In this paper, we use the parametric form of fuzzy numbers, and aniterative approach for obtaining approximate solution for a classof fuzzy nonlinear Fredholm integral equations of the second kindis proposed. This paper presents a method based on Newton-Cotesmethods with positive coefficient. Then we obtain approximatesolution of the fuzzy nonlinear integral equations by an iterativeapproach.

Density Estimation: Deals with the problem of estimating probability density functions (PDFs) based on some data sampled from the PDF. May use assumed forms of the distribution, parameterized in some way (parametric statistics); or May avoid making assumptions about the form of the PDF (nonparametric statistics). We are concerned more here with the non-parametric case (see Roger Barlow’s lectur...

This paper proposes a new technique based on double parametric form of fuzzy numbers to handle the uncertain vibration equation for very large membrane for different particular cases. Uncertainties present in the initial condition and the wave velocity of free vibration are modelled through Gaussian convex normalised fuzzy set. Using the single parametric form of fuzzy number, the original fuzz...

in this research optimal reconfiguration strategy of the improved srr reconfigurable mobile robot based on force-angle stability measure has been designed using genetic algorithm. path tracking nonlinear controller which keeps robot’s maximum stability has been designed and simulated in matlab. motion equations of the robot have been derived in parametric form by means of newton- euler, lagrang...

Lambda is an important variable in the Rorschach Comprehensive System. However, because of the way it is calculated it has properties that can produce problems for parametric statistical analyses. We illustrate these difficulties and encourage the use of Form% (i.e., pure form responses/total responses) instead of Lambda in research. Form% is easy to calculate, and it is conceptually and mathem...

Most of the previous research on term weighting for information retrieval has focused on developing specialized parametric term weighting functions. Examples include TF.IDF vector-space formulations, BM25, and language modeling weighting. Each of these term weighting functions takes on a specific parametric form. While these weighting functions have proven to be highly effective, they impose st...

Markov distributions are used to describe multivariate data with conditional independence structure. Applications of Markov distributions arise in many fields including demography, flood prediction, and telecommunications. A hyper Markov law is a distribution over the space of all Markov distributions; such laws have been used as prior distributions for various types of graphical models. Dirich...

Selection models are appropriate when the probability that a potential datum enters the sample is a nondecreasing function of the numeric value of the datum. It is rarely justiiable to model this function, called the weight function, with a speciic parametric form, but is appealing to model with a nonparametric prior centered around a parametric form. The Bayesian analysis with Dirichlet proces...