Overview
- This books describes and discusses linear models in the mathematics of uncertainty including analytic hierarchy method, data fusion, and evidence theory
- This book also provides some applications of these methods to a range of different practical situations
- Written by leading experts in the field
Part of the book series: Studies in Computational Intelligence (SCI)
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Table of contents (15 chapters)
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Front Matter
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Mathematics of Uncertainty
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Front Matter
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Part III Applications
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The Problems
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Front Matter
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Analysis of Results
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Front Matter
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Keywords
About this book
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.
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)Authors and Affiliations
Bibliographic Information
Book Title: Linear Models in the Mathematics of Uncertainty
Authors: John N. Mordeson, Mark J. Wierman, Terry D. Clark, Alex Pham, Michael A. Redmond
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-35224-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-35223-2Published: 02 February 2013
Softcover ISBN: 978-3-642-43880-6Published: 07 March 2015
eBook ISBN: 978-3-642-35224-9Published: 01 February 2013
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXVIII, 265
Number of Illustrations: 7 b/w illustrations, 8 illustrations in colour
Topics: Computational Intelligence
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