Username   Password       Forgot your password?  Forgot your username? 


Volume 13 - 2017

Volume 12 - 2016

Volume 11 - 2015

Volume 10 - 2014

Volume 9 - 2013

Volume 8 - 2012

Volume 7 - 2011

Volume 6 - 2010

Volume 5 - 2009

Volume 4 - 2008

Volume 3 - 2007

Volume 2 - 2006


Detailed review of:

Measurement Uncertainty: An Approach via the Mathematical Theory of Evidence





Springer, London




Simona Salicone




Measurement Uncertainty: An Approach via the Mathematical Theory of Evidence


Year of Publication














Krishna B. Misra




Review published in IJPE, Vol. 5, No. 3, April 2009, p. 282. 


The book consists of 9 chapters as follows:



 2 pages

Chapter 1

Uncertainty in Measurement

 14 Pages

Chapter 2

Fuzzy Variables and Measurement Uncertainty

 15 Pages

Chapter 3

The Theory of Evidence

 41 Pages

Chapter 4

Random-Fuzzy Variables

 13 Pages

Chapter 5

Construction of Random-Fuzzy Variables

 12 Pages

Chapter 6

Fuzzy Operators

 26 Pages

Chapter 7

The Mathematics of Random-Fuzzy Variables

 70 Pages

Chapter 8

Representation of Random-Fuzzy Variables

 2 Pages

Chapter 9

Decision-Making Rules with Random-Fuzzy Variables

 26 Pages


List of Symbols

 2 Pages



 2 Pages



 2 Pages


This is a very useful introductory book for anyone who is interested in the problem of uncertainty associated with measurement of physical and theoretical quantities.


Reliability engineers invariably face this problem while analyzing life data which is often incomplete or inaccurate, or while using a particular failure model and in computing parameters of interest including reliability itself. The probabilistic approach of handling uncertainty by specifying mean and variance along with confidence interval has not been found adequate and satisfactory in practice and in taking decisions based on that, primarily due to problem of estimating probability density functions. The book is primarily aimed at the scientists and engineers who come across very often the problem of uncertainty of measurement, data, and models in their respective fields. The information about uncertainty helps in deciding the mathematical approach to a physical problem and also in making decision in presence of uncertainties. The layout of chapters of the book indeed has been logically arranged for a beginner to understand the essence and intricacies of possibility theory and the evidence theory. Starting with discussion of theory of error, the author leads to theory of uncertainty and modern methods of treating it. Although today there are several exhaustive books available on the subject of fuzzy sets theory or evidence theory but the author must be complimented to have produced such a compact book on the subject while discussing several practical examples from various fields in an effort to make the understanding of the abstract subject quite lucid to a beginner. Chapters describing probability-possibility transformation, how to construct random-fuzzy variable, fuzzy operators, decision making rules with random fuzzy variable are quite interesting and informative and replete with current developments in the area.
The reviewer would like to recommend this 228 pages book to anyone who would like to know recent developments to tackle the problem of uncertainty of measurements.

                                                                                                                                     Krishna  B. Misra

Review published in the International Journal of Performability Engineeringin Vol. 5, No. 3, April 2009, p. 282.


This site uses encryption for transmitting your passwords.