نتایج جستجو برای: fuzzy trapezoidal rule

تعداد نتایج: 240301  

Journal: :international journal of industrial mathematics 2016
n. ahmady e. ahmady

fuzzy newton-cotes method for integration of fuzzy functions that was proposed by ahmady in [1]. in this paper we construct error estimate of fuzzy newton-cotes method such as fuzzy trapezoidal rule and fuzzy simpson rule by using taylor's series. the corresponding error terms are proven by two theorems. we prove that the fuzzy trapezoidal rule is accurate for fuzzy polynomial of degree one and...

E. Ahmady N. Ahmady,

Fuzzy Newton-Cotes method for integration of fuzzy functions that was proposed by Ahmady in [1]. In this paper we construct error estimate of fuzzy Newton-Cotes method such as fuzzy Trapezoidal rule and fuzzy Simpson rule by using Taylor's series. The corresponding error terms are proven by two theorems. We prove that the fuzzy Trapezoidal rule is accurate for fuzzy polynomial of degree one and...

2008
M. Barkhordary N. A. Kiani A. R. Bozorgmanesh

In this paper, a numerical method for solving fuzzy Fredholm integral equations of the second kind is introduced. We apply the trapezoidal rule to compute the Riemann integrals.This kind of integral equations convert to a linear system. Then, by solving the linear system , unknowns are determined. Finally, an algorithm is presented to solve the fuzzy integral equation by using the trapezoidal r...

Journal: :iranian journal of fuzzy systems 0
mojtaba ghanbari department of mathematics, aliabad katoul branch, islamic azad university, aliabad katoul, iran

in this paper, a  fuzzy numerical procedure for solving fuzzy linear volterra integro-differential equations of the second kind under strong  generalized differentiability is designed. unlike the existing numerical methods, we do not replace the original fuzzy equation by a $2times 2$ system ofcrisp equations, that is the main difference between our method  and other numerical methods.error ana...

Journal: :Fuzzy Sets and Systems 2011
Lucian C. Coroianu

In this paper, we prove new distance properties between a fuzzy number and its trapezoidal approximation preserving the expected interval. Then, we find the best Lipschitz constant of the trapezoidal approximation operator preserving the expected interval. Finally, we use this result in finding within a reasonable error the trapezoidal approximation of a fuzzy number preserving the expected int...

Journal: :iranian journal of fuzzy systems 2013
masoumeh zeinali sedaghat shahmorad kamal mirnia

this paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. finally an example is given to illustrate the performance of the methods.

This paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. Then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. Finally an example is given to illustrate the performance of the methods.

2013
B. Asady

In this paper, we introduce a method to obtain the nearest trapezoidal approximation of fuzzy numbers so that preserving conditions expect interval and include the core of a fuzzy number.

Journal: :Fuzzy Sets and Systems 2008
Adrian I. Ban

The problem to find the nearest trapezoidal approximation of a fuzzy number with respect to a well-knownmetric, which preserves the expected interval of the fuzzy number, is completely solved. The previously proposed approximation operators are improved so as to always obtain a trapezoidal fuzzy number. Properties of this new trapezoidal approximation operator are studied. © 2007 Elsevier B.V. ...

2015
Shahaf Duenyas Michael Margaliot

Support vector machines (SVMs) proved to be highly efficient computational tools in various classification tasks. However, SVMs are nonlinear classifiers and the knowledge learned by an SVM is encoded in a long list of parameter values, making it difficult to comprehend what the SVM is actually computing. We show that certain types of SVMs are mathematically equivalent to a specific fuzzy–rule ...

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