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5: Paper Source PDF document

Paper's Title:

Credibility Based Fuzzy Entropy Measure

Author(s):

G. Yari, M. Rahimi, B. Moomivand and P. Kumar

Department of Mathematics,
Iran University of Science and Technology,
Tehran,
Iran.
E-mail: Yari@iust.ac.ir
E-mail: Mt_Rahimi@iust.ac.ir
URL: http://www.iust.ac.ir/find.php?item=30.11101.20484.en
URL: http://webpages.iust.ac.ir/mt_rahimi/en.html

Qarzol-hasaneh
Mehr Iran Bank, Tehran,
Iran.
E-mail: B.moomivand@qmb.ir

Department of Mathematics and Statistics,
University of Northern British Columbia,
Prince George, BC,
Canada.
E-mail: Pranesh.Kumar@unbc.ca

Abstract:

Fuzzy entropy is the entropy of a fuzzy variable, loosely representing the information of uncertainty. This paper, first examines both previous membership and credibility based entropy measures in fuzzy environment, and then suggests an extended credibility based measure which satisfies mostly in Du Luca and Termini axioms. Furthermore, using credibility and the proposed measure, the relative entropy is defined to measure uncertainty between fuzzy numbers. Finally we provide some properties of this Credibility based fuzzy entropy measure and to clarify, give some examples.



1: Paper Source PDF document

Paper's Title:

Robust Error Analysis of Solutions to Nonlinear Volterra Integral Equation in Lp Spaces

Author(s):

Hamid Baghani, Javad Farokhi-Ostad and Omid Baghani

Department of Mathematics, Faculty of Mathematics,
University of Sistan and Baluchestan, P.O. Box 98135-674, Zahedan,
Iran.
E-mail: h.baghani@gmail.com

Department of Mathematics, Faculty of Basic Sciences,
Birjand University of Technology, Birjand,
Iran.
E-mail: j.farrokhi@birjandut.ac.ir

Department of Mathematics and Computer Sciences,
Hakim Sabzevari University, P.O. Box 397, Sabzevar,
Iran.
E-mail: o.baghani@gmail.com

Abstract:

In this paper, we propose a novel strategy for proving an important inequality for a contraction integral equations. The obtained inequality allows us to express our iterative algorithm using a "for loop" rather than a "while loop". The main tool used in this paper is the fixed point theorem in the Lebesgue space. Also, a numerical example shows the efficiency and the accuracy of the proposed scheme.



1: Paper Source PDF document

Paper's Title:

A Comparison Between Two Different Stochastic Epidemic Models with Respect to the Entropy

Author(s):

Farzad Fatehi and Tayebe Waezizadeh

Department of Mathematics,
University of Sussex,
Brighton BN1 9QH,
UK.
E-mail: f.fatehi@sussex.ac.uk
URL: http://www.sussex.ac.uk/profiles/361251

Department of Pure Mathematics, Faculty of Mathematics and Computer,
Shahid Bahonar University of Kerman,
Kerman 76169-14111,
Iran.
E-mail: waezizadeh@uk.ac.ir
URL: http://academicstaff.uk.ac.ir/en/tavaezizadeh

Abstract:

In this paper at first a brief history of mathematical models is presented with the aim to clarify the reliability of stochastic models over deterministic models. Next, the necessary background about random variables and stochastic processes, especially Markov chains and the entropy are introduced. After that, entropy of SIR stochastic models is computed and it is proven that an epidemic will disappear after a long time. Entropy of a stochastic mathematical model determines the average uncertainty about the outcome of that random experiment. At the end, we introduce a chain binomial epidemic model and compute its entropy, which is then compared with the DTMC SIR epidemic model to show which one is nearer to reality.


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