Linear Models in the Mathematics of Uncertainty - Studies in Computational Intelligence
Linear Models in the Mathematics of Uncertainty - Studies in Computational Intelligence
paperback
Published:
7 March, 2015
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Description
The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable.
In this book, we examine cases where the number of data points is
small (effects of nuclear warfare), where the experiment is not repeatable (the breakup of the former Soviet Union), and where the data is derived from expert opinion (how conservative is a political party). In all these cases the data is difficult to measure and an assumption of randomness and/or statistical validity is questionable.
We apply our methods to real world issues in international relations such as nuclear deterrence, smart power, and cooperative threat reduction. We next apply our methods to issues in comparative politics such as successful democratization, quality of life, economic freedom, political stability, and failed states. Finally, issues involving deaf and hard of hearing children are explored.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9783642438806 |
| ISBN10 | 3642438806 |
| Number Of Pages | 265 |
| Item Weight | 1000 g |
| Publisher / Reseller | Springer-Verlag Berlin and Heidelberg GmbH & Co. KG |
| Format | paperback |
| Edition | 2013 ed. |
Media Reviews
From the reviews:
“The research monograph is devoted to a plethora of decision-making problems whose structure involves combinations (aggregations) of causal factors. … the material is carefully structured and makes the book self-contained and easy to read to novices and those not fully familiar with the background ideas. … This coherently organized reading … will offer the reader a breadth and rigor of the technology of fuzzy sets and comes as a testimony to the need and usefulness of the technology of coping with uncertainty to real-world problems.” (Witold Pedrycz, zbMATH, Vol. 1268, 2013)