

Abstract We introduce novel adaptive methods to approximate moments of solutions partial differential Equations (PDEs) with uncertain parametric inputs. A typical problem in Uncertainty Quantification is the approximation expected values quantities interest solution, which requires efficient numerical high-dimensional integrals. perform this task by a class deterministic quasi-Monte Carlo integ...